[{"OA_place":"publisher","_id":"12378","degree_awarded":"PhD","abstract":[{"text":"Environmental cues influence the highly dynamic morphology of microglia. Strategies to \r\ncharacterize these changes usually involve user-selected morphometric features, which \r\npreclude the identification of a spectrum of context-dependent morphological phenotypes. \r\nHere, we develop MorphOMICs, a topological data analysis approach, which enables semi\u0002automatic mapping of microglial morphology into an atlas of cue-dependent phenotypes,\r\novercomes feature-selection bias and minimizes biological variability. \r\nFirst, with MorphOMICs we derive the morphological spectrum of microglia across seven \r\nbrain regions during postnatal development and in two distinct Alzheimer’s disease \r\ndegeneration mouse models. We uncover region-specific and sexually dimorphic\r\nmorphological trajectories, with females showing an earlier morphological shift than males in \r\nthe degenerating brain. Overall, we demonstrate that both long primary- and short terminal \r\nprocesses provide distinct insights to morphological phenotypes. Moreover, using machine \r\nlearning to map novel condition on the spectrum, we observe that microglia morphologies \r\nreflect a dose-dependent adaptation upon ketamine anesthesia and do not recover to control \r\nmorphologies.\r\nNext, we took advantage of MorphOMICs to build a high-resolution and layer-specific map of \r\nmicroglial morphological spectrum in the retina, covering postnatal development and rd10 \r\ndegeneration. Here, following photoreceptor death, microglia assume an early development\u0002like morphology. Finally, we map microglial morphology following optic nerve crush on the \r\nretinal spectrum and observe a layer- and sex-dependent response. \r\nOverall, MorphOMICs opens a new perspective to analyze microglial morphology across \r\nmultiple conditions, and provides a novel tool to characterize microglial morphology beyond \r\nthe traditionally dichotomized view of microglia.","lang":"eng"}],"page":"142","oa":1,"related_material":{"record":[{"id":"12244","status":"public","relation":"part_of_dissertation"}]},"citation":{"mla":"Colombo, Gloria. <i>MorphOMICs, a Tool for Mapping Microglial Morphology, Reveals Brain Region- and Sex-Dependent Phenotypes</i>. Institute of Science and Technology Austria, 2022, doi:<a href=\"https://doi.org/10.15479/at:ista:12378\">10.15479/at:ista:12378</a>.","ieee":"G. Colombo, “MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes,” Institute of Science and Technology Austria, 2022.","ista":"Colombo G. 2022. MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes. Institute of Science and Technology Austria.","chicago":"Colombo, Gloria. “MorphOMICs, a Tool for Mapping Microglial Morphology, Reveals Brain Region- and Sex-Dependent Phenotypes.” Institute of Science and Technology Austria, 2022. <a href=\"https://doi.org/10.15479/at:ista:12378\">https://doi.org/10.15479/at:ista:12378</a>.","ama":"Colombo G. MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes. 2022. doi:<a href=\"https://doi.org/10.15479/at:ista:12378\">10.15479/at:ista:12378</a>","apa":"Colombo, G. (2022). <i>MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:12378\">https://doi.org/10.15479/at:ista:12378</a>","short":"G. Colombo, MorphOMICs, a Tool for Mapping Microglial Morphology, Reveals Brain Region- and Sex-Dependent Phenotypes, Institute of Science and Technology Austria, 2022."},"month":"11","type":"dissertation","publisher":"Institute of Science and Technology Austria","oa_version":"Published Version","corr_author":"1","tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png"},"date_updated":"2026-04-07T14:29:41Z","language":[{"iso":"eng"}],"acknowledged_ssus":[{"_id":"PreCl"},{"_id":"Bio"},{"_id":"ScienComp"}],"doi":"10.15479/at:ista:12378","ddc":["570"],"year":"2022","date_published":"2022-11-11T00:00:00Z","project":[{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program","call_identifier":"H2020"}],"date_created":"2023-01-25T14:27:43Z","title":"MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes","author":[{"full_name":"Colombo, Gloria","first_name":"Gloria","orcid":"0000-0001-9434-8902","last_name":"Colombo","id":"3483CF6C-F248-11E8-B48F-1D18A9856A87"}],"ec_funded":1,"file":[{"embargo_to":"open_access","file_size":23890382,"date_created":"2023-01-25T14:31:32Z","creator":"cchlebak","file_name":"Gloria_Colombo_Thesis.docx","access_level":"closed","file_id":"12379","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","checksum":"8cd3ddfe9b53381dcf086023d8d8893a","date_updated":"2023-04-12T22:30:03Z","relation":"source_file"},{"date_created":"2023-01-25T14:31:36Z","creator":"cchlebak","file_size":13802421,"file_id":"12380","access_level":"open_access","checksum":"8af4319c18b516e8758e9a6cb02b103b","content_type":"application/pdf","embargo":"2023-04-11","relation":"main_file","date_updated":"2023-04-12T22:30:03Z","file_name":"Gloria_Colombo_Thesis.pdf"}],"file_date_updated":"2023-04-12T22:30:03Z","day":"11","publication_identifier":{"issn":["2663-337X"]},"alternative_title":["ISTA Thesis"],"supervisor":[{"orcid":"0000-0001-8635-0877","id":"36ACD32E-F248-11E8-B48F-1D18A9856A87","last_name":"Siegert","full_name":"Siegert, Sandra","first_name":"Sandra"}],"status":"public","has_accepted_license":"1","publication_status":"published","article_processing_charge":"No","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","department":[{"_id":"GradSch"},{"_id":"SaSi"}]},{"year":"2022","doi":"10.15479/at:ista:11388","ddc":["576"],"title":"The genetic basis of complex traits studied via analysis of evolve and resequence experiments","author":[{"orcid":"0000-0002-9849-498X","id":"43FE426A-F248-11E8-B48F-1D18A9856A87","last_name":"Belohlavy","full_name":"Belohlavy, Stefanie","first_name":"Stefanie"}],"date_created":"2022-05-16T16:49:18Z","file":[{"file_size":8247240,"date_created":"2022-05-19T13:03:13Z","creator":"sbelohla","file_name":"thesis_sb_final_pdfa.pdf","file_id":"11398","access_level":"open_access","content_type":"application/pdf","checksum":"4d75e6a619df7e8a9d6e840aee182380","date_updated":"2023-05-20T22:30:03Z","embargo":"2023-05-19","relation":"main_file"},{"date_updated":"2023-05-20T22:30:03Z","relation":"source_file","access_level":"closed","file_id":"11399","content_type":"application/x-zip-compressed","checksum":"7a5d8b6dd0ca00784f860075b0a7d8f0","file_name":"thesis_sb_final.zip","creator":"sbelohla","date_created":"2022-05-19T13:07:47Z","file_size":7094,"embargo_to":"open_access"}],"date_published":"2022-05-18T00:00:00Z","file_date_updated":"2023-05-20T22:30:03Z","publication_status":"published","department":[{"_id":"GradSch"},{"_id":"NiBa"}],"article_processing_charge":"No","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","day":"18","publication_identifier":{"isbn":["978-3-99078-018-3"]},"alternative_title":["ISTA Thesis"],"has_accepted_license":"1","supervisor":[{"first_name":"Nicholas H","full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","orcid":"0000-0002-8548-5240"}],"status":"public","OA_place":"publisher","page":"98","oa":1,"related_material":{"record":[{"status":"public","id":"6713","relation":"part_of_dissertation"}]},"type":"dissertation","citation":{"ieee":"S. Belohlavy, “The genetic basis of complex traits studied via analysis of evolve and resequence experiments,” Institute of Science and Technology Austria, 2022.","mla":"Belohlavy, Stefanie. <i>The Genetic Basis of Complex Traits Studied via Analysis of Evolve and Resequence Experiments</i>. Institute of Science and Technology Austria, 2022, doi:<a href=\"https://doi.org/10.15479/at:ista:11388\">10.15479/at:ista:11388</a>.","chicago":"Belohlavy, Stefanie. “The Genetic Basis of Complex Traits Studied via Analysis of Evolve and Resequence Experiments.” Institute of Science and Technology Austria, 2022. <a href=\"https://doi.org/10.15479/at:ista:11388\">https://doi.org/10.15479/at:ista:11388</a>.","ista":"Belohlavy S. 2022. The genetic basis of complex traits studied via analysis of evolve and resequence experiments. Institute of Science and Technology Austria.","ama":"Belohlavy S. The genetic basis of complex traits studied via analysis of evolve and resequence experiments. 2022. doi:<a href=\"https://doi.org/10.15479/at:ista:11388\">10.15479/at:ista:11388</a>","apa":"Belohlavy, S. (2022). <i>The genetic basis of complex traits studied via analysis of evolve and resequence experiments</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:11388\">https://doi.org/10.15479/at:ista:11388</a>","short":"S. Belohlavy, The Genetic Basis of Complex Traits Studied via Analysis of Evolve and Resequence Experiments, Institute of Science and Technology Austria, 2022."},"month":"05","_id":"11388","degree_awarded":"PhD","abstract":[{"lang":"eng","text":"In evolve and resequence experiments, a population is sequenced, subjected to selection and\r\nthen sequenced again, so that genetic changes before and after selection can be observed at\r\nthe genetic level. Here, I use these studies to better understand the genetic basis of complex\r\ntraits - traits which depend on more than a few genes.\r\nIn the first chapter, I discuss the first evolve and resequence experiment, in which a population\r\nof mice, the so-called \"Longshanks\" mice, were selected for tibia length while their body mass\r\nwas kept constant. The full pedigree is known. We observed a selection response on all\r\nchromosomes and used the infinitesimal model with linkage, a model which assumes an infinite\r\nnumber of genes with infinitesimally small effect sizes, as a null model. Results implied a very\r\npolygenic basis with a few loci of major effect standing out and changing in parallel. There\r\nwas large variability between the different chromosomes in this study, probably due to LD.\r\nIn chapter two, I go on to discuss the impact of LD, on the variability in an allele-frequency\r\nbased summary statistic, giving an equation based on the initial allele frequencies, average\r\npairwise LD, and the first four moments of the haplotype block copy number distribution. I\r\ndescribe this distribution by referring back to the founder generation. I then demonstrate\r\nhow to infer selection via a maximum likelihood scheme on the example of a single locus and\r\ndiscuss how to extend this to more realistic scenarios.\r\nIn chapter three, I discuss the second evolve and resequence experiment, in which a small\r\npopulation of Drosophila melanogaster was selected for increased pupal case size over 6\r\ngenerations. The experiment was highly replicated with 27 lines selected within family and a\r\nknown pedigree. We observed a phenotypic selection response of over one standard deviation.\r\nI describe the patterns in allele frequency data, including allele frequency changes and patterns\r\nof heterozygosity, and give ideas for future work."}],"tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png"},"date_updated":"2026-04-07T14:29:57Z","language":[{"iso":"eng"}],"publisher":"Institute of Science and Technology Austria","oa_version":"Published Version","corr_author":"1"},{"publication_identifier":{"eissn":["1878-1551"],"issn":["1534-5807"]},"day":"10","status":"public","main_file_link":[{"open_access":"1","url":"https://www.sciencedirect.com/science/article/pii/S1534580721009497"}],"isi":1,"external_id":{"pmid":["34919802"],"isi":["000768933800005"]},"publication_status":"published","article_processing_charge":"No","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","department":[{"_id":"MiSi"},{"_id":"EM-Fac"},{"_id":"NanoFab"},{"_id":"BjHo"}],"ddc":["570"],"doi":"10.1016/j.devcel.2021.11.024","acknowledgement":"We thank N. Darwish-Miranda, F. Leite, F.P. Assen, and A. Eichner for advice and help with experiments. We thank J. Renkawitz, E. Kiermaier, A. Juanes Garcia, and M. Avellaneda for critical reading of the manuscript. We thank M. Driscoll for advice on fluorescent labeling of collagen gels. This research was supported by the Scientific Service Units (SSUs) of IST Austria through resources provided by Molecular Biology Services/Lab Support Facility (LSF)/Bioimaging Facility/Electron Microscopy Facility. This work was funded by grants from the European Research Council ( CoG 724373 ) and the Austrian Science Foundation (FWF) to M.S. F.G. received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 747687.","intvolume":"        57","publication":"Developmental Cell","year":"2022","pmid":1,"scopus_import":"1","volume":57,"date_published":"2022-01-10T00:00:00Z","article_type":"original","project":[{"_id":"260AA4E2-B435-11E9-9278-68D0E5697425","grant_number":"747687","name":"Mechanical Adaptation of Lamellipodial Actin Networks in Migrating Cells","call_identifier":"H2020"},{"call_identifier":"H2020","name":"Cellular Navigation Along Spatial Gradients","_id":"25FE9508-B435-11E9-9278-68D0E5697425","grant_number":"724373"}],"ec_funded":1,"title":"WASp triggers mechanosensitive actin patches to facilitate immune cell migration in dense tissues","author":[{"full_name":"Gaertner, Florian","first_name":"Florian","last_name":"Gaertner"},{"full_name":"Dos Reis Rodrigues, Patricia","first_name":"Patricia","orcid":"0000-0003-1681-508X","last_name":"Dos Reis Rodrigues","id":"26E95904-5160-11E9-9C0B-C5B0DC97E90F"},{"full_name":"De Vries, Ingrid","first_name":"Ingrid","last_name":"De Vries","id":"4C7D837E-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Hons, Miroslav","first_name":"Miroslav","orcid":"0000-0002-6625-3348","last_name":"Hons","id":"4167FE56-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Juan","full_name":"Aguilera, Juan","last_name":"Aguilera"},{"full_name":"Riedl, Michael","first_name":"Michael","orcid":"0000-0003-4844-6311","last_name":"Riedl","id":"3BE60946-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Leithner, Alexander F","first_name":"Alexander F","orcid":"0000-0002-1073-744X","last_name":"Leithner","id":"3B1B77E4-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Tasciyan, Saren","first_name":"Saren","orcid":"0000-0003-1671-393X","last_name":"Tasciyan","id":"4323B49C-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Kopf, Aglaja","first_name":"Aglaja","orcid":"0000-0002-2187-6656","id":"31DAC7B6-F248-11E8-B48F-1D18A9856A87","last_name":"Kopf"},{"orcid":"0000-0001-5145-4609","last_name":"Merrin","id":"4515C308-F248-11E8-B48F-1D18A9856A87","full_name":"Merrin, Jack","first_name":"Jack"},{"last_name":"Zheden","id":"39C5A68A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-9438-4783","first_name":"Vanessa","full_name":"Zheden, Vanessa"},{"full_name":"Kaufmann, Walter","first_name":"Walter","orcid":"0000-0001-9735-5315","id":"3F99E422-F248-11E8-B48F-1D18A9856A87","last_name":"Kaufmann"},{"full_name":"Hauschild, Robert","first_name":"Robert","orcid":"0000-0001-9843-3522","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","last_name":"Hauschild"},{"first_name":"Michael K","full_name":"Sixt, Michael K","id":"41E9FBEA-F248-11E8-B48F-1D18A9856A87","last_name":"Sixt","orcid":"0000-0002-6620-9179"}],"date_created":"2022-01-30T23:01:33Z","issue":"1","quality_controlled":"1","publisher":"Cell Press","corr_author":"1","oa_version":"Published Version","date_updated":"2026-06-20T22:31:00Z","language":[{"iso":"eng"}],"tmp":{"image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode"},"acknowledged_ssus":[{"_id":"LifeSc"},{"_id":"Bio"},{"_id":"EM-Fac"}],"_id":"10703","abstract":[{"lang":"eng","text":"When crawling through the body, leukocytes often traverse tissues that are densely packed with extracellular matrix and other cells, and this raises the question: How do leukocytes overcome compressive mechanical loads? Here, we show that the actin cortex of leukocytes is mechanoresponsive and that this responsiveness requires neither force sensing via the nucleus nor adhesive interactions with a substrate. Upon global compression of the cell body as well as local indentation of the plasma membrane, Wiskott-Aldrich syndrome protein (WASp) assembles into dot-like structures, providing activation platforms for Arp2/3 nucleated actin patches. These patches locally push against the external load, which can be obstructing collagen fibers or other cells, and thereby create space to facilitate forward locomotion. We show in vitro and in vivo that this WASp function is rate limiting for ameboid leukocyte migration in dense but not in loose environments and is required for trafficking through diverse tissues such as skin and lymph nodes."}],"oa":1,"page":"47-62.e9","type":"journal_article","month":"01","citation":{"apa":"Gaertner, F., Dos Reis Rodrigues, P., de Vries, I., Hons, M., Aguilera, J., Riedl, M., … Sixt, M. K. (2022). WASp triggers mechanosensitive actin patches to facilitate immune cell migration in dense tissues. <i>Developmental Cell</i>. Cell Press. <a href=\"https://doi.org/10.1016/j.devcel.2021.11.024\">https://doi.org/10.1016/j.devcel.2021.11.024</a>","short":"F. Gaertner, P. Dos Reis Rodrigues, I. de Vries, M. Hons, J. Aguilera, M. Riedl, A.F. Leithner, S. Tasciyan, A. Kopf, J. Merrin, V. Zheden, W. Kaufmann, R. Hauschild, M.K. Sixt, Developmental Cell 57 (2022) 47–62.e9.","ista":"Gaertner F, Dos Reis Rodrigues P, de Vries I, Hons M, Aguilera J, Riedl M, Leithner AF, Tasciyan S, Kopf A, Merrin J, Zheden V, Kaufmann W, Hauschild R, Sixt MK. 2022. WASp triggers mechanosensitive actin patches to facilitate immune cell migration in dense tissues. Developmental Cell. 57(1), 47–62.e9.","chicago":"Gaertner, Florian, Patricia Dos Reis Rodrigues, Ingrid de Vries, Miroslav Hons, Juan Aguilera, Michael Riedl, Alexander F Leithner, et al. “WASp Triggers Mechanosensitive Actin Patches to Facilitate Immune Cell Migration in Dense Tissues.” <i>Developmental Cell</i>. Cell Press, 2022. <a href=\"https://doi.org/10.1016/j.devcel.2021.11.024\">https://doi.org/10.1016/j.devcel.2021.11.024</a>.","ama":"Gaertner F, Dos Reis Rodrigues P, de Vries I, et al. WASp triggers mechanosensitive actin patches to facilitate immune cell migration in dense tissues. <i>Developmental Cell</i>. 2022;57(1):47-62.e9. doi:<a href=\"https://doi.org/10.1016/j.devcel.2021.11.024\">10.1016/j.devcel.2021.11.024</a>","ieee":"F. Gaertner <i>et al.</i>, “WASp triggers mechanosensitive actin patches to facilitate immune cell migration in dense tissues,” <i>Developmental Cell</i>, vol. 57, no. 1. Cell Press, p. 47–62.e9, 2022.","mla":"Gaertner, Florian, et al. “WASp Triggers Mechanosensitive Actin Patches to Facilitate Immune Cell Migration in Dense Tissues.” <i>Developmental Cell</i>, vol. 57, no. 1, Cell Press, 2022, p. 47–62.e9, doi:<a href=\"https://doi.org/10.1016/j.devcel.2021.11.024\">10.1016/j.devcel.2021.11.024</a>."},"related_material":{"record":[{"relation":"dissertation_contains","id":"20149","status":"public"},{"relation":"dissertation_contains","id":"12726","status":"public"},{"id":"14530","status":"public","relation":"dissertation_contains"},{"relation":"dissertation_contains","status":"public","id":"12401"}]}},{"_id":"12401","abstract":[{"text":"Detachment of the cancer cells from the bulk of the tumor is the first step of metastasis, which\r\nis the primary cause of cancer related deaths. It is unclear, which factors contribute to this step.\r\nRecent studies indicate a crucial role of the tumor microenvironment in malignant\r\ntransformation and metastasis. Studying cancer cell invasion and detachments quantitatively in\r\nthe context of its physiological microenvironment is technically challenging. Especially, precise\r\ncontrol of microenvironmental properties in vivo is currently not possible. Here, I studied the\r\nrole of microenvironment geometry in the invasion and detachment of cancer cells from the\r\nbulk with a simplistic and reductionist approach. In this approach, I engineered microfluidic\r\ndevices to mimic a pseudo 3D extracellular matrix environment, where I was able to\r\nquantitatively tune the geometrical configuration of the microenvironment and follow tumor\r\ncells with fluorescence live imaging. To aid quantitative analysis I developed a widely applicable\r\nsoftware application to automatically analyze and visualize particle tracking data.\r\nQuantitative analysis of tumor cell invasion in isotropic and anisotropic microenvironments\r\nshowed that heterogeneity in the microenvironment promotes faster invasion and more\r\nfrequent detachment of cells. These observations correlated with overall higher speed of cells at\r\nthe edge of the bulk of the cells. In heterogeneous microenvironments cells preferentially\r\npassed through larger pores, thus invading areas of least resistance and generating finger-like\r\ninvasive structures. The detachments occurred mostly at the tips of these structures.\r\nTo investigate the potential mechanism, we established a two dimensional model to simulate\r\nactive Brownian particles representing the cell nuclei dynamics. These simulations backed our in\r\nvitro observations without the need of precise fitting the simulation parameters. Our model\r\nsuggests the importance of the pore heterogeneity in the direction perpendicular to the\r\norientation of bias field (lateral heterogeneity), which causes the interface roughening.","lang":"eng"}],"degree_awarded":"PhD","oa":1,"page":"105","related_material":{"record":[{"relation":"part_of_dissertation","id":"7885","status":"public"},{"id":"10703","status":"public","relation":"part_of_dissertation"},{"id":"679","status":"public","relation":"part_of_dissertation"},{"relation":"part_of_dissertation","id":"9429","status":"public"}]},"type":"dissertation","citation":{"chicago":"Tasciyan, Saren. “Role of Microenvironment Heterogeneity in Cancer Cell Invasion.” Institute of Science and Technology Austria, 2022. <a href=\"https://doi.org/10.15479/at:ista:12401\">https://doi.org/10.15479/at:ista:12401</a>.","ista":"Tasciyan S. 2022. Role of microenvironment heterogeneity in cancer cell invasion. Institute of Science and Technology Austria.","ama":"Tasciyan S. Role of microenvironment heterogeneity in cancer cell invasion. 2022. doi:<a href=\"https://doi.org/10.15479/at:ista:12401\">10.15479/at:ista:12401</a>","apa":"Tasciyan, S. (2022). <i>Role of microenvironment heterogeneity in cancer cell invasion</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:12401\">https://doi.org/10.15479/at:ista:12401</a>","short":"S. Tasciyan, Role of Microenvironment Heterogeneity in Cancer Cell Invasion, Institute of Science and Technology Austria, 2022.","mla":"Tasciyan, Saren. <i>Role of Microenvironment Heterogeneity in Cancer Cell Invasion</i>. Institute of Science and Technology Austria, 2022, doi:<a href=\"https://doi.org/10.15479/at:ista:12401\">10.15479/at:ista:12401</a>.","ieee":"S. Tasciyan, “Role of microenvironment heterogeneity in cancer cell invasion,” Institute of Science and Technology Austria, 2022."},"month":"12","OA_place":"publisher","publisher":"Institute of Science and Technology Austria","corr_author":"1","oa_version":"Published Version","date_updated":"2026-04-14T09:07:14Z","language":[{"iso":"eng"}],"date_published":"2022-12-22T00:00:00Z","date_created":"2023-01-26T11:55:16Z","author":[{"id":"4323B49C-F248-11E8-B48F-1D18A9856A87","last_name":"Tasciyan","orcid":"0000-0003-1671-393X","first_name":"Saren","full_name":"Tasciyan, Saren"}],"title":"Role of microenvironment heterogeneity in cancer cell invasion","file":[{"creator":"cchlebak","date_created":"2023-01-26T11:58:14Z","file_size":42059787,"relation":"main_file","date_updated":"2023-12-21T23:30:03Z","embargo":"2023-12-20","access_level":"open_access","file_id":"12402","checksum":"cc4a2b4a7e3c4ee8ef7f2dbf909b12bd","content_type":"application/pdf","file_name":"PhD-Thesis_Saren Tasciyan_formatted_aftercrash_fixed_600dpi_95pc_final_PDFA3b.pdf"},{"file_name":"Source Files - Saren Tasciyan - PhD Thesis.zip","file_id":"12403","access_level":"closed","content_type":"application/x-zip-compressed","checksum":"f1b4ca98b8ab0cb043b1830971e9bd9c","date_updated":"2023-12-21T23:30:03Z","relation":"source_file","embargo_to":"open_access","file_size":261256696,"date_created":"2023-01-26T12:00:10Z","creator":"cchlebak"}],"ddc":["610"],"doi":"10.15479/at:ista:12401","year":"2022","day":"22","publication_identifier":{"issn":["2663-337X"]},"has_accepted_license":"1","status":"public","supervisor":[{"full_name":"Sixt, Michael K","first_name":"Michael K","orcid":"0000-0002-6620-9179","last_name":"Sixt","id":"41E9FBEA-F248-11E8-B48F-1D18A9856A87"}],"alternative_title":["ISTA Thesis"],"publication_status":"published","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","article_processing_charge":"No","department":[{"_id":"GradSch"},{"_id":"MiSi"}],"file_date_updated":"2023-12-21T23:30:03Z"},{"related_material":{"record":[{"id":"11653","status":"public","relation":"research_data"},{"id":"19386","status":"public","relation":"dissertation_contains"}]},"month":"10","type":"journal_article","citation":{"short":"M.N. Elkrewi, U. Khauratovich, M.A. Toups, V.K. Bett, A. Mrnjavac, A. Macon, C. Fraisse, L. Sax, A.K. Huylmans, F. Hontoria, B. Vicoso, Genetics 222 (2022).","apa":"Elkrewi, M. N., Khauratovich, U., Toups, M. A., Bett, V. K., Mrnjavac, A., Macon, A., … Vicoso, B. (2022). ZW sex-chromosome evolution and contagious parthenogenesis in Artemia brine shrimp. <i>Genetics</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/genetics/iyac123\">https://doi.org/10.1093/genetics/iyac123</a>","chicago":"Elkrewi, Marwan N, Uladzislava Khauratovich, Melissa A Toups, Vincent K Bett, Andrea Mrnjavac, Ariana Macon, Christelle Fraisse, et al. “ZW Sex-Chromosome Evolution and Contagious Parthenogenesis in Artemia Brine Shrimp.” <i>Genetics</i>. Oxford University Press, 2022. <a href=\"https://doi.org/10.1093/genetics/iyac123\">https://doi.org/10.1093/genetics/iyac123</a>.","ista":"Elkrewi MN, Khauratovich U, Toups MA, Bett VK, Mrnjavac A, Macon A, Fraisse C, Sax L, Huylmans AK, Hontoria F, Vicoso B. 2022. ZW sex-chromosome evolution and contagious parthenogenesis in Artemia brine shrimp. Genetics. 222(2), iyac123.","ama":"Elkrewi MN, Khauratovich U, Toups MA, et al. ZW sex-chromosome evolution and contagious parthenogenesis in Artemia brine shrimp. <i>Genetics</i>. 2022;222(2). doi:<a href=\"https://doi.org/10.1093/genetics/iyac123\">10.1093/genetics/iyac123</a>","mla":"Elkrewi, Marwan N., et al. “ZW Sex-Chromosome Evolution and Contagious Parthenogenesis in Artemia Brine Shrimp.” <i>Genetics</i>, vol. 222, no. 2, iyac123, Oxford University Press, 2022, doi:<a href=\"https://doi.org/10.1093/genetics/iyac123\">10.1093/genetics/iyac123</a>.","ieee":"M. N. Elkrewi <i>et al.</i>, “ZW sex-chromosome evolution and contagious parthenogenesis in Artemia brine shrimp,” <i>Genetics</i>, vol. 222, no. 2. Oxford University Press, 2022."},"oa":1,"abstract":[{"text":"Eurasian brine shrimp (genus Artemia) have closely related sexual and asexual lineages of parthenogenetic females, which produce rare males at low frequencies. Although they are known to have ZW chromosomes, these are not well characterized, and it is unclear whether they are shared across the clade. Furthermore, the underlying genetic architecture of the transmission of asexuality, which can occur when rare males mate with closely related sexual females, is not well understood. We produced a chromosome-level assembly for the sexual Eurasian species Artemia sinica and characterized in detail the pair of sex chromosomes of this species. We combined this new assembly with short-read genomic data for the sexual species Artemia sp. Kazakhstan and several asexual lineages of Artemia parthenogenetica, allowing us to perform an in-depth characterization of sex-chromosome evolution across the genus. We identified a small differentiated region of the ZW pair that is shared by all sexual and asexual lineages, supporting the shared ancestry of the sex chromosomes. We also inferred that recombination suppression has spread to larger sections of the chromosome independently in the American and Eurasian lineages. Finally, we took advantage of a rare male, which we backcrossed to sexual females, to explore the genetic basis of asexuality. Our results suggest that parthenogenesis is likely partly controlled by a locus on the Z chromosome, highlighting the interplay between sex determination and asexuality.","lang":"eng"}],"keyword":["Genetics"],"_id":"12248","acknowledged_ssus":[{"_id":"ScienComp"}],"date_updated":"2026-06-20T22:31:10Z","language":[{"iso":"eng"}],"tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png"},"corr_author":"1","oa_version":"Published Version","quality_controlled":"1","publisher":"Oxford University Press","file":[{"file_name":"2022_Genetics_Elkrewi.pdf","date_updated":"2023-01-30T08:59:58Z","relation":"main_file","access_level":"open_access","file_id":"12440","success":1,"content_type":"application/pdf","checksum":"f79ff5383e882ea3f95f3da47a78029d","file_size":1347136,"creator":"dernst","date_created":"2023-01-30T08:59:58Z"}],"issue":"2","ec_funded":1,"date_created":"2023-01-16T09:56:10Z","title":"ZW sex-chromosome evolution and contagious parthenogenesis in Artemia brine shrimp","author":[{"orcid":"0000-0002-5328-7231","last_name":"Elkrewi","id":"0B46FACA-A8E1-11E9-9BD3-79D1E5697425","full_name":"Elkrewi, Marwan N","first_name":"Marwan N"},{"last_name":"Khauratovich","id":"5eba06f4-97d8-11ed-9f8f-d826ebdd9434","full_name":"Khauratovich, Uladzislava","first_name":"Uladzislava"},{"full_name":"Toups, Melissa A","first_name":"Melissa A","orcid":"0000-0002-9752-7380","last_name":"Toups","id":"4E099E4E-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Bett, Vincent K","first_name":"Vincent K","last_name":"Bett","id":"57854184-AAE0-11E9-8D04-98D6E5697425"},{"first_name":"Andrea","full_name":"Mrnjavac, Andrea","last_name":"Mrnjavac","id":"353FAC84-AE61-11E9-8BFC-00D3E5697425"},{"last_name":"Macon","id":"2A0848E2-F248-11E8-B48F-1D18A9856A87","first_name":"Ariana","full_name":"Macon, Ariana"},{"orcid":"0000-0001-8441-5075","id":"32DF5794-F248-11E8-B48F-1D18A9856A87","last_name":"Fraisse","full_name":"Fraisse, Christelle","first_name":"Christelle"},{"full_name":"Sax, Luca","first_name":"Luca","id":"701c5602-97d8-11ed-96b5-b52773c70189","last_name":"Sax"},{"id":"4C0A3874-F248-11E8-B48F-1D18A9856A87","last_name":"Huylmans","orcid":"0000-0001-8871-4961","first_name":"Ann K","full_name":"Huylmans, Ann K"},{"last_name":"Hontoria","first_name":"Francisco","full_name":"Hontoria, Francisco"},{"full_name":"Vicoso, Beatriz","first_name":"Beatriz","orcid":"0000-0002-4579-8306","id":"49E1C5C6-F248-11E8-B48F-1D18A9856A87","last_name":"Vicoso"}],"article_number":"iyac123","article_type":"original","project":[{"grant_number":"715257","_id":"250BDE62-B435-11E9-9278-68D0E5697425","name":"Prevalence and Influence of Sexual Antagonism on Genome Evolution","call_identifier":"H2020"},{"_id":"34ae1506-11ca-11ed-8bc3-c14f4c474396","grant_number":"F8810","name":"The highjacking of meiosis for asexual reproduction"}],"date_published":"2022-10-01T00:00:00Z","volume":222,"year":"2022","publication":"Genetics","pmid":1,"scopus_import":"1","intvolume":"       222","ddc":["570"],"doi":"10.1093/genetics/iyac123","acknowledgement":"This work was supported by the European Research Council under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 715257) and by the Austrian Science Foundation (FWF SFB F88-10).\r\nWe thank the Vicoso group for comments on the manuscript and the ISTA Scientific computing team and the Vienna Biocenter Sequencing facility for technical support.","department":[{"_id":"BeVi"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","article_processing_charge":"No","external_id":{"isi":["000850270300001"],"pmid":["35977389"]},"publication_status":"published","status":"public","has_accepted_license":"1","isi":1,"publication_identifier":{"issn":["1943-2631"]},"day":"01","file_date_updated":"2023-01-30T08:59:58Z"},{"corr_author":"1","oa_version":"Published Version","quality_controlled":"1","publisher":"The Royal Society","language":[{"iso":"eng"}],"date_updated":"2026-06-20T22:31:11Z","tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png"},"abstract":[{"text":"The t-haplotype of mice is a classical model for autosomal transmission distortion. A largely non-recombining variant of the proximal region of chromosome 17, it is transmitted to more than 90% of the progeny of heterozygous males through the disabling of sperm carrying a standard chromosome. While extensive genetic and functional work has shed light on individual genes involved in drive, much less is known about the evolution and function of the rest of its hundreds of genes. Here, we characterize the sequence and expression of dozens of t-specific transcripts and of their chromosome 17 homologues. Many genes showed reduced expression of the t-allele, but an equal number of genes showed increased expression of their t-copy, consistent with increased activity or a newly evolved function. Genes on the t-haplotype had a significantly higher non-synonymous substitution rate than their homologues on the standard chromosome, with several genes harbouring dN/dS ratios above 1. Finally, the t-haplotype has acquired at least two genes from other chromosomes, which show high and tissue-specific expression. These results provide a first overview of the gene content of this selfish element, and support a more dynamic evolutionary scenario than expected of a large genomic region with almost no recombination.","lang":"eng"}],"_id":"10767","citation":{"ama":"Kelemen RK, Elkrewi MN, Lindholm AK, Vicoso B. Novel patterns of expression and recruitment of new genes on the t-haplotype, a mouse selfish chromosome. <i>Proceedings of the Royal Society B: Biological Sciences</i>. 2022;289(1968):20211985. doi:<a href=\"https://doi.org/10.1098/rspb.2021.1985\">10.1098/rspb.2021.1985</a>","chicago":"Kelemen, Réka K, Marwan N Elkrewi, Anna K. Lindholm, and Beatriz Vicoso. “Novel Patterns of Expression and Recruitment of New Genes on the T-Haplotype, a Mouse Selfish Chromosome.” <i>Proceedings of the Royal Society B: Biological Sciences</i>. The Royal Society, 2022. <a href=\"https://doi.org/10.1098/rspb.2021.1985\">https://doi.org/10.1098/rspb.2021.1985</a>.","ista":"Kelemen RK, Elkrewi MN, Lindholm AK, Vicoso B. 2022. Novel patterns of expression and recruitment of new genes on the t-haplotype, a mouse selfish chromosome. Proceedings of the Royal Society B: Biological Sciences. 289(1968), 20211985.","short":"R.K. Kelemen, M.N. Elkrewi, A.K. Lindholm, B. Vicoso, Proceedings of the Royal Society B: Biological Sciences 289 (2022) 20211985.","apa":"Kelemen, R. K., Elkrewi, M. N., Lindholm, A. K., &#38; Vicoso, B. (2022). Novel patterns of expression and recruitment of new genes on the t-haplotype, a mouse selfish chromosome. <i>Proceedings of the Royal Society B: Biological Sciences</i>. The Royal Society. <a href=\"https://doi.org/10.1098/rspb.2021.1985\">https://doi.org/10.1098/rspb.2021.1985</a>","mla":"Kelemen, Réka K., et al. “Novel Patterns of Expression and Recruitment of New Genes on the T-Haplotype, a Mouse Selfish Chromosome.” <i>Proceedings of the Royal Society B: Biological Sciences</i>, vol. 289, no. 1968, The Royal Society, 2022, p. 20211985, doi:<a href=\"https://doi.org/10.1098/rspb.2021.1985\">10.1098/rspb.2021.1985</a>.","ieee":"R. K. Kelemen, M. N. Elkrewi, A. K. Lindholm, and B. Vicoso, “Novel patterns of expression and recruitment of new genes on the t-haplotype, a mouse selfish chromosome,” <i>Proceedings of the Royal Society B: Biological Sciences</i>, vol. 289, no. 1968. The Royal Society, p. 20211985, 2022."},"related_material":{"record":[{"status":"public","id":"17119","relation":"dissertation_contains"},{"id":"19386","status":"public","relation":"dissertation_contains"}]},"type":"journal_article","month":"02","oa":1,"page":"20211985","has_accepted_license":"1","isi":1,"status":"public","day":"09","publication_identifier":{"eissn":["1471-2954"]},"article_processing_charge":"No","department":[{"_id":"BeVi"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","external_id":{"pmid":["35135349"],"isi":["000752812800012"]},"publication_status":"published","file_date_updated":"2022-02-21T08:17:38Z","article_type":"original","project":[{"name":"Prevalence and Influence of Sexual Antagonism on Genome Evolution","call_identifier":"H2020","grant_number":"715257","_id":"250BDE62-B435-11E9-9278-68D0E5697425"}],"date_published":"2022-02-09T00:00:00Z","file":[{"file_name":"2022_ProceedingsRoyalSocB_Kelemen.pdf","checksum":"27042a3706ae52a919fed1ac114bf7bb","content_type":"application/pdf","access_level":"open_access","file_id":"10779","success":1,"date_updated":"2022-02-21T08:17:38Z","relation":"main_file","file_size":2366976,"date_created":"2022-02-21T08:17:38Z","creator":"dernst"}],"issue":"1968","ec_funded":1,"title":"Novel patterns of expression and recruitment of new genes on the t-haplotype, a mouse selfish chromosome","date_created":"2022-02-20T23:01:31Z","author":[{"full_name":"Kelemen, Réka K","first_name":"Réka K","orcid":"0000-0002-8489-9281","id":"48D3F8DE-F248-11E8-B48F-1D18A9856A87","last_name":"Kelemen"},{"orcid":"0000-0002-5328-7231","last_name":"Elkrewi","id":"0B46FACA-A8E1-11E9-9BD3-79D1E5697425","full_name":"Elkrewi, Marwan N","first_name":"Marwan N"},{"last_name":"Lindholm","full_name":"Lindholm, Anna K.","first_name":"Anna K."},{"full_name":"Vicoso, Beatriz","first_name":"Beatriz","orcid":"0000-0002-4579-8306","id":"49E1C5C6-F248-11E8-B48F-1D18A9856A87","last_name":"Vicoso"}],"intvolume":"       289","ddc":["570"],"acknowledgement":"This project has received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 715257) and from the Swiss National Science Foundation (grant no. 310030_189145).\r\nWe thank Jari Garbely of the Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland, for conducting the PCR verification. Barbara\r\nKonig, Gabi Stichel and A.K.L. collected mouse tissue samples, from the field study led by R.K.K. ","doi":"10.1098/rspb.2021.1985","volume":289,"publication":"Proceedings of the Royal Society B: Biological Sciences","year":"2022","scopus_import":"1","pmid":1},{"abstract":[{"text":"Solid-state microwave systems offer strong interactions for fast quantum logic and sensing but photons at telecom wavelength are the ideal choice for high-density low-loss quantum interconnects. A general-purpose interface that can make use of single photon effects requires < 1 input noise quanta, which has remained elusive due to either low efficiency or pump induced heating. Here we demonstrate coherent electro-optic modulation on nanosecond-timescales with only 0.16+0.02−0.01 microwave input noise photons with a total bidirectional transduction efficiency of 8.7% (or up to 15% with 0.41+0.02−0.02), as required for near-term heralded quantum network protocols. The use of short and high-power optical pump pulses also enables near-unity cooperativity of the electro-optic interaction leading to an internal pure conversion efficiency of up to 99.5%. Together with the low mode occupancy this provides evidence for electro-optic laser cooling and vacuum amplification as predicted a decade ago.","lang":"eng"}],"_id":"10924","type":"journal_article","month":"03","related_material":{"record":[{"status":"public","id":"13175","relation":"dissertation_contains"},{"relation":"dissertation_contains","id":"12900","status":"public"},{"id":"18871","status":"public","relation":"dissertation_contains"}]},"citation":{"short":"R. Sahu, W.J. Hease, A.R. Rueda Sanchez, G.M. Arnold, L. Qiu, J.M. Fink, Nature Communications 13 (2022).","apa":"Sahu, R., Hease, W. J., Rueda Sanchez, A. R., Arnold, G. M., Qiu, L., &#38; Fink, J. M. (2022). Quantum-enabled operation of a microwave-optical interface. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-022-28924-2\">https://doi.org/10.1038/s41467-022-28924-2</a>","ama":"Sahu R, Hease WJ, Rueda Sanchez AR, Arnold GM, Qiu L, Fink JM. Quantum-enabled operation of a microwave-optical interface. <i>Nature Communications</i>. 2022;13. doi:<a href=\"https://doi.org/10.1038/s41467-022-28924-2\">10.1038/s41467-022-28924-2</a>","ista":"Sahu R, Hease WJ, Rueda Sanchez AR, Arnold GM, Qiu L, Fink JM. 2022. Quantum-enabled operation of a microwave-optical interface. Nature Communications. 13, 1276.","chicago":"Sahu, Rishabh, William J Hease, Alfredo R Rueda Sanchez, Georg M Arnold, Liu Qiu, and Johannes M Fink. “Quantum-Enabled Operation of a Microwave-Optical Interface.” <i>Nature Communications</i>. Springer Nature, 2022. <a href=\"https://doi.org/10.1038/s41467-022-28924-2\">https://doi.org/10.1038/s41467-022-28924-2</a>.","ieee":"R. Sahu, W. J. Hease, A. R. Rueda Sanchez, G. M. Arnold, L. Qiu, and J. M. Fink, “Quantum-enabled operation of a microwave-optical interface,” <i>Nature Communications</i>, vol. 13. Springer Nature, 2022.","mla":"Sahu, Rishabh, et al. “Quantum-Enabled Operation of a Microwave-Optical Interface.” <i>Nature Communications</i>, vol. 13, 1276, Springer Nature, 2022, doi:<a href=\"https://doi.org/10.1038/s41467-022-28924-2\">10.1038/s41467-022-28924-2</a>."},"oa":1,"arxiv":1,"acknowledged_ssus":[{"_id":"M-Shop"}],"corr_author":"1","oa_version":"Published Version","quality_controlled":"1","publisher":"Springer Nature","date_updated":"2026-06-20T22:31:12Z","language":[{"iso":"eng"}],"tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png"},"article_type":"original","project":[{"call_identifier":"H2020","name":"A Fiber Optic Transceiver for Superconducting Qubits","grant_number":"758053","_id":"26336814-B435-11E9-9278-68D0E5697425"},{"call_identifier":"H2020","name":"Quantum Local Area Networks with Superconducting Qubits","_id":"9B868D20-BA93-11EA-9121-9846C619BF3A","grant_number":"899354"},{"name":"ISTplus - Postdoctoral Fellowships","call_identifier":"H2020","_id":"260C2330-B435-11E9-9278-68D0E5697425","grant_number":"754411"},{"name":"Quantum readout techniques and technologies","call_identifier":"H2020","grant_number":"862644","_id":"237CBA6C-32DE-11EA-91FC-C7463DDC885E"},{"name":"QUANTUM INFORMATION SYSTEMS BEYOND CLASSICAL CAPABILITIES / P5- Integration of Superconducting Quantum Circuits","grant_number":"F07105","_id":"bdb108fd-d553-11ed-ba76-83dc74a9864f"}],"date_published":"2022-03-11T00:00:00Z","file":[{"creator":"dernst","date_created":"2022-03-28T08:02:12Z","file_size":1167492,"date_updated":"2022-03-28T08:02:12Z","relation":"main_file","file_id":"10929","success":1,"access_level":"open_access","checksum":"7c5176db7b8e2ed18a4e0c5aca70a72c","content_type":"application/pdf","file_name":"2022_NatureCommunications_Sahu.pdf"}],"ec_funded":1,"article_number":"1276","date_created":"2022-03-27T22:01:45Z","title":"Quantum-enabled operation of a microwave-optical interface","author":[{"full_name":"Sahu, Rishabh","first_name":"Rishabh","orcid":"0000-0001-6264-2162","last_name":"Sahu","id":"47D26E34-F248-11E8-B48F-1D18A9856A87"},{"first_name":"William J","full_name":"Hease, William J","last_name":"Hease","id":"29705398-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9868-2166"},{"id":"3B82B0F8-F248-11E8-B48F-1D18A9856A87","last_name":"Rueda Sanchez","orcid":"0000-0001-6249-5860","first_name":"Alfredo R","full_name":"Rueda Sanchez, Alfredo R"},{"full_name":"Arnold, Georg M","first_name":"Georg M","orcid":"0000-0003-1397-7876","last_name":"Arnold","id":"3770C838-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Liu","full_name":"Qiu, Liu","id":"45e99c0d-1eb1-11eb-9b96-ed8ab2983cac","last_name":"Qiu","orcid":"0000-0003-4345-4267"},{"full_name":"Fink, Johannes M","first_name":"Johannes M","orcid":"0000-0001-8112-028X","last_name":"Fink","id":"4B591CBA-F248-11E8-B48F-1D18A9856A87"}],"intvolume":"        13","ddc":["530"],"doi":"10.1038/s41467-022-28924-2","acknowledgement":"The authors thank S. Wald and F. Diorico for their help with optical filtering, O. Hosten\r\nand M. Aspelmeyer for equipment, H.G.L. Schwefel for materials and discussions, L.\r\nDrmic and P. Zielinski for software support, and the MIBA workshop at IST Austria for\r\nmachining the microwave cavity. This work was supported by the European Research\r\nCouncil under grant agreement no. 758053 (ERC StG QUNNECT) and the European\r\nUnion’s Horizon 2020 research and innovation program under grant agreement no.\r\n899354 (FETopen SuperQuLAN). W.H. is the recipient of an ISTplus postdoctoral fellowship\r\nwith funding from the European Union’s Horizon 2020 research and innovation\r\nprogram under the Marie Skłodowska-Curie grant agreement no. 754411. G.A. is the\r\nrecipient of a DOC fellowship of the Austrian Academy of Sciences at IST Austria. J.M.F.\r\nacknowledges support from the Austrian Science Fund (FWF) through BeyondC (F7105)\r\nand the European Union’s Horizon 2020 research and innovation programs under grant\r\nagreement no. 862644 (FETopen QUARTET).","volume":13,"publication":"Nature Communications","year":"2022","scopus_import":"1","pmid":1,"has_accepted_license":"1","status":"public","isi":1,"publication_identifier":{"eissn":["2041-1723"]},"day":"11","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","department":[{"_id":"JoFi"}],"external_id":{"pmid":["35277488"],"isi":["000767892300013"],"arxiv":["2107.08303"]},"publication_status":"published","file_date_updated":"2022-03-28T08:02:12Z"},{"publication_status":"published","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","article_processing_charge":"No","department":[{"_id":"PeJo"},{"_id":"GradSch"}],"day":"20","publication_identifier":{"issn":["2663-337X"]},"alternative_title":["ISTA Thesis"],"supervisor":[{"orcid":"0000-0001-5001-4804","id":"353C1B58-F248-11E8-B48F-1D18A9856A87","last_name":"Jonas","full_name":"Jonas, Peter M","first_name":"Peter M"}],"has_accepted_license":"1","status":"public","file_date_updated":"2023-04-20T22:30:03Z","author":[{"full_name":"Kim, Olena","first_name":"Olena","orcid":"0000-0003-2344-1039","last_name":"Kim","id":"3F8ABDDA-F248-11E8-B48F-1D18A9856A87"}],"title":"Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses","date_created":"2022-04-20T09:47:12Z","ec_funded":1,"file":[{"creator":"okim","date_created":"2022-04-20T14:21:56Z","file_size":21273537,"relation":"main_file","embargo":"2023-04-19","date_updated":"2023-04-20T22:30:03Z","access_level":"open_access","file_id":"11220","content_type":"application/pdf","checksum":"1616a8bf6f13a57c892dac873dcd0936","file_name":"Olena_KIM_thesis_final.pdf"},{"creator":"okim","date_created":"2022-04-20T14:22:56Z","file_size":59248569,"embargo_to":"open_access","date_updated":"2023-04-20T22:30:03Z","relation":"source_file","file_id":"11221","access_level":"closed","content_type":"application/x-zip-compressed","checksum":"1acb433f98dc42abb0b4b0cbb0c4b918","file_name":"KIM_thesis_final.zip"}],"date_published":"2022-04-20T00:00:00Z","project":[{"call_identifier":"H2020","name":"Presynaptic calcium channels distribution and impact on coupling at the hippocampal mossy fiber synapse","_id":"25BAF7B2-B435-11E9-9278-68D0E5697425","grant_number":"708497"},{"name":"Biophysics and circuit function of a giant cortical glutamatergic synapse","call_identifier":"H2020","_id":"25B7EB9E-B435-11E9-9278-68D0E5697425","grant_number":"692692"},{"_id":"25C3DBB6-B435-11E9-9278-68D0E5697425","grant_number":"W01205","call_identifier":"FWF","name":"Zellkommunikation in Gesundheit und Krankheit"},{"name":"Synaptic communication in neuronal microcircuits","call_identifier":"FWF","grant_number":"Z00312","_id":"25C5A090-B435-11E9-9278-68D0E5697425"}],"year":"2022","doi":"10.15479/at:ista:11196","ddc":["570"],"acknowledged_ssus":[{"_id":"EM-Fac"},{"_id":"PreCl"}],"tmp":{"image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode"},"date_updated":"2026-06-18T10:49:27Z","language":[{"iso":"eng"}],"publisher":"Institute of Science and Technology Austria","oa_version":"Published Version","corr_author":"1","page":"132","oa":1,"month":"04","related_material":{"record":[{"relation":"part_of_dissertation","id":"7473","status":"public"},{"status":"public","id":"11222","relation":"part_of_dissertation"}]},"type":"dissertation","citation":{"ieee":"O. Kim, “Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses,” Institute of Science and Technology Austria, 2022.","mla":"Kim, Olena. <i>Nanoarchitecture of Hippocampal Mossy Fiber-CA3 Pyramidal Neuron Synapses</i>. Institute of Science and Technology Austria, 2022, doi:<a href=\"https://doi.org/10.15479/at:ista:11196\">10.15479/at:ista:11196</a>.","short":"O. Kim, Nanoarchitecture of Hippocampal Mossy Fiber-CA3 Pyramidal Neuron Synapses, Institute of Science and Technology Austria, 2022.","apa":"Kim, O. (2022). <i>Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:11196\">https://doi.org/10.15479/at:ista:11196</a>","ama":"Kim O. Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses. 2022. doi:<a href=\"https://doi.org/10.15479/at:ista:11196\">10.15479/at:ista:11196</a>","chicago":"Kim, Olena. “Nanoarchitecture of Hippocampal Mossy Fiber-CA3 Pyramidal Neuron Synapses.” Institute of Science and Technology Austria, 2022. <a href=\"https://doi.org/10.15479/at:ista:11196\">https://doi.org/10.15479/at:ista:11196</a>.","ista":"Kim O. 2022. Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses. Institute of Science and Technology Austria."},"_id":"11196","degree_awarded":"PhD","abstract":[{"lang":"eng","text":"One of the fundamental questions in Neuroscience is how the structure of synapses and their physiological properties are related. While synaptic transmission remains a dynamic process, electron microscopy provides images with comparably low temporal resolution (Studer et al., 2014). The current work overcomes this challenge and describes an improved “Flash and Freeze” technique (Watanabe et al., 2013a; Watanabe et al., 2013b) to study synaptic transmission at the hippocampal mossy fiber-CA3 pyramidal neuron synapses, using mouse acute brain slices and organotypic slices culture. The improved method allowed for selective stimulation of presynaptic mossy fiber boutons and the observation of synaptic vesicle pool dynamics at the active zones. Our results uncovered several intriguing morphological features of mossy fiber boutons. First, the docked vesicle pool was largely depleted (more than 70%) after stimulation, implying that the docked synaptic vesicles pool and readily releasable pool are vastly overlapping in mossy fiber boutons. Second, the synaptic vesicles are skewed towards larger diameters, displaying a wide range of sizes. An increase in the mean diameter of synaptic vesicles, after single and repetitive stimulation, suggests that smaller vesicles have a higher release probability. Third, we observed putative endocytotic structures after moderate light stimulation, matching the timing of previously described ultrafast endocytosis (Watanabe et al., 2013a; Delvendahl et al., 2016). \r\n\tIn addition, synaptic transmission depends on a sophisticated system of protein machinery and calcium channels (Südhof, 2013b), which amplifies the challenge in studying synaptic communication as these interactions can be potentially modified during synaptic plasticity. And although recent study elucidated the potential correlation between physiological and morphological properties of synapses during synaptic plasticity (Vandael et al., 2020), the molecular underpinning of it remains unknown. Thus, the presented work tries to overcome this challenge and aims to pinpoint changes in the molecular architecture at hippocampal mossy fiber bouton synapses during short- and long-term potentiation (STP and LTP), we combined chemical potentiation, with the application of a cyclic adenosine monophosphate agonist (i.e. forskolin) and freeze-fracture replica immunolabelling. This method allowed the localization of membrane-bound proteins with nanometer precision within the active zone, in particular, P/Q-type calcium channels and synaptic vesicle priming proteins Munc13-1/2. First, we found that the number of clusters of Munc13-1 in the mossy fiber bouton active zone increased significantly during STP, but decreased to lower than the control value during LTP. Secondly, although the distance between the calcium channels and Munc13-1s did not change after induction of STP, it shortened during the LTP phase. Additionally, forskolin did not affect Munc13-2 distribution during STP and LTP. These results indicate the existence of two distinct mechanisms that govern STP and LTP at mossy fiber bouton synapses: an increase in the readily realizable pool in the case of STP and a potential increase in release probability during LTP. “Flash and freeze” and functional electron microscopy, are versatile methods that can be successfully applied to intact brain circuits to study synaptic transmission even at the molecular level.\r\n"}],"OA_place":"publisher"},{"article_type":"original","date_published":"2022-07-20T00:00:00Z","file":[{"file_name":"2022_JourCellBiology_Stopp.pdf","date_updated":"2023-01-30T10:39:34Z","relation":"main_file","checksum":"6b1620743669679b48b9389bb40f5a11","content_type":"application/pdf","file_id":"12451","success":1,"access_level":"open_access","file_size":969969,"creator":"dernst","date_created":"2023-01-30T10:39:34Z"}],"issue":"8","author":[{"first_name":"Julian A","full_name":"Stopp, Julian A","last_name":"Stopp","id":"489E3F00-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0002-6620-9179","id":"41E9FBEA-F248-11E8-B48F-1D18A9856A87","last_name":"Sixt","full_name":"Sixt, Michael K","first_name":"Michael K"}],"date_created":"2023-01-16T10:01:08Z","article_number":"e202206127","title":"Plan your trip before you leave: The neutrophils’ search-and-run journey","intvolume":"       221","ddc":["570"],"doi":"10.1083/jcb.202206127","volume":221,"publication":"Journal of Cell Biology","year":"2022","pmid":1,"scopus_import":"1","status":"public","has_accepted_license":"1","isi":1,"day":"20","publication_identifier":{"eissn":["1540-8140"],"issn":["0021-9525"]},"department":[{"_id":"MiSi"}],"article_processing_charge":"No","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","external_id":{"isi":["000874717200001"],"pmid":["35856919"]},"publication_status":"published","file_date_updated":"2023-01-30T10:39:34Z","abstract":[{"text":"Reading, interpreting and crawling along gradients of chemotactic cues is one of the most complex questions in cell biology. In this issue, Georgantzoglou et al. (2022. J. Cell. Biol.https://doi.org/10.1083/jcb.202103207) use in vivo models to map the temporal sequence of how neutrophils respond to an acutely arising gradient of chemoattractant.","lang":"eng"}],"keyword":["Cell Biology"],"_id":"12272","type":"journal_article","month":"07","related_material":{"record":[{"relation":"dissertation_contains","id":"14697","status":"public"}]},"citation":{"ieee":"J. A. Stopp and M. K. Sixt, “Plan your trip before you leave: The neutrophils’ search-and-run journey,” <i>Journal of Cell Biology</i>, vol. 221, no. 8. Rockefeller University Press, 2022.","mla":"Stopp, Julian A., and Michael K. Sixt. “Plan Your Trip before You Leave: The Neutrophils’ Search-and-Run Journey.” <i>Journal of Cell Biology</i>, vol. 221, no. 8, e202206127, Rockefeller University Press, 2022, doi:<a href=\"https://doi.org/10.1083/jcb.202206127\">10.1083/jcb.202206127</a>.","ista":"Stopp JA, Sixt MK. 2022. Plan your trip before you leave: The neutrophils’ search-and-run journey. Journal of Cell Biology. 221(8), e202206127.","chicago":"Stopp, Julian A, and Michael K Sixt. “Plan Your Trip before You Leave: The Neutrophils’ Search-and-Run Journey.” <i>Journal of Cell Biology</i>. Rockefeller University Press, 2022. <a href=\"https://doi.org/10.1083/jcb.202206127\">https://doi.org/10.1083/jcb.202206127</a>.","ama":"Stopp JA, Sixt MK. Plan your trip before you leave: The neutrophils’ search-and-run journey. <i>Journal of Cell Biology</i>. 2022;221(8). doi:<a href=\"https://doi.org/10.1083/jcb.202206127\">10.1083/jcb.202206127</a>","short":"J.A. Stopp, M.K. Sixt, Journal of Cell Biology 221 (2022).","apa":"Stopp, J. A., &#38; Sixt, M. K. (2022). Plan your trip before you leave: The neutrophils’ search-and-run journey. <i>Journal of Cell Biology</i>. Rockefeller University Press. <a href=\"https://doi.org/10.1083/jcb.202206127\">https://doi.org/10.1083/jcb.202206127</a>"},"oa":1,"license":"https://creativecommons.org/licenses/by-nc-sa/4.0/","corr_author":"1","oa_version":"Published Version","quality_controlled":"1","publisher":"Rockefeller University Press","language":[{"iso":"eng"}],"date_updated":"2026-06-20T22:31:20Z","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","short":"CC BY-NC-SA (4.0)","image":"/images/cc_by_nc_sa.png","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)"}},{"_id":"11420","abstract":[{"lang":"eng","text":"Understanding the properties of neural networks trained via stochastic gradient descent (SGD) is at the heart of the theory of deep learning. In this work, we take a mean-field view, and consider a two-layer ReLU network trained via noisy-SGD for a univariate regularized regression problem. Our main result is that SGD with vanishingly small noise injected in the gradients is biased towards a simple solution: at convergence, the ReLU network implements a piecewise linear map of the inputs, and the number of “knot” points -- i.e., points where the tangent of the ReLU network estimator changes -- between two consecutive training inputs is at most three. In particular, as the number of neurons of the network grows, the SGD dynamics is captured by the solution of a gradient flow and, at convergence, the distribution of the weights approaches the unique minimizer of a related free energy, which has a Gibbs form. Our key technical contribution consists in the analysis of the estimator resulting from this minimizer: we show that its second derivative vanishes everywhere, except at some specific locations which represent the “knot” points. We also provide empirical evidence that knots at locations distinct from the data points might occur, as predicted by our theory."}],"page":"1-55","oa":1,"type":"journal_article","related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"17465"}],"link":[{"url":"https://www.jmlr.org/papers/v23/21-1365.html","relation":"other"}]},"month":"04","citation":{"short":"A. Shevchenko, V. Kungurtsev, M. Mondelli, Journal of Machine Learning Research 23 (2022) 1–55.","apa":"Shevchenko, A., Kungurtsev, V., &#38; Mondelli, M. (2022). Mean-field analysis of piecewise linear solutions for wide ReLU networks. <i>Journal of Machine Learning Research</i>. Journal of Machine Learning Research.","chicago":"Shevchenko, Alexander, Vyacheslav Kungurtsev, and Marco Mondelli. “Mean-Field Analysis of Piecewise Linear Solutions for Wide ReLU Networks.” <i>Journal of Machine Learning Research</i>. Journal of Machine Learning Research, 2022.","ista":"Shevchenko A, Kungurtsev V, Mondelli M. 2022. Mean-field analysis of piecewise linear solutions for wide ReLU networks. Journal of Machine Learning Research. 23(130), 1–55.","ama":"Shevchenko A, Kungurtsev V, Mondelli M. Mean-field analysis of piecewise linear solutions for wide ReLU networks. <i>Journal of Machine Learning Research</i>. 2022;23(130):1-55.","mla":"Shevchenko, Alexander, et al. “Mean-Field Analysis of Piecewise Linear Solutions for Wide ReLU Networks.” <i>Journal of Machine Learning Research</i>, vol. 23, no. 130, Journal of Machine Learning Research, 2022, pp. 1–55.","ieee":"A. Shevchenko, V. Kungurtsev, and M. Mondelli, “Mean-field analysis of piecewise linear solutions for wide ReLU networks,” <i>Journal of Machine Learning Research</i>, vol. 23, no. 130. Journal of Machine Learning Research, pp. 1–55, 2022."},"arxiv":1,"publisher":"Journal of Machine Learning Research","quality_controlled":"1","oa_version":"Published Version","corr_author":"1","tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png"},"date_updated":"2026-06-20T22:31:21Z","language":[{"iso":"eng"}],"date_published":"2022-04-01T00:00:00Z","project":[{"_id":"059876FA-7A3F-11EA-A408-12923DDC885E","name":"Prix Lopez-Loretta 2019 - Marco Mondelli"}],"article_type":"original","date_created":"2022-05-29T22:01:54Z","title":"Mean-field analysis of piecewise linear solutions for wide ReLU networks","author":[{"last_name":"Shevchenko","id":"F2B06EC2-C99E-11E9-89F0-752EE6697425","full_name":"Shevchenko, Aleksandr","first_name":"Aleksandr"},{"last_name":"Kungurtsev","full_name":"Kungurtsev, Vyacheslav","first_name":"Vyacheslav"},{"first_name":"Marco","full_name":"Mondelli, Marco","last_name":"Mondelli","id":"27EB676C-8706-11E9-9510-7717E6697425","orcid":"0000-0002-3242-7020"}],"issue":"130","file":[{"file_size":1521701,"creator":"cchlebak","date_created":"2022-05-30T08:22:55Z","file_name":"21-1365.pdf","relation":"main_file","date_updated":"2022-05-30T08:22:55Z","content_type":"application/pdf","checksum":"d4ff5d1affb34848b5c5e4002483fc62","access_level":"open_access","file_id":"11422","success":1}],"acknowledgement":"We would like to thank Mert Pilanci for several exploratory discussions in the early stage\r\nof the project, Jan Maas for clarifications about Jordan et al. (1998), and Max Zimmer for\r\nsuggestive numerical experiments. A. Shevchenko and M. Mondelli are partially supported\r\nby the 2019 Lopez-Loreta Prize. V. Kungurtsev acknowledges support to the OP VVV\r\nproject CZ.02.1.01/0.0/0.0/16 019/0000765 Research Center for Informatics.\r\n","ddc":["000"],"intvolume":"        23","scopus_import":"1","publication":"Journal of Machine Learning Research","year":"2022","volume":23,"day":"01","publication_identifier":{"issn":["1532-4435"],"eissn":["1533-7928"]},"status":"public","has_accepted_license":"1","publication_status":"published","external_id":{"arxiv":["2111.02278"]},"department":[{"_id":"MaMo"},{"_id":"DaAl"}],"article_processing_charge":"No","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","file_date_updated":"2022-05-30T08:22:55Z"},{"_id":"12186","keyword":["Plant Science","Physiology"],"abstract":[{"lang":"eng","text":"Activation of cell-surface and intracellular receptor-mediated immunity results in rapid transcriptional reprogramming that underpins disease resistance. However, the mechanisms by which co-activation of both immune systems lead to transcriptional changes are not clear. Here, we combine RNA-seq and ATAC-seq to define changes in gene expression and chromatin accessibility. Activation of cell-surface or intracellular receptor-mediated immunity, or both, increases chromatin accessibility at induced defence genes. Analysis of ATAC-seq and RNA-seq data combined with publicly available information on transcription factor DNA-binding motifs enabled comparison of individual gene regulatory networks activated by cell-surface or intracellular receptor-mediated immunity, or by both. These results and analyses reveal overlapping and conserved transcriptional regulatory mechanisms between the two immune systems."}],"page":"7927-7941","citation":{"short":"P. Ding, T. Sakai, R. Krishna Shrestha, N. Manosalva Perez, W. Guo, B.P.M. Ngou, S. He, C. Liu, X. Feng, R. Zhang, K. Vandepoele, D. MacLean, J.D.G. Jones, Journal of Experimental Botany 72 (2021) 7927–7941.","apa":"Ding, P., Sakai, T., Krishna Shrestha, R., Manosalva Perez, N., Guo, W., Ngou, B. P. M., … Jones, J. D. G. (2021). Chromatin accessibility landscapes activated by cell-surface and intracellular immune receptors. <i>Journal of Experimental Botany</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/jxb/erab373\">https://doi.org/10.1093/jxb/erab373</a>","ista":"Ding P, Sakai T, Krishna Shrestha R, Manosalva Perez N, Guo W, Ngou BPM, He S, Liu C, Feng X, Zhang R, Vandepoele K, MacLean D, Jones JDG. 2021. Chromatin accessibility landscapes activated by cell-surface and intracellular immune receptors. Journal of Experimental Botany. 72(22), 7927–7941.","chicago":"Ding, Pingtao, Toshiyuki Sakai, Ram Krishna Shrestha, Nicolas Manosalva Perez, Wenbin Guo, Bruno Pok Man Ngou, Shengbo He, et al. “Chromatin Accessibility Landscapes Activated by Cell-Surface and Intracellular Immune Receptors.” <i>Journal of Experimental Botany</i>. Oxford University Press, 2021. <a href=\"https://doi.org/10.1093/jxb/erab373\">https://doi.org/10.1093/jxb/erab373</a>.","ama":"Ding P, Sakai T, Krishna Shrestha R, et al. Chromatin accessibility landscapes activated by cell-surface and intracellular immune receptors. <i>Journal of Experimental Botany</i>. 2021;72(22):7927-7941. doi:<a href=\"https://doi.org/10.1093/jxb/erab373\">10.1093/jxb/erab373</a>","mla":"Ding, Pingtao, et al. “Chromatin Accessibility Landscapes Activated by Cell-Surface and Intracellular Immune Receptors.” <i>Journal of Experimental Botany</i>, vol. 72, no. 22, Oxford University Press, 2021, pp. 7927–41, doi:<a href=\"https://doi.org/10.1093/jxb/erab373\">10.1093/jxb/erab373</a>.","ieee":"P. Ding <i>et al.</i>, “Chromatin accessibility landscapes activated by cell-surface and intracellular immune receptors,” <i>Journal of Experimental Botany</i>, vol. 72, no. 22. Oxford University Press, pp. 7927–7941, 2021."},"month":"08","type":"journal_article","quality_controlled":"1","publisher":"Oxford University Press","oa_version":"None","language":[{"iso":"eng"}],"date_updated":"2023-05-08T11:01:18Z","date_published":"2021-08-13T00:00:00Z","article_type":"original","author":[{"last_name":"Ding","first_name":"Pingtao","full_name":"Ding, Pingtao"},{"last_name":"Sakai","first_name":"Toshiyuki","full_name":"Sakai, Toshiyuki"},{"first_name":"Ram","full_name":"Krishna Shrestha, Ram","last_name":"Krishna Shrestha"},{"full_name":"Manosalva Perez, Nicolas","first_name":"Nicolas","last_name":"Manosalva Perez"},{"full_name":"Guo, Wenbin","first_name":"Wenbin","last_name":"Guo"},{"last_name":"Ngou","full_name":"Ngou, Bruno Pok Man","first_name":"Bruno Pok Man"},{"full_name":"He, Shengbo","first_name":"Shengbo","last_name":"He"},{"last_name":"Liu","full_name":"Liu, Chang","first_name":"Chang"},{"orcid":"0000-0002-4008-1234","last_name":"Feng","id":"e0164712-22ee-11ed-b12a-d80fcdf35958","full_name":"Feng, Xiaoqi","first_name":"Xiaoqi"},{"first_name":"Runxuan","full_name":"Zhang, Runxuan","last_name":"Zhang"},{"first_name":"Klaas","full_name":"Vandepoele, Klaas","last_name":"Vandepoele"},{"first_name":"Dan","full_name":"MacLean, Dan","last_name":"MacLean"},{"last_name":"Jones","first_name":"Jonathan D G","full_name":"Jones, Jonathan D G"}],"date_created":"2023-01-16T09:14:35Z","title":"Chromatin accessibility landscapes activated by cell-surface and intracellular immune receptors","issue":"22","doi":"10.1093/jxb/erab373","acknowledgement":"We thank the Gatsby Foundation (UK) for funding to the JDGJ laboratory. PD acknowledges support from the European Union’s Horizon 2020 Research and Innovation Program under Marie Skłodowska Curie Actions (grant agreement: 656243) and a Future Leader Fellowship from the Biotechnology and Biological Sciences Research Council (BBSRC) (grant agreement: BB/R012172/1). TS, RKS, DM, and JDGJ were supported by the Gatsby Foundation funding to the\r\nSainsbury Laboratory. NMP and KV were supported by a BOF grant from Ghent University (grant agreement: BOF24Y2019001901). WG and RZ were supported by the Scottish Government Rural and Environment Science and Analytical Services division (RESAS), and RZ also acknowledges the support from a BBSRC Bioinformatics and Biological Resources Fund (grant agreement: BB/S020160/1).BPMN was supported by the Norwich Research Park (NRP) Biosciences Doctoral Training Partnership (DTP) funded by the BBSRC (grant agreement: BB/M011216/1). SH and XF were supported by a BBSRC Responsive Mode grant (grant agreement: BB/S009620/1) and a European Research Council Starting grant ‘SexMeth’ (grant agreement: 804981). CL was supported by Deutsche Forschungsgemeinschaft (grant agreement: LI 2862/4). ","intvolume":"        72","year":"2021","publication":"Journal of Experimental Botany","pmid":1,"scopus_import":"1","volume":72,"publication_identifier":{"issn":["0022-0957","1460-2431"]},"day":"13","status":"public","external_id":{"pmid":["34387350"]},"publication_status":"published","extern":"1","department":[{"_id":"XiFe"}],"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87"},{"arxiv":1,"oa":1,"page":"612-634","month":"05","type":"journal_article","citation":{"ieee":"B. Scholkopf <i>et al.</i>, “Toward causal representation learning,” <i>Proceedings of the IEEE</i>, vol. 109, no. 5. Institute of Electrical and Electronics Engineers, pp. 612–634, 2021.","mla":"Scholkopf, Bernhard, et al. “Toward Causal Representation Learning.” <i>Proceedings of the IEEE</i>, vol. 109, no. 5, Institute of Electrical and Electronics Engineers, 2021, pp. 612–34, doi:<a href=\"https://doi.org/10.1109/jproc.2021.3058954\">10.1109/jproc.2021.3058954</a>.","chicago":"Scholkopf, Bernhard, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, and Yoshua Bengio. “Toward Causal Representation Learning.” <i>Proceedings of the IEEE</i>. Institute of Electrical and Electronics Engineers, 2021. <a href=\"https://doi.org/10.1109/jproc.2021.3058954\">https://doi.org/10.1109/jproc.2021.3058954</a>.","ista":"Scholkopf B, Locatello F, Bauer S, Ke NR, Kalchbrenner N, Goyal A, Bengio Y. 2021. Toward causal representation learning. Proceedings of the IEEE. 109(5), 612–634.","ama":"Scholkopf B, Locatello F, Bauer S, et al. Toward causal representation learning. <i>Proceedings of the IEEE</i>. 2021;109(5):612-634. doi:<a href=\"https://doi.org/10.1109/jproc.2021.3058954\">10.1109/jproc.2021.3058954</a>","short":"B. Scholkopf, F. Locatello, S. Bauer, N.R. Ke, N. Kalchbrenner, A. Goyal, Y. Bengio, Proceedings of the IEEE 109 (2021) 612–634.","apa":"Scholkopf, B., Locatello, F., Bauer, S., Ke, N. R., Kalchbrenner, N., Goyal, A., &#38; Bengio, Y. (2021). Toward causal representation learning. <i>Proceedings of the IEEE</i>. Institute of Electrical and Electronics Engineers. <a href=\"https://doi.org/10.1109/jproc.2021.3058954\">https://doi.org/10.1109/jproc.2021.3058954</a>"},"_id":"14117","keyword":["Electrical and Electronic Engineering"],"abstract":[{"lang":"eng","text":"The two fields of machine learning and graphical causality arose and are developed separately. However, there is, now, cross-pollination and increasing interest in both fields to benefit from the advances of the other. In this article, we review fundamental concepts of causal inference and relate them to crucial open problems of machine learning, including transfer and generalization, thereby assaying how causality can contribute to modern machine learning research. This also applies in the opposite direction: we note that most work in causality starts from the premise that the causal variables are given. A central problem for AI and causality is, thus, causal representation learning, that is, the discovery of high-level causal variables from low-level observations. Finally, we delineate some implications of causality for machine learning and propose key research areas at the intersection of both communities."}],"language":[{"iso":"eng"}],"date_updated":"2023-09-11T11:43:35Z","quality_controlled":"1","publisher":"Institute of Electrical and Electronics Engineers","oa_version":"Published Version","year":"2021","publication":"Proceedings of the IEEE","scopus_import":"1","volume":109,"doi":"10.1109/jproc.2021.3058954","intvolume":"       109","author":[{"full_name":"Scholkopf, Bernhard","first_name":"Bernhard","last_name":"Scholkopf"},{"first_name":"Francesco","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","orcid":"0000-0002-4850-0683"},{"last_name":"Bauer","full_name":"Bauer, Stefan","first_name":"Stefan"},{"full_name":"Ke, Nan Rosemary","first_name":"Nan Rosemary","last_name":"Ke"},{"full_name":"Kalchbrenner, Nal","first_name":"Nal","last_name":"Kalchbrenner"},{"last_name":"Goyal","full_name":"Goyal, Anirudh","first_name":"Anirudh"},{"full_name":"Bengio, Yoshua","first_name":"Yoshua","last_name":"Bengio"}],"title":"Toward causal representation learning","date_created":"2023-08-21T12:19:30Z","issue":"5","date_published":"2021-05-01T00:00:00Z","article_type":"original","external_id":{"arxiv":["2102.11107"]},"extern":"1","publication_status":"published","department":[{"_id":"FrLo"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","day":"01","publication_identifier":{"eissn":["1558-2256"],"issn":["0018-9219"]},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1109/JPROC.2021.3058954"}],"status":"public"},{"volume":139,"scopus_import":"1","year":"2021","publication":"Proceedings of 38th International Conference on Machine Learning","intvolume":"       139","author":[{"full_name":"Yèche, Hugo","first_name":"Hugo","last_name":"Yèche"},{"last_name":"Dresdner","first_name":"Gideon","full_name":"Dresdner, Gideon"},{"full_name":"Locatello, Francesco","first_name":"Francesco","orcid":"0000-0002-4850-0683","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"},{"first_name":"Matthias","full_name":"Hüser, Matthias","last_name":"Hüser"},{"first_name":"Gunnar","full_name":"Rätsch, Gunnar","last_name":"Rätsch"}],"date_created":"2023-08-22T14:03:04Z","title":"Neighborhood contrastive learning applied to online patient monitoring","date_published":"2021-08-01T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"FrLo"}],"article_processing_charge":"No","extern":"1","publication_status":"published","external_id":{"arxiv":["2106.05142"]},"alternative_title":["PMLR"],"status":"public","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2106.05142"}],"day":"01","arxiv":1,"citation":{"mla":"Yèche, Hugo, et al. “Neighborhood Contrastive Learning Applied to Online Patient Monitoring.” <i>Proceedings of 38th International Conference on Machine Learning</i>, vol. 139, ML Research Press, 2021, pp. 11964–74.","ieee":"H. Yèche, G. Dresdner, F. Locatello, M. Hüser, and G. Rätsch, “Neighborhood contrastive learning applied to online patient monitoring,” in <i>Proceedings of 38th International Conference on Machine Learning</i>, Virtual, 2021, vol. 139, pp. 11964–11974.","ista":"Yèche H, Dresdner G, Locatello F, Hüser M, Rätsch G. 2021. Neighborhood contrastive learning applied to online patient monitoring. Proceedings of 38th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 139, 11964–11974.","chicago":"Yèche, Hugo, Gideon Dresdner, Francesco Locatello, Matthias Hüser, and Gunnar Rätsch. “Neighborhood Contrastive Learning Applied to Online Patient Monitoring.” In <i>Proceedings of 38th International Conference on Machine Learning</i>, 139:11964–74. ML Research Press, 2021.","ama":"Yèche H, Dresdner G, Locatello F, Hüser M, Rätsch G. Neighborhood contrastive learning applied to online patient monitoring. In: <i>Proceedings of 38th International Conference on Machine Learning</i>. Vol 139. ML Research Press; 2021:11964-11974.","short":"H. Yèche, G. Dresdner, F. Locatello, M. Hüser, G. Rätsch, in:, Proceedings of 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 11964–11974.","apa":"Yèche, H., Dresdner, G., Locatello, F., Hüser, M., &#38; Rätsch, G. (2021). Neighborhood contrastive learning applied to online patient monitoring. In <i>Proceedings of 38th International Conference on Machine Learning</i> (Vol. 139, pp. 11964–11974). Virtual: ML Research Press."},"type":"conference","month":"08","conference":{"name":"International Conference on Machine Learning","start_date":"2021-07-18","end_date":"2021-07-24","location":"Virtual"},"page":"11964-11974","oa":1,"abstract":[{"lang":"eng","text":"Intensive care units (ICU) are increasingly looking towards machine learning for methods to provide online monitoring of critically ill patients. In machine learning, online monitoring is often formulated as a supervised learning problem. Recently, contrastive learning approaches have demonstrated promising improvements over competitive supervised benchmarks. These methods rely on well-understood data augmentation techniques developed for image data which do not apply to online monitoring. In this work, we overcome this limitation by\r\nsupplementing time-series data augmentation techniques with a novel contrastive\r\nlearning objective which we call neighborhood contrastive learning (NCL). Our objective explicitly groups together contiguous time segments from each patient while maintaining state-specific information. Our experiments demonstrate a marked improvement over existing work applying contrastive methods to medical time-series."}],"_id":"14176","language":[{"iso":"eng"}],"date_updated":"2023-09-11T10:16:55Z","oa_version":"Preprint","publisher":"ML Research Press","quality_controlled":"1"},{"volume":139,"scopus_import":"1","year":"2021","publication":"Proceedings of the 38th International Conference on Machine Learning","intvolume":"       139","title":"On disentangled representations learned from correlated data","author":[{"last_name":"Träuble","first_name":"Frederik","full_name":"Träuble, Frederik"},{"first_name":"Elliot","full_name":"Creager, Elliot","last_name":"Creager"},{"last_name":"Kilbertus","full_name":"Kilbertus, Niki","first_name":"Niki"},{"full_name":"Locatello, Francesco","first_name":"Francesco","orcid":"0000-0002-4850-0683","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"},{"full_name":"Dittadi, Andrea","first_name":"Andrea","last_name":"Dittadi"},{"last_name":"Goyal","full_name":"Goyal, Anirudh","first_name":"Anirudh"},{"last_name":"Schölkopf","full_name":"Schölkopf, Bernhard","first_name":"Bernhard"},{"first_name":"Stefan","full_name":"Bauer, Stefan","last_name":"Bauer"}],"date_created":"2023-08-22T14:03:47Z","date_published":"2021-08-01T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"FrLo"}],"article_processing_charge":"No","publication_status":"published","extern":"1","external_id":{"arxiv":["2006.07886"]},"alternative_title":["PMLR"],"main_file_link":[{"url":"https://arxiv.org/abs/2006.07886","open_access":"1"}],"status":"public","day":"01","arxiv":1,"month":"08","type":"conference","citation":{"ieee":"F. Träuble <i>et al.</i>, “On disentangled representations learned from correlated data,” in <i>Proceedings of the 38th International Conference on Machine Learning</i>, Virtual, 2021, vol. 139, pp. 10401–10412.","mla":"Träuble, Frederik, et al. “On Disentangled Representations Learned from Correlated Data.” <i>Proceedings of the 38th International Conference on Machine Learning</i>, vol. 139, ML Research Press, 2021, pp. 10401–12.","chicago":"Träuble, Frederik, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, and Stefan Bauer. “On Disentangled Representations Learned from Correlated Data.” In <i>Proceedings of the 38th International Conference on Machine Learning</i>, 139:10401–12. ML Research Press, 2021.","ista":"Träuble F, Creager E, Kilbertus N, Locatello F, Dittadi A, Goyal A, Schölkopf B, Bauer S. 2021. On disentangled representations learned from correlated data. Proceedings of the 38th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 139, 10401–10412.","ama":"Träuble F, Creager E, Kilbertus N, et al. On disentangled representations learned from correlated data. In: <i>Proceedings of the 38th International Conference on Machine Learning</i>. Vol 139. ML Research Press; 2021:10401-10412.","short":"F. Träuble, E. Creager, N. Kilbertus, F. Locatello, A. Dittadi, A. Goyal, B. Schölkopf, S. Bauer, in:, Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 10401–10412.","apa":"Träuble, F., Creager, E., Kilbertus, N., Locatello, F., Dittadi, A., Goyal, A., … Bauer, S. (2021). On disentangled representations learned from correlated data. In <i>Proceedings of the 38th International Conference on Machine Learning</i> (Vol. 139, pp. 10401–10412). Virtual: ML Research Press."},"conference":{"end_date":"2021-07-24","start_date":"2021-07-18","name":"ICML: International Conference on Machine Learning","location":"Virtual"},"page":"10401-10412","oa":1,"abstract":[{"lang":"eng","text":"The focus of disentanglement approaches has been on identifying independent factors of variation in data. However, the causal variables underlying real-world observations are often not statistically independent. In this work, we bridge the gap to real-world scenarios by analyzing the behavior of the most prominent disentanglement approaches on correlated data in a large-scale empirical study (including 4260 models). We show and quantify that systematically induced correlations in the dataset are being learned and reflected in the latent representations, which has implications for downstream applications of disentanglement such as fairness. We also demonstrate how to resolve these latent correlations, either using weak supervision during\r\ntraining or by post-hoc correcting a pre-trained model with a small number of labels."}],"_id":"14177","date_updated":"2023-09-11T10:18:48Z","language":[{"iso":"eng"}],"oa_version":"Published Version","publisher":"ML Research Press","quality_controlled":"1"},{"main_file_link":[{"url":"https://arxiv.org/abs/2010.14407","open_access":"1"}],"status":"public","day":"04","department":[{"_id":"FrLo"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","extern":"1","publication_status":"published","external_id":{"arxiv":["2010.14407"]},"oa_version":"Preprint","quality_controlled":"1","date_updated":"2023-09-11T10:55:30Z","language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Learning meaningful representations that disentangle the underlying structure of the data generating process is considered to be of key importance in machine learning. While disentangled representations were found to be useful for diverse tasks such as abstract reasoning and fair classification, their scalability and real-world impact remain questionable. We introduce a new high-resolution dataset with 1M simulated images and over 1,800 annotated real-world images of the same setup. In contrast to previous work, this new dataset exhibits correlations, a complex underlying structure, and allows to evaluate transfer to unseen simulated and real-world settings where the encoder i) remains in distribution or ii) is out of distribution. We propose new architectures in order to scale disentangled representation learning to realistic high-resolution settings and conduct a large-scale empirical study of disentangled representations on this dataset. We observe that disentanglement is a good predictor for out-of-distribution (OOD) task performance."}],"_id":"14178","date_published":"2021-05-04T00:00:00Z","type":"conference","month":"05","citation":{"mla":"Dittadi, Andrea, et al. “On the Transfer of Disentangled Representations in Realistic Settings.” <i>The Ninth International Conference on Learning Representations</i>, 2021.","ieee":"A. Dittadi <i>et al.</i>, “On the transfer of disentangled representations in realistic settings,” in <i>The Ninth International Conference on Learning Representations</i>, Virtual, 2021.","short":"A. Dittadi, F. Träuble, F. Locatello, M. Wüthrich, V. Agrawal, O. Winther, S. Bauer, B. Schölkopf, in:, The Ninth International Conference on Learning Representations, 2021.","apa":"Dittadi, A., Träuble, F., Locatello, F., Wüthrich, M., Agrawal, V., Winther, O., … Schölkopf, B. (2021). On the transfer of disentangled representations in realistic settings. In <i>The Ninth International Conference on Learning Representations</i>. Virtual.","ista":"Dittadi A, Träuble F, Locatello F, Wüthrich M, Agrawal V, Winther O, Bauer S, Schölkopf B. 2021. On the transfer of disentangled representations in realistic settings. The Ninth International Conference on Learning Representations. ICLR: International Conference on Learning Representations.","chicago":"Dittadi, Andrea, Frederik Träuble, Francesco Locatello, Manuel Wüthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, and Bernhard Schölkopf. “On the Transfer of Disentangled Representations in Realistic Settings.” In <i>The Ninth International Conference on Learning Representations</i>, 2021.","ama":"Dittadi A, Träuble F, Locatello F, et al. On the transfer of disentangled representations in realistic settings. In: <i>The Ninth International Conference on Learning Representations</i>. ; 2021."},"title":"On the transfer of disentangled representations in realistic settings","author":[{"first_name":"Andrea","full_name":"Dittadi, Andrea","last_name":"Dittadi"},{"last_name":"Träuble","first_name":"Frederik","full_name":"Träuble, Frederik"},{"first_name":"Francesco","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","orcid":"0000-0002-4850-0683"},{"last_name":"Wüthrich","first_name":"Manuel","full_name":"Wüthrich, Manuel"},{"last_name":"Agrawal","full_name":"Agrawal, Vaibhav","first_name":"Vaibhav"},{"first_name":"Ole","full_name":"Winther, Ole","last_name":"Winther"},{"first_name":"Stefan","full_name":"Bauer, Stefan","last_name":"Bauer"},{"last_name":"Schölkopf","first_name":"Bernhard","full_name":"Schölkopf, Bernhard"}],"conference":{"location":"Virtual","name":"ICLR: International Conference on Learning Representations","start_date":"2021-05-03","end_date":"2021-05-07"},"date_created":"2023-08-22T14:04:16Z","oa":1,"arxiv":1,"year":"2021","publication":"The Ninth International Conference on Learning Representations"},{"status":"public","main_file_link":[{"url":"https://arxiv.org/abs/2106.04619","open_access":"1"}],"day":"08","publication_identifier":{"isbn":["9781713845393"]},"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"FrLo"}],"extern":"1","publication_status":"published","external_id":{"arxiv":["2106.04619"]},"intvolume":"        34","volume":34,"publication":"Advances in Neural Information Processing Systems","year":"2021","date_published":"2021-06-08T00:00:00Z","date_created":"2023-08-22T14:04:36Z","title":"Self-supervised learning with data augmentations provably isolates content from style","author":[{"full_name":"Kügelgen, Julius von","first_name":"Julius von","last_name":"Kügelgen"},{"last_name":"Sharma","first_name":"Yash","full_name":"Sharma, Yash"},{"first_name":"Luigi","full_name":"Gresele, Luigi","last_name":"Gresele"},{"first_name":"Wieland","full_name":"Brendel, Wieland","last_name":"Brendel"},{"last_name":"Schölkopf","full_name":"Schölkopf, Bernhard","first_name":"Bernhard"},{"first_name":"Michel","full_name":"Besserve, Michel","last_name":"Besserve"},{"orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","full_name":"Locatello, Francesco","first_name":"Francesco"}],"oa_version":"Preprint","quality_controlled":"1","date_updated":"2023-09-11T10:33:19Z","language":[{"iso":"eng"}],"arxiv":1,"abstract":[{"text":"Self-supervised representation learning has shown remarkable success in a number of domains. A common practice is to perform data augmentation via hand-crafted transformations intended to leave the semantics of the data invariant. We seek to understand the empirical success of this approach from a theoretical perspective. We formulate the augmentation process as a latent variable model by postulating a partition of the latent representation into a content component, which is assumed invariant to augmentation, and a style component, which is allowed to change. Unlike prior work on disentanglement and independent component analysis, we allow for both nontrivial statistical and causal dependencies in the latent space. We study the identifiability of the latent representation based on pairs of views of the observations and prove sufficient conditions that allow us to identify the invariant content partition up to an invertible mapping in both generative and discriminative settings. We find numerical simulations with dependent latent variables are consistent with our theory. Lastly, we introduce Causal3DIdent, a dataset of high-dimensional, visually complex images with rich causal dependencies, which we use to study the effect of data augmentations performed in practice.","lang":"eng"}],"_id":"14179","type":"conference","month":"06","citation":{"mla":"Kügelgen, Julius von, et al. “Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style.” <i>Advances in Neural Information Processing Systems</i>, vol. 34, 2021, pp. 16451–67.","ieee":"J. von Kügelgen <i>et al.</i>, “Self-supervised learning with data augmentations provably isolates content from style,” in <i>Advances in Neural Information Processing Systems</i>, Virtual, 2021, vol. 34, pp. 16451–16467.","apa":"Kügelgen, J. von, Sharma, Y., Gresele, L., Brendel, W., Schölkopf, B., Besserve, M., &#38; Locatello, F. (2021). Self-supervised learning with data augmentations provably isolates content from style. In <i>Advances in Neural Information Processing Systems</i> (Vol. 34, pp. 16451–16467). Virtual.","short":"J. von Kügelgen, Y. Sharma, L. Gresele, W. Brendel, B. Schölkopf, M. Besserve, F. Locatello, in:, Advances in Neural Information Processing Systems, 2021, pp. 16451–16467.","chicago":"Kügelgen, Julius von, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, and Francesco Locatello. “Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style.” In <i>Advances in Neural Information Processing Systems</i>, 34:16451–67, 2021.","ista":"Kügelgen J von, Sharma Y, Gresele L, Brendel W, Schölkopf B, Besserve M, Locatello F. 2021. Self-supervised learning with data augmentations provably isolates content from style. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 16451–16467.","ama":"Kügelgen J von, Sharma Y, Gresele L, et al. Self-supervised learning with data augmentations provably isolates content from style. In: <i>Advances in Neural Information Processing Systems</i>. Vol 34. ; 2021:16451-16467."},"conference":{"location":"Virtual","start_date":"2021-12-07","name":"NeurIPS: Neural Information Processing Systems","end_date":"2021-12-10"},"page":"16451-16467","oa":1},{"arxiv":1,"_id":"14180","abstract":[{"text":"Modern neural network architectures can leverage large amounts of data to generalize well within the training distribution. However, they are less capable of systematic generalization to data drawn from unseen but related distributions, a feat that is hypothesized to require compositional reasoning and reuse of knowledge. In this work, we present Neural Interpreters, an architecture that factorizes inference in a self-attention network as a system of modules, which we call \\emph{functions}. Inputs to the model are routed through a sequence of functions in a way that is end-to-end learned. The proposed architecture can flexibly compose computation along width and depth, and lends itself well to capacity extension after training. To demonstrate the versatility of Neural Interpreters, we evaluate it in two distinct settings: image classification and visual abstract reasoning on Raven Progressive Matrices. In the former, we show that Neural Interpreters perform on par with the vision transformer using fewer parameters, while being transferrable to a new task in a sample efficient manner. In the latter, we find that Neural Interpreters are competitive with respect to the state-of-the-art in terms of systematic generalization. ","lang":"eng"}],"oa":1,"conference":{"end_date":"2021-12-10","start_date":"2021-12-07","name":"NeurIPS: Neural Information Processing Systems","location":"Virtual"},"page":"10985-10998","type":"conference","citation":{"mla":"Rahaman, Nasim, et al. “Dynamic Inference with Neural Interpreters.” <i>Advances in Neural Information Processing Systems</i>, vol. 34, 2021, pp. 10985–98.","ieee":"N. Rahaman <i>et al.</i>, “Dynamic inference with neural interpreters,” in <i>Advances in Neural Information Processing Systems</i>, Virtual, 2021, vol. 34, pp. 10985–10998.","ista":"Rahaman N, Gondal MW, Joshi S, Gehler P, Bengio Y, Locatello F, Schölkopf B. 2021. Dynamic inference with neural interpreters. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 10985–10998.","chicago":"Rahaman, Nasim, Muhammad Waleed Gondal, Shruti Joshi, Peter Gehler, Yoshua Bengio, Francesco Locatello, and Bernhard Schölkopf. “Dynamic Inference with Neural Interpreters.” In <i>Advances in Neural Information Processing Systems</i>, 34:10985–98, 2021.","ama":"Rahaman N, Gondal MW, Joshi S, et al. Dynamic inference with neural interpreters. In: <i>Advances in Neural Information Processing Systems</i>. Vol 34. ; 2021:10985-10998.","short":"N. Rahaman, M.W. Gondal, S. Joshi, P. Gehler, Y. Bengio, F. Locatello, B. Schölkopf, in:, Advances in Neural Information Processing Systems, 2021, pp. 10985–10998.","apa":"Rahaman, N., Gondal, M. W., Joshi, S., Gehler, P., Bengio, Y., Locatello, F., &#38; Schölkopf, B. (2021). Dynamic inference with neural interpreters. In <i>Advances in Neural Information Processing Systems</i> (Vol. 34, pp. 10985–10998). Virtual."},"month":"10","quality_controlled":"1","oa_version":"Preprint","date_updated":"2024-10-14T12:27:25Z","language":[{"iso":"eng"}],"intvolume":"        34","publication":"Advances in Neural Information Processing Systems","year":"2021","volume":34,"date_published":"2021-10-12T00:00:00Z","title":"Dynamic inference with neural interpreters","date_created":"2023-08-22T14:04:55Z","author":[{"last_name":"Rahaman","first_name":"Nasim","full_name":"Rahaman, Nasim"},{"last_name":"Gondal","first_name":"Muhammad Waleed","full_name":"Gondal, Muhammad Waleed"},{"last_name":"Joshi","first_name":"Shruti","full_name":"Joshi, Shruti"},{"full_name":"Gehler, Peter","first_name":"Peter","last_name":"Gehler"},{"last_name":"Bengio","first_name":"Yoshua","full_name":"Bengio, Yoshua"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","orcid":"0000-0002-4850-0683","first_name":"Francesco","full_name":"Locatello, Francesco"},{"first_name":"Bernhard","full_name":"Schölkopf, Bernhard","last_name":"Schölkopf"}],"day":"12","publication_identifier":{"isbn":["9781713845393"]},"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2110.06399","open_access":"1"}],"status":"public","external_id":{"arxiv":["2110.06399"]},"extern":"1","publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","department":[{"_id":"FrLo"}]},{"citation":{"ista":"Dresdner G, Shekhar S, Pedregosa F, Locatello F, Rätsch G. 2021. Boosting variational inference with locally adaptive step-sizes. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. IJCAI: International Joint Conference on Artificial Intelligence, 2337–2343.","chicago":"Dresdner, Gideon, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, and Gunnar Rätsch. “Boosting Variational Inference with Locally Adaptive Step-Sizes.” In <i>Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence</i>, 2337–43. International Joint Conferences on Artificial Intelligence, 2021. <a href=\"https://doi.org/10.24963/ijcai.2021/322\">https://doi.org/10.24963/ijcai.2021/322</a>.","ama":"Dresdner G, Shekhar S, Pedregosa F, Locatello F, Rätsch G. Boosting variational inference with locally adaptive step-sizes. In: <i>Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence</i>. International Joint Conferences on Artificial Intelligence; 2021:2337-2343. doi:<a href=\"https://doi.org/10.24963/ijcai.2021/322\">10.24963/ijcai.2021/322</a>","short":"G. Dresdner, S. Shekhar, F. Pedregosa, F. Locatello, G. Rätsch, in:, Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, 2021, pp. 2337–2343.","apa":"Dresdner, G., Shekhar, S., Pedregosa, F., Locatello, F., &#38; Rätsch, G. (2021). Boosting variational inference with locally adaptive step-sizes. In <i>Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence</i> (pp. 2337–2343). Montreal, Canada: International Joint Conferences on Artificial Intelligence. <a href=\"https://doi.org/10.24963/ijcai.2021/322\">https://doi.org/10.24963/ijcai.2021/322</a>","mla":"Dresdner, Gideon, et al. “Boosting Variational Inference with Locally Adaptive Step-Sizes.” <i>Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence</i>, International Joint Conferences on Artificial Intelligence, 2021, pp. 2337–43, doi:<a href=\"https://doi.org/10.24963/ijcai.2021/322\">10.24963/ijcai.2021/322</a>.","ieee":"G. Dresdner, S. Shekhar, F. Pedregosa, F. Locatello, and G. Rätsch, “Boosting variational inference with locally adaptive step-sizes,” in <i>Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence</i>, Montreal, Canada, 2021, pp. 2337–2343."},"month":"05","type":"conference","conference":{"start_date":"2021-08-19","name":"IJCAI: International Joint Conference on Artificial Intelligence","end_date":"2021-08-27","location":"Montreal, Canada"},"page":"2337-2343","oa":1,"abstract":[{"text":"Variational Inference makes a trade-off between the capacity of the variational family and the tractability of finding an approximate posterior distribution. Instead, Boosting Variational Inference allows practitioners to obtain increasingly good posterior approximations by spending more compute. The main obstacle to widespread adoption of Boosting Variational Inference is the amount of resources necessary to improve over a strong Variational Inference baseline. In our work, we trace this limitation back to the global curvature of the KL-divergence. We characterize how the global curvature impacts time and memory consumption, address the problem with the notion of local curvature, and provide a novel approximate backtracking algorithm for estimating local curvature. We give new theoretical convergence rates for our algorithms and provide experimental validation on synthetic and real-world datasets.","lang":"eng"}],"_id":"14181","arxiv":1,"language":[{"iso":"eng"}],"date_updated":"2023-09-11T11:14:30Z","oa_version":"Published Version","publisher":"International Joint Conferences on Artificial Intelligence","quality_controlled":"1","author":[{"last_name":"Dresdner","full_name":"Dresdner, Gideon","first_name":"Gideon"},{"last_name":"Shekhar","first_name":"Saurav","full_name":"Shekhar, Saurav"},{"full_name":"Pedregosa, Fabian","first_name":"Fabian","last_name":"Pedregosa"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","orcid":"0000-0002-4850-0683","first_name":"Francesco","full_name":"Locatello, Francesco"},{"last_name":"Rätsch","full_name":"Rätsch, Gunnar","first_name":"Gunnar"}],"date_created":"2023-08-22T14:05:14Z","title":"Boosting variational inference with locally adaptive step-sizes","date_published":"2021-05-19T00:00:00Z","year":"2021","publication":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","doi":"10.24963/ijcai.2021/322","article_processing_charge":"No","department":[{"_id":"FrLo"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","extern":"1","publication_status":"published","external_id":{"arxiv":["2105.09240"]},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2105.09240"}],"status":"public","day":"19","publication_identifier":{"eisbn":["9780999241196"]}},{"quality_controlled":"1","oa_version":"Preprint","date_updated":"2023-09-11T11:31:59Z","language":[{"iso":"eng"}],"_id":"14182","abstract":[{"lang":"eng","text":"When machine learning systems meet real world applications, accuracy is only\r\none of several requirements. In this paper, we assay a complementary\r\nperspective originating from the increasing availability of pre-trained and\r\nregularly improving state-of-the-art models. While new improved models develop\r\nat a fast pace, downstream tasks vary more slowly or stay constant. Assume that\r\nwe have a large unlabelled data set for which we want to maintain accurate\r\npredictions. Whenever a new and presumably better ML models becomes available,\r\nwe encounter two problems: (i) given a limited budget, which data points should\r\nbe re-evaluated using the new model?; and (ii) if the new predictions differ\r\nfrom the current ones, should we update? Problem (i) is about compute cost,\r\nwhich matters for very large data sets and models. Problem (ii) is about\r\nmaintaining consistency of the predictions, which can be highly relevant for\r\ndownstream applications; our demand is to avoid negative flips, i.e., changing\r\ncorrect to incorrect predictions. In this paper, we formalize the Prediction\r\nUpdate Problem and present an efficient probabilistic approach as answer to the\r\nabove questions. In extensive experiments on standard classification benchmark\r\ndata sets, we show that our method outperforms alternative strategies along key\r\nmetrics for backward-compatible prediction updates."}],"oa":1,"conference":{"end_date":"2021-12-10","name":"NeurIPS: Neural Information Processing Systems","start_date":"2021-12-07","location":"Virtual"},"page":"116-128","type":"conference","month":"07","citation":{"mla":"Träuble, Frederik, et al. “Backward-Compatible Prediction Updates: A Probabilistic Approach.” <i>35th Conference on Neural Information Processing Systems</i>, vol. 34, 2021, pp. 116–28.","ieee":"F. Träuble, J. von Kügelgen, M. Kleindessner, F. Locatello, B. Schölkopf, and P. Gehler, “Backward-compatible prediction updates: A probabilistic approach,” in <i>35th Conference on Neural Information Processing Systems</i>, Virtual, 2021, vol. 34, pp. 116–128.","ama":"Träuble F, Kügelgen J von, Kleindessner M, Locatello F, Schölkopf B, Gehler P. Backward-compatible prediction updates: A probabilistic approach. In: <i>35th Conference on Neural Information Processing Systems</i>. Vol 34. ; 2021:116-128.","ista":"Träuble F, Kügelgen J von, Kleindessner M, Locatello F, Schölkopf B, Gehler P. 2021. Backward-compatible prediction updates: A probabilistic approach. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 116–128.","chicago":"Träuble, Frederik, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, and Peter Gehler. “Backward-Compatible Prediction Updates: A Probabilistic Approach.” In <i>35th Conference on Neural Information Processing Systems</i>, 34:116–28, 2021.","short":"F. Träuble, J. von Kügelgen, M. Kleindessner, F. Locatello, B. Schölkopf, P. Gehler, in:, 35th Conference on Neural Information Processing Systems, 2021, pp. 116–128.","apa":"Träuble, F., Kügelgen, J. von, Kleindessner, M., Locatello, F., Schölkopf, B., &#38; Gehler, P. (2021). Backward-compatible prediction updates: A probabilistic approach. In <i>35th Conference on Neural Information Processing Systems</i> (Vol. 34, pp. 116–128). Virtual."},"arxiv":1,"day":"02","publication_identifier":{"isbn":["9781713845393"]},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2107.01057"}],"status":"public","external_id":{"arxiv":["2107.01057"]},"extern":"1","publication_status":"published","article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"FrLo"}],"date_published":"2021-07-02T00:00:00Z","author":[{"first_name":"Frederik","full_name":"Träuble, Frederik","last_name":"Träuble"},{"first_name":"Julius von","full_name":"Kügelgen, Julius von","last_name":"Kügelgen"},{"last_name":"Kleindessner","first_name":"Matthäus","full_name":"Kleindessner, Matthäus"},{"orcid":"0000-0002-4850-0683","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","full_name":"Locatello, Francesco","first_name":"Francesco"},{"last_name":"Schölkopf","full_name":"Schölkopf, Bernhard","first_name":"Bernhard"},{"first_name":"Peter","full_name":"Gehler, Peter","last_name":"Gehler"}],"date_created":"2023-08-22T14:05:41Z","title":"Backward-compatible prediction updates: A probabilistic approach","intvolume":"        34","year":"2021","publication":"35th Conference on Neural Information Processing Systems","volume":34},{"article_processing_charge":"No","publication_date":"2021-12-09","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","department":[{"_id":"FrLo"}],"extern":"1","external_id":{"arxiv":["2006.15055"]},"main_file_link":[{"open_access":"1","url":"https://patents.google.com/patent/US20210383199A1/en"}],"status":"public","day":"09","date_updated":"2025-01-31T11:35:46Z","application_date":"2020-07-13","ipc":"G06N 3/063 ; G06N 3/08 ; G06F 17/16","oa_version":"Published Version","application_number":"16 / 927,018 ","ipn":"US20210383199A1","citation":{"ista":"Weissenborn D, Uszkoreit J, Unterthiner T, Mahendran A, Locatello F, Kipf T, Heigold G, Dosovitskiy A. 2021. Object-centric learning with slot attention.","chicago":"Weissenborn, Dirk, Jakob Uszkoreit, Thomas Unterthiner, Aravindh Mahendran, Francesco Locatello, Thomas Kipf, Georg Heigold, and Alexey Dosovitskiy. “Object-Centric Learning with Slot Attention,” 2021.","ama":"Weissenborn D, Uszkoreit J, Unterthiner T, et al. Object-centric learning with slot attention. 2021.","apa":"Weissenborn, D., Uszkoreit, J., Unterthiner, T., Mahendran, A., Locatello, F., Kipf, T., … Dosovitskiy, A. (2021). Object-centric learning with slot attention.","short":"D. Weissenborn, J. Uszkoreit, T. Unterthiner, A. Mahendran, F. Locatello, T. Kipf, G. Heigold, A. Dosovitskiy, (2021).","ieee":"D. Weissenborn <i>et al.</i>, “Object-centric learning with slot attention.” 2021.","mla":"Weissenborn, Dirk, et al. <i>Object-Centric Learning with Slot Attention</i>. 2021."},"type":"patent","month":"12","author":[{"full_name":"Weissenborn, Dirk","first_name":"Dirk","last_name":"Weissenborn"},{"first_name":"Jakob","full_name":"Uszkoreit, Jakob","last_name":"Uszkoreit"},{"last_name":"Unterthiner","full_name":"Unterthiner, Thomas","first_name":"Thomas"},{"full_name":"Mahendran, Aravindh","first_name":"Aravindh","last_name":"Mahendran"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","orcid":"0000-0002-4850-0683","first_name":"Francesco","full_name":"Locatello, Francesco"},{"last_name":"Kipf","full_name":"Kipf, Thomas","first_name":"Thomas"},{"last_name":"Heigold","full_name":"Heigold, Georg","first_name":"Georg"},{"first_name":"Alexey","full_name":"Dosovitskiy, Alexey","last_name":"Dosovitskiy"}],"applicant":["Google LLC"],"title":"Object-centric learning with slot attention","date_created":"2023-08-22T14:07:06Z","oa":1,"abstract":[{"lang":"eng","text":"A method involves receiving a perceptual representation including a plurality of feature vectors, and initializing a plurality of slot vectors represented by a neural network memory unit. Each respective slot vector is configured to represent a corresponding entity in the perceptual representation. The method also involves determining an attention matrix based on a product of the plurality of feature vectors transformed by a key function and the plurality of slot vectors transformed by a query function. Each respective value of a plurality of values along each respective dimension of the attention matrix is normalized with respect to the plurality of values. The method additionally involves determining an update matrix based on the plurality of feature vectors transformed by a value function and the attention matrix, and updating the plurality of slot vectors based on the update matrix by way of the neural network memory unit."}],"_id":"14185","date_published":"2021-12-09T00:00:00Z","year":"2021","arxiv":1,"OA_place":"repository"}]