[{"year":"2020","citation":{"apa":"Kavcic, B., Tkačik, G., &#38; Bollenbach, M. T. (2020). A minimal biophysical model of combined antibiotic action. <i>bioRxiv</i>. <a href=\"https://doi.org/10.1101/2020.04.18.047886\">https://doi.org/10.1101/2020.04.18.047886</a>","chicago":"Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “A Minimal Biophysical Model of Combined Antibiotic Action.” <i>BioRxiv</i>, 2020. <a href=\"https://doi.org/10.1101/2020.04.18.047886\">https://doi.org/10.1101/2020.04.18.047886</a>.","ieee":"B. Kavcic, G. Tkačik, and M. T. Bollenbach, “A minimal biophysical model of combined antibiotic action,” <i>bioRxiv</i>. 2020.","short":"B. Kavcic, G. Tkačik, M.T. Bollenbach, BioRxiv (2020).","ista":"Kavcic B, Tkačik G, Bollenbach MT. 2020. A minimal biophysical model of combined antibiotic action. bioRxiv, <a href=\"https://doi.org/10.1101/2020.04.18.047886\">10.1101/2020.04.18.047886</a>.","mla":"Kavcic, Bor, et al. “A Minimal Biophysical Model of Combined Antibiotic Action.” <i>BioRxiv</i>, 2020, doi:<a href=\"https://doi.org/10.1101/2020.04.18.047886\">10.1101/2020.04.18.047886</a>.","ama":"Kavcic B, Tkačik G, Bollenbach MT. A minimal biophysical model of combined antibiotic action. <i>bioRxiv</i>. 2020. doi:<a href=\"https://doi.org/10.1101/2020.04.18.047886\">10.1101/2020.04.18.047886</a>"},"publication_status":"published","author":[{"orcid":"0000-0001-6041-254X","last_name":"Kavcic","first_name":"Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","full_name":"Kavcic, Bor"},{"last_name":"Tkačik","orcid":"0000-0002-6699-1455","first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper"},{"orcid":"0000-0003-4398-476X","last_name":"Bollenbach","full_name":"Bollenbach, Tobias","first_name":"Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1101/2020.04.18.047886 "}],"doi":"10.1101/2020.04.18.047886","status":"public","day":"18","project":[{"name":"Revealing the mechanisms underlying drug interactions","grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"},{"grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Biophysics of information processing in gene regulation"}],"article_processing_charge":"No","title":"A minimal biophysical model of combined antibiotic action","abstract":[{"lang":"eng","text":"Combining drugs can improve the efficacy of treatments. However, predicting the effect of drug combinations is still challenging. The combined potency of drugs determines the drug interaction, which is classified as synergistic, additive, antagonistic, or suppressive. While probabilistic, non-mechanistic models exist, there is currently no biophysical model that can predict antibiotic interactions. Here, we present a physiologically relevant model of the combined action of antibiotics that inhibit protein synthesis by targeting the ribosome. This model captures the kinetics of antibiotic binding and transport, and uses bacterial growth laws to predict growth in the presence of antibiotic combinations. We find that this biophysical model can produce all drug interaction types except suppression. We show analytically that antibiotics which cannot bind to the ribosome simultaneously generally act as substitutes for one another, leading to additive drug interactions. Previously proposed null expectations for higher-order drug interactions follow as a limiting case of our model. We further extend the model to include the effects of direct physical or allosteric interactions between individual drugs on the ribosome. Notably, such direct interactions profoundly change the combined drug effect, depending on the kinetic parameters of the drugs used. The model makes additional predictions for the effects of resistance genes on drug interactions and for interactions between ribosome-targeting antibiotics and antibiotics with other targets. These findings enhance our understanding of the interplay between drug action and cell physiology and are a key step toward a general framework for predicting drug interactions."}],"type":"preprint","department":[{"_id":"GaTk"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2020-04-22T08:27:56Z","month":"04","fulldoi":"https://doi.org/10.1101/2020.04.18.047886","_id":"7673","oa_version":"Preprint","publication":"bioRxiv","date_published":"2020-04-18T00:00:00Z","date_updated":"2026-10-29T23:30:41Z","language":[{"iso":"eng"}],"oa":1,"related_material":{"record":[{"id":"8997","status":"public","relation":"later_version"},{"relation":"dissertation_contains","id":"8657","status":"public"}]},"das_tickbox":"1"},{"article_processing_charge":"No","type":"conference","day":"12","author":[{"first_name":"Ali","full_name":"Asadi, Ali","last_name":"Asadi"},{"last_name":"Chatterjee","orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","first_name":"Krishnendu"},{"last_name":"Goharshady","orcid":"0000-0003-1702-6584","id":"391365CE-F248-11E8-B48F-1D18A9856A87","first_name":"Amir Kafshdar","full_name":"Goharshady, Amir Kafshdar"},{"last_name":"Mohammadi","first_name":"Kiarash","full_name":"Mohammadi, Kiarash"},{"orcid":"0000-0002-8943-0722","last_name":"Pavlogiannis","full_name":"Pavlogiannis, Andreas","id":"49704004-F248-11E8-B48F-1D18A9856A87","first_name":"Andreas"}],"scopus_import":"1","publication_identifier":{"issn":["0302-9743"],"eisbn":["9783030591526"],"eissn":["1611-3349"],"isbn":["9783030591519"]},"page":"253-270","language":[{"iso":"eng"}],"date_published":"2020-10-12T00:00:00Z","external_id":{"isi":["000723555700014"]},"alternative_title":["LNCS"],"ddc":["000"],"fulldoi":"https://doi.org/10.1007/978-3-030-59152-6_14","has_accepted_license":"1","title":"Faster algorithms for quantitative analysis of MCs and MDPs with small treewidth","abstract":[{"lang":"eng","text":"Discrete-time Markov Chains (MCs) and Markov Decision Processes (MDPs) are two standard formalisms in system analysis. Their main associated quantitative objectives are hitting probabilities, discounted sum, and mean payoff. Although there are many techniques for computing these objectives in general MCs/MDPs, they have not been thoroughly studied in terms of parameterized algorithms, particularly when treewidth is used as the parameter. This is in sharp contrast to qualitative objectives for MCs, MDPs and graph games, for which treewidth-based algorithms yield significant complexity improvements. In this work, we show that treewidth can also be used to obtain faster algorithms for the quantitative problems. For an MC with n states and m transitions, we show that each of the classical quantitative objectives can be computed in   O((n+m)⋅t2)  time, given a tree decomposition of the MC with width t. Our results also imply a bound of   O(κ⋅(n+m)⋅t2)  for each objective on MDPs, where   κ  is the number of strategy-iteration refinements required for the given input and objective. Finally, we make an experimental evaluation of our new algorithms on low-treewidth MCs and MDPs obtained from the DaCapo benchmark suite. Our experiments show that on low-treewidth MCs and MDPs, our algorithms outperform existing well-established methods by one or more orders of magnitude."}],"status":"public","project":[{"call_identifier":"FWF","grant_number":"S 11407_N23","_id":"25832EC2-B435-11E9-9278-68D0E5697425","name":"Rigorous Systems Engineering"},{"grant_number":"ICT15-003","_id":"25892FC0-B435-11E9-9278-68D0E5697425","name":"Efficient Algorithms for Computer Aided Verification"},{"name":"Quantitative Analysis of Probabilistic Systems with a focus on Crypto-Currencies","_id":"267066CE-B435-11E9-9278-68D0E5697425"}],"publisher":"Springer Nature","quality_controlled":"1","doi":"10.1007/978-3-030-59152-6_14","volume":12302,"year":"2020","publication_status":"published","citation":{"ama":"Asadi A, Chatterjee K, Goharshady AK, Mohammadi K, Pavlogiannis A. Faster algorithms for quantitative analysis of MCs and MDPs with small treewidth. In: <i>Automated Technology for Verification and Analysis</i>. Vol 12302. Springer Nature; 2020:253-270. doi:<a href=\"https://doi.org/10.1007/978-3-030-59152-6_14\">10.1007/978-3-030-59152-6_14</a>","mla":"Asadi, Ali, et al. “Faster Algorithms for Quantitative Analysis of MCs and MDPs with Small Treewidth.” <i>Automated Technology for Verification and Analysis</i>, vol. 12302, Springer Nature, 2020, pp. 253–70, doi:<a href=\"https://doi.org/10.1007/978-3-030-59152-6_14\">10.1007/978-3-030-59152-6_14</a>.","ista":"Asadi A, Chatterjee K, Goharshady AK, Mohammadi K, Pavlogiannis A. 2020. Faster algorithms for quantitative analysis of MCs and MDPs with small treewidth. Automated Technology for Verification and Analysis. ATVA: Automated Technology for Verification and Analysis, LNCS, vol. 12302, 253–270.","short":"A. Asadi, K. Chatterjee, A.K. Goharshady, K. Mohammadi, A. Pavlogiannis, in:, Automated Technology for Verification and Analysis, Springer Nature, 2020, pp. 253–270.","ieee":"A. Asadi, K. Chatterjee, A. K. Goharshady, K. Mohammadi, and A. Pavlogiannis, “Faster algorithms for quantitative analysis of MCs and MDPs with small treewidth,” in <i>Automated Technology for Verification and Analysis</i>, Hanoi, Vietnam, 2020, vol. 12302, pp. 253–270.","chicago":"Asadi, Ali, Krishnendu Chatterjee, Amir Kafshdar Goharshady, Kiarash Mohammadi, and Andreas Pavlogiannis. “Faster Algorithms for Quantitative Analysis of MCs and MDPs with Small Treewidth.” In <i>Automated Technology for Verification and Analysis</i>, 12302:253–70. Springer Nature, 2020. <a href=\"https://doi.org/10.1007/978-3-030-59152-6_14\">https://doi.org/10.1007/978-3-030-59152-6_14</a>.","apa":"Asadi, A., Chatterjee, K., Goharshady, A. K., Mohammadi, K., &#38; Pavlogiannis, A. (2020). Faster algorithms for quantitative analysis of MCs and MDPs with small treewidth. In <i>Automated Technology for Verification and Analysis</i> (Vol. 12302, pp. 253–270). Hanoi, Vietnam: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-030-59152-6_14\">https://doi.org/10.1007/978-3-030-59152-6_14</a>"},"date_updated":"2026-10-29T23:30:46Z","isi":1,"file":[{"success":1,"file_id":"8729","date_updated":"2020-11-06T07:41:03Z","file_name":"2020_LNCS_ATVA_Asadi_accepted.pdf","creator":"dernst","relation":"main_file","checksum":"ae83f27e5b189d5abc2e7514f1b7e1b5","file_size":726648,"date_created":"2020-11-06T07:41:03Z","content_type":"application/pdf","access_level":"open_access"}],"oa":1,"related_material":{"record":[{"relation":"dissertation_contains","id":"8934","status":"public"}]},"file_date_updated":"2020-11-06T07:41:03Z","intvolume":"     12302","publication":"Automated Technology for Verification and Analysis","oa_version":"Submitted Version","month":"10","_id":"8728","conference":{"start_date":"2020-10-19","end_date":"2020-10-23","name":"ATVA: Automated Technology for Verification and Analysis","location":"Hanoi, Vietnam"},"department":[{"_id":"KrCh"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","date_created":"2020-11-06T07:30:05Z"},{"main_file_link":[{"url":"https://arxiv.org/abs/1902.04373","open_access":"1"}],"publication_identifier":{"isbn":["9781450376136"]},"scopus_import":"1","author":[{"full_name":"Chatterjee, Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","first_name":"Krishnendu","orcid":"0000-0002-4561-241X","last_name":"Chatterjee"},{"full_name":"Fu, Hongfei","first_name":"Hongfei","id":"3AAD03D6-F248-11E8-B48F-1D18A9856A87","last_name":"Fu"},{"orcid":"0000-0003-1702-6584","last_name":"Goharshady","first_name":"Amir Kafshdar","id":"391365CE-F248-11E8-B48F-1D18A9856A87","full_name":"Goharshady, Amir Kafshdar"},{"last_name":"Goharshady","full_name":"Goharshady, Ehsan Kafshdar","first_name":"Ehsan Kafshdar"}],"page":"672-687","type":"conference","article_processing_charge":"No","day":"11","fulldoi":"https://doi.org/10.1145/3385412.3385969","language":[{"iso":"eng"}],"date_published":"2020-06-11T00:00:00Z","external_id":{"isi":["000614622300045"],"arxiv":["1902.04373"]},"arxiv":1,"doi":"10.1145/3385412.3385969","publication_status":"published","citation":{"chicago":"Chatterjee, Krishnendu, Hongfei Fu, Amir Kafshdar Goharshady, and Ehsan Kafshdar Goharshady. “Polynomial Invariant Generation for Non-Deterministic Recursive Programs.” In <i>Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation</i>, 672–87. Association for Computing Machinery, 2020. <a href=\"https://doi.org/10.1145/3385412.3385969\">https://doi.org/10.1145/3385412.3385969</a>.","apa":"Chatterjee, K., Fu, H., Goharshady, A. K., &#38; Goharshady, E. K. (2020). Polynomial invariant generation for non-deterministic recursive programs. In <i>Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation</i> (pp. 672–687). London, United Kingdom: Association for Computing Machinery. <a href=\"https://doi.org/10.1145/3385412.3385969\">https://doi.org/10.1145/3385412.3385969</a>","short":"K. Chatterjee, H. Fu, A.K. Goharshady, E.K. Goharshady, in:, Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation, Association for Computing Machinery, 2020, pp. 672–687.","ieee":"K. Chatterjee, H. Fu, A. K. Goharshady, and E. K. Goharshady, “Polynomial invariant generation for non-deterministic recursive programs,” in <i>Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation</i>, London, United Kingdom, 2020, pp. 672–687.","ista":"Chatterjee K, Fu H, Goharshady AK, Goharshady EK. 2020. Polynomial invariant generation for non-deterministic recursive programs. Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation. PLDI: Programming Language Design and Implementation, 672–687.","ama":"Chatterjee K, Fu H, Goharshady AK, Goharshady EK. Polynomial invariant generation for non-deterministic recursive programs. In: <i>Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation</i>. Association for Computing Machinery; 2020:672-687. doi:<a href=\"https://doi.org/10.1145/3385412.3385969\">10.1145/3385412.3385969</a>","mla":"Chatterjee, Krishnendu, et al. “Polynomial Invariant Generation for Non-Deterministic Recursive Programs.” <i>Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation</i>, Association for Computing Machinery, 2020, pp. 672–87, doi:<a href=\"https://doi.org/10.1145/3385412.3385969\">10.1145/3385412.3385969</a>."},"year":"2020","title":"Polynomial invariant generation for non-deterministic recursive programs","abstract":[{"text":"We consider the classical problem of invariant generation for programs with polynomial assignments and focus on synthesizing invariants that are a conjunction of strict polynomial inequalities. We present a sound and semi-complete method based on positivstellensaetze, i.e. theorems in semi-algebraic geometry that characterize positive polynomials over a semi-algebraic set.\r\n\r\nOn the theoretical side, the worst-case complexity of our approach is subexponential, whereas the worst-case complexity of the previous complete method (Kapur, ACA 2004) is doubly-exponential. Even when restricted to linear invariants, the best previous complexity for complete invariant generation is exponential (Colon et al, CAV 2003). On the practical side, we reduce the invariant generation problem to quadratic programming (QCLP), which is a classical optimization problem with many industrial solvers. We demonstrate the applicability of our approach by providing experimental results on several academic benchmarks. To the best of our knowledge, the only previous invariant generation method that provides completeness guarantees for invariants consisting of polynomial inequalities is (Kapur, ACA 2004), which relies on quantifier elimination and cannot even handle toy programs such as our running example.","lang":"eng"}],"quality_controlled":"1","status":"public","publisher":"Association for Computing Machinery","project":[{"name":"Rigorous Systems Engineering","grant_number":"S 11407_N23","_id":"25832EC2-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"},{"name":"Efficient Algorithms for Computer Aided Verification","grant_number":"ICT15-003","_id":"25892FC0-B435-11E9-9278-68D0E5697425"}],"_id":"8089","conference":{"location":"London, United Kingdom","end_date":"2020-06-20","name":"PLDI: Programming Language Design and Implementation","start_date":"2020-06-15"},"month":"06","date_created":"2020-07-05T22:00:45Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"KrCh"}],"related_material":{"record":[{"relation":"dissertation_contains","id":"8934","status":"public"}]},"date_updated":"2026-10-29T23:30:46Z","isi":1,"oa":1,"oa_version":"Preprint","publication":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation"},{"doi":"10.1007/978-3-030-44914-8_5","citation":{"short":"K. Chatterjee, A.K. Goharshady, R. Ibsen-Jensen, A. Pavlogiannis, in:, European Symposium on Programming, Springer Nature, 2020, pp. 112–140.","ieee":"K. Chatterjee, A. K. Goharshady, R. Ibsen-Jensen, and A. Pavlogiannis, “Optimal and perfectly parallel algorithms for on-demand data-flow analysis,” in <i>European Symposium on Programming</i>, Dublin, Ireland, 2020, vol. 12075, pp. 112–140.","chicago":"Chatterjee, Krishnendu, Amir Kafshdar Goharshady, Rasmus Ibsen-Jensen, and Andreas Pavlogiannis. “Optimal and Perfectly Parallel Algorithms for On-Demand Data-Flow Analysis.” In <i>European Symposium on Programming</i>, 12075:112–40. Springer Nature, 2020. <a href=\"https://doi.org/10.1007/978-3-030-44914-8_5\">https://doi.org/10.1007/978-3-030-44914-8_5</a>.","apa":"Chatterjee, K., Goharshady, A. K., Ibsen-Jensen, R., &#38; Pavlogiannis, A. (2020). Optimal and perfectly parallel algorithms for on-demand data-flow analysis. In <i>European Symposium on Programming</i> (Vol. 12075, pp. 112–140). Dublin, Ireland: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-030-44914-8_5\">https://doi.org/10.1007/978-3-030-44914-8_5</a>","ama":"Chatterjee K, Goharshady AK, Ibsen-Jensen R, Pavlogiannis A. Optimal and perfectly parallel algorithms for on-demand data-flow analysis. In: <i>European Symposium on Programming</i>. Vol 12075. Springer Nature; 2020:112-140. doi:<a href=\"https://doi.org/10.1007/978-3-030-44914-8_5\">10.1007/978-3-030-44914-8_5</a>","mla":"Chatterjee, Krishnendu, et al. “Optimal and Perfectly Parallel Algorithms for On-Demand Data-Flow Analysis.” <i>European Symposium on Programming</i>, vol. 12075, Springer Nature, 2020, pp. 112–40, doi:<a href=\"https://doi.org/10.1007/978-3-030-44914-8_5\">10.1007/978-3-030-44914-8_5</a>.","ista":"Chatterjee K, Goharshady AK, Ibsen-Jensen R, Pavlogiannis A. 2020. Optimal and perfectly parallel algorithms for on-demand data-flow analysis. European Symposium on Programming. ESOP: Programming Languages and Systems, LNCS, vol. 12075, 112–140."},"publication_status":"published","year":"2020","tmp":{"image":"/images/cc_by.png","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)"},"volume":12075,"abstract":[{"lang":"eng","text":"Interprocedural data-flow analyses form an expressive and useful paradigm of numerous static analysis applications, such as live variables analysis, alias analysis and null pointers analysis. The most widely-used framework for interprocedural data-flow analysis is IFDS, which encompasses distributive data-flow functions over a finite domain. On-demand data-flow analyses restrict the focus of the analysis on specific program locations and data facts. This setting provides a natural split between (i) an offline (or preprocessing) phase, where the program is partially analyzed and analysis summaries are created, and (ii) an online (or query) phase, where analysis queries arrive on demand and the summaries are used to speed up answering queries.\r\nIn this work, we consider on-demand IFDS analyses where the queries concern program locations of the same procedure (aka same-context queries). We exploit the fact that flow graphs of programs have low treewidth to develop faster algorithms that are space and time optimal for many common data-flow analyses, in both the preprocessing and the query phase. We also use treewidth to develop query solutions that are embarrassingly parallelizable, i.e. the total work for answering each query is split to a number of threads such that each thread performs only a constant amount of work. Finally, we implement a static analyzer based on our algorithms, and perform a series of on-demand analysis experiments on standard benchmarks. Our experimental results show a drastic speed-up of the queries after only a lightweight preprocessing phase, which significantly outperforms existing techniques."}],"title":"Optimal and perfectly parallel algorithms for on-demand data-flow analysis","quality_controlled":"1","status":"public","project":[{"name":"Rigorous Systems Engineering","_id":"25832EC2-B435-11E9-9278-68D0E5697425","grant_number":"S 11407_N23","call_identifier":"FWF"},{"_id":"25892FC0-B435-11E9-9278-68D0E5697425","grant_number":"ICT15-003","name":"Efficient Algorithms for Computer Aided Verification"},{"_id":"266EEEC0-B435-11E9-9278-68D0E5697425","name":"Quantitative Game-theoretic Analysis of Blockchain Applications and Smart Contracts"},{"_id":"267066CE-B435-11E9-9278-68D0E5697425","name":"Quantitative Analysis of Probabilistic Systems with a focus on Crypto-Currencies"}],"publisher":"Springer Nature","_id":"7810","conference":{"end_date":"2020-04-30","name":"ESOP: Programming Languages and Systems","location":"Dublin, Ireland","start_date":"2020-04-25"},"month":"04","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","date_created":"2020-05-10T22:00:50Z","department":[{"_id":"KrCh"}],"related_material":{"record":[{"relation":"dissertation_contains","id":"8934","status":"public"}]},"isi":1,"file":[{"access_level":"open_access","date_created":"2020-05-26T13:34:48Z","content_type":"application/pdf","checksum":"8618b80f4cf7b39a60e61a6445ad9807","file_size":651250,"relation":"main_file","file_name":"2020_LNCS_Chatterjee.pdf","creator":"dernst","date_updated":"2020-07-14T12:48:03Z","file_id":"7895"}],"date_updated":"2026-10-29T23:30:46Z","oa":1,"oa_version":"Published Version","publication":"European Symposium on Programming","file_date_updated":"2020-07-14T12:48:03Z","intvolume":"     12075","scopus_import":"1","publication_identifier":{"eissn":["1611-3349"],"isbn":["9783030449131"],"issn":["0302-9743"]},"author":[{"last_name":"Chatterjee","orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","first_name":"Krishnendu"},{"last_name":"Goharshady","orcid":"0000-0003-1702-6584","full_name":"Goharshady, Amir Kafshdar","id":"391365CE-F248-11E8-B48F-1D18A9856A87","first_name":"Amir Kafshdar"},{"orcid":"0000-0003-4783-0389","last_name":"Ibsen-Jensen","id":"3B699956-F248-11E8-B48F-1D18A9856A87","first_name":"Rasmus","full_name":"Ibsen-Jensen, Rasmus"},{"last_name":"Pavlogiannis","orcid":"0000-0002-8943-0722","full_name":"Pavlogiannis, Andreas","id":"49704004-F248-11E8-B48F-1D18A9856A87","first_name":"Andreas"}],"page":"112-140","corr_author":"1","type":"conference","article_processing_charge":"No","day":"18","has_accepted_license":"1","ddc":["000"],"fulldoi":"https://doi.org/10.1007/978-3-030-44914-8_5","language":[{"iso":"eng"}],"alternative_title":["LNCS"],"date_published":"2020-04-18T00:00:00Z","external_id":{"isi":["000681656800005"]}},{"date_published":"2020-01-01T00:00:00Z","external_id":{"isi":["000501641400050"],"arxiv":["1712.09692"]},"arxiv":1,"language":[{"iso":"eng"}],"fulldoi":"https://doi.org/10.1016/j.ress.2019.106665","day":"01","type":"journal_article","article_processing_charge":"No","article_number":"106665","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1712.09692"}],"scopus_import":"1","publication_identifier":{"issn":["0951-8320"]},"author":[{"last_name":"Goharshady","orcid":"0000-0003-1702-6584","full_name":"Goharshady, Amir Kafshdar","id":"391365CE-F248-11E8-B48F-1D18A9856A87","first_name":"Amir Kafshdar"},{"full_name":"Mohammadi, Fatemeh","first_name":"Fatemeh","last_name":"Mohammadi"}],"publication":"Reliability Engineering and System Safety","oa_version":"Preprint","intvolume":"       193","related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"8934"}]},"isi":1,"date_updated":"2026-10-29T23:30:46Z","oa":1,"user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","date_created":"2019-09-29T22:00:44Z","department":[{"_id":"KrCh"}],"article_type":"original","_id":"6918","month":"01","quality_controlled":"1","status":"public","project":[{"_id":"266EEEC0-B435-11E9-9278-68D0E5697425","name":"Quantitative Game-theoretic Analysis of Blockchain Applications and Smart Contracts"}],"publisher":"Elsevier","acknowledgement":"We are grateful to the anonymous reviewers for their comments, which significantly improved the present work. The research was partially supported by the EPSRC Early Career Fellowship EP/R023379/1, grant no. SC7-1718-01 of the London Mathematical Society, an IBM PhD Fellowship, and a DOC Fellowship of the Austrian Academy of Sciences (ÖAW).","title":"An efficient algorithm for computing network reliability in small treewidth","abstract":[{"text":"We consider the classic problem of Network Reliability. A network is given together with a source vertex, one or more target vertices, and probabilities assigned to each of the edges. Each edge of the network is operable with its associated probability and the problem is to determine the probability of having at least one source-to-target path that is entirely composed of operable edges. This problem is known to be NP-hard.\r\n\r\nWe provide a novel scalable algorithm to solve the Network Reliability problem when the treewidth of the underlying network is small. We also show our algorithm’s applicability for real-world transit networks that have small treewidth, including the metro networks of major cities, such as London and Tokyo. Our algorithm leverages tree decompositions to shrink the original graph into much smaller graphs, for which reliability can be efficiently and exactly computed using a brute force method. To the best of our knowledge, this is the first exact algorithm for Network Reliability that can scale to handle real-world instances of the problem.","lang":"eng"}],"citation":{"chicago":"Goharshady, Amir Kafshdar, and Fatemeh Mohammadi. “An Efficient Algorithm for Computing Network Reliability in Small Treewidth.” <i>Reliability Engineering and System Safety</i>. Elsevier, 2020. <a href=\"https://doi.org/10.1016/j.ress.2019.106665\">https://doi.org/10.1016/j.ress.2019.106665</a>.","apa":"Goharshady, A. K., &#38; Mohammadi, F. (2020). An efficient algorithm for computing network reliability in small treewidth. <i>Reliability Engineering and System Safety</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.ress.2019.106665\">https://doi.org/10.1016/j.ress.2019.106665</a>","short":"A.K. Goharshady, F. Mohammadi, Reliability Engineering and System Safety 193 (2020).","ieee":"A. K. Goharshady and F. Mohammadi, “An efficient algorithm for computing network reliability in small treewidth,” <i>Reliability Engineering and System Safety</i>, vol. 193. Elsevier, 2020.","ista":"Goharshady AK, Mohammadi F. 2020. An efficient algorithm for computing network reliability in small treewidth. Reliability Engineering and System Safety. 193, 106665.","ama":"Goharshady AK, Mohammadi F. An efficient algorithm for computing network reliability in small treewidth. <i>Reliability Engineering and System Safety</i>. 2020;193. doi:<a href=\"https://doi.org/10.1016/j.ress.2019.106665\">10.1016/j.ress.2019.106665</a>","mla":"Goharshady, Amir Kafshdar, and Fatemeh Mohammadi. “An Efficient Algorithm for Computing Network Reliability in Small Treewidth.” <i>Reliability Engineering and System Safety</i>, vol. 193, 106665, Elsevier, 2020, doi:<a href=\"https://doi.org/10.1016/j.ress.2019.106665\">10.1016/j.ress.2019.106665</a>."},"publication_status":"published","volume":193,"year":"2020","doi":"10.1016/j.ress.2019.106665"},{"fulldoi":"https://doi.org/10.3389/fcell.2020.574382","ddc":["570"],"has_accepted_license":"1","pmid":1,"date_published":"2020-09-25T00:00:00Z","external_id":{"isi":["000577915900001"],"pmid":["33102480"]},"language":[{"iso":"eng"}],"article_number":"574382","corr_author":"1","author":[{"last_name":"Hansen","first_name":"Andi H","id":"38853E16-F248-11E8-B48F-1D18A9856A87","full_name":"Hansen, Andi H"},{"last_name":"Hippenmeyer","orcid":"0000-0003-2279-1061","full_name":"Hippenmeyer, Simon","first_name":"Simon","id":"37B36620-F248-11E8-B48F-1D18A9856A87"}],"scopus_import":"1","publication_identifier":{"issn":["2296-634X"]},"day":"25","article_processing_charge":"Yes (via OA deal)","type":"journal_article","article_type":"original","department":[{"_id":"SiHi"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","date_created":"2020-09-26T06:11:07Z","month":"09","ec_funded":1,"_id":"8569","intvolume":"         8","file_date_updated":"2020-09-28T13:11:17Z","oa_version":"Published Version","publication":"Frontiers in Cell and Developmental Biology","oa":1,"isi":1,"date_updated":"2026-10-29T23:30:47Z","file":[{"file_name":"2020_Frontiers_Hansen.pdf","creator":"dernst","date_updated":"2020-09-28T13:11:17Z","file_id":"8584","success":1,"access_level":"open_access","content_type":"application/pdf","date_created":"2020-09-28T13:11:17Z","file_size":5527139,"checksum":"01f731824194c94c81a5da360d997073","relation":"main_file"}],"related_material":{"record":[{"relation":"dissertation_contains","id":"9962","status":"public"}]},"year":"2020","tmp":{"image":"/images/cc_by.png","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)"},"volume":8,"publication_status":"published","citation":{"short":"A.H. Hansen, S. Hippenmeyer, Frontiers in Cell and Developmental Biology 8 (2020).","ieee":"A. H. Hansen and S. Hippenmeyer, “Non-cell-autonomous mechanisms in radial projection neuron migration in the developing cerebral cortex,” <i>Frontiers in Cell and Developmental Biology</i>, vol. 8, no. 9. Frontiers, 2020.","chicago":"Hansen, Andi H, and Simon Hippenmeyer. “Non-Cell-Autonomous Mechanisms in Radial Projection Neuron Migration in the Developing Cerebral Cortex.” <i>Frontiers in Cell and Developmental Biology</i>. Frontiers, 2020. <a href=\"https://doi.org/10.3389/fcell.2020.574382\">https://doi.org/10.3389/fcell.2020.574382</a>.","apa":"Hansen, A. H., &#38; Hippenmeyer, S. (2020). Non-cell-autonomous mechanisms in radial projection neuron migration in the developing cerebral cortex. <i>Frontiers in Cell and Developmental Biology</i>. Frontiers. <a href=\"https://doi.org/10.3389/fcell.2020.574382\">https://doi.org/10.3389/fcell.2020.574382</a>","ama":"Hansen AH, Hippenmeyer S. Non-cell-autonomous mechanisms in radial projection neuron migration in the developing cerebral cortex. <i>Frontiers in Cell and Developmental Biology</i>. 2020;8(9). doi:<a href=\"https://doi.org/10.3389/fcell.2020.574382\">10.3389/fcell.2020.574382</a>","mla":"Hansen, Andi H., and Simon Hippenmeyer. “Non-Cell-Autonomous Mechanisms in Radial Projection Neuron Migration in the Developing Cerebral Cortex.” <i>Frontiers in Cell and Developmental Biology</i>, vol. 8, no. 9, 574382, Frontiers, 2020, doi:<a href=\"https://doi.org/10.3389/fcell.2020.574382\">10.3389/fcell.2020.574382</a>.","ista":"Hansen AH, Hippenmeyer S. 2020. Non-cell-autonomous mechanisms in radial projection neuron migration in the developing cerebral cortex. Frontiers in Cell and Developmental Biology. 8(9), 574382."},"doi":"10.3389/fcell.2020.574382","publisher":"Frontiers","project":[{"name":"Molecular mechanisms of radial neuronal migration","_id":"2625A13E-B435-11E9-9278-68D0E5697425","grant_number":"24812"},{"_id":"25D61E48-B435-11E9-9278-68D0E5697425","grant_number":"618444","call_identifier":"FP7","name":"Molecular Mechanisms of Cerebral Cortex Development"}],"issue":"9","status":"public","quality_controlled":"1","title":"Non-cell-autonomous mechanisms in radial projection neuron migration in the developing cerebral cortex","abstract":[{"text":"Concerted radial migration of newly born cortical projection neurons, from their birthplace to their final target lamina, is a key step in the assembly of the cerebral cortex. The cellular and molecular mechanisms regulating the specific sequential steps of radial neuronal migration in vivo are however still unclear, let alone the effects and interactions with the extracellular environment. In any in vivo context, cells will always be exposed to a complex extracellular environment consisting of (1) secreted factors acting as potential signaling cues, (2) the extracellular matrix, and (3) other cells providing cell–cell interaction through receptors and/or direct physical stimuli. Most studies so far have described and focused mainly on intrinsic cell-autonomous gene functions in neuronal migration but there is accumulating evidence that non-cell-autonomous-, local-, systemic-, and/or whole tissue-wide effects substantially contribute to the regulation of radial neuronal migration. These non-cell-autonomous effects may differentially affect cortical neuron migration in distinct cellular environments. However, the cellular and molecular natures of such non-cell-autonomous mechanisms are mostly unknown. Furthermore, physical forces due to collective migration and/or community effects (i.e., interactions with surrounding cells) may play important roles in neocortical projection neuron migration. In this concise review, we first outline distinct models of non-cell-autonomous interactions of cortical projection neurons along their radial migration trajectory during development. We then summarize experimental assays and platforms that can be utilized to visualize and potentially probe non-cell-autonomous mechanisms. Lastly, we define key questions to address in the future.","lang":"eng"}],"acknowledgement":"AH was a recipient of a DOC Fellowship (24812) of the Austrian Academy of Sciences. This work also received support from IST Austria institutional funds; the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007–2013) under REA Grant Agreement No. 618444 to SH."},{"day":"01","type":"journal_article","article_processing_charge":"No","page":"877–894","publication_identifier":{"issn":["0022-3239"],"eissn":["1573-2878"]},"scopus_import":"1","author":[{"orcid":"0000-0001-9224-7139","last_name":"Shehu","full_name":"Shehu, Yekini","first_name":"Yekini","id":"3FC7CB58-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Gibali","first_name":"Aviv","full_name":"Gibali, Aviv"},{"full_name":"Sagratella, Simone","first_name":"Simone","last_name":"Sagratella"}],"date_published":"2020-03-01T00:00:00Z","external_id":{"isi":["000511805200009"]},"language":[{"iso":"eng"}],"has_accepted_license":"1","fulldoi":"https://doi.org/10.1007/s10957-019-01616-6","ddc":["518","510","515"],"quality_controlled":"1","publisher":"Springer Nature","project":[{"name":"Discrete Optimization in Computer Vision: Theory and Practice","call_identifier":"FP7","grant_number":"616160","_id":"25FBA906-B435-11E9-9278-68D0E5697425"}],"status":"public","acknowledgement":"We are grateful to the anonymous referees and editor whose insightful comments helped to considerably improve an earlier version of this paper. The research of the first author is supported by an ERC Grant from the Institute of Science and Technology (IST).","abstract":[{"lang":"eng","text":"In this paper, we introduce an inertial projection-type method with different updating strategies for solving quasi-variational inequalities with strongly monotone and Lipschitz continuous operators in real Hilbert spaces. Under standard assumptions, we establish different strong convergence results for the proposed algorithm. Primary numerical experiments demonstrate the potential applicability of our scheme compared with some related methods in the literature."}],"title":"Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces","publication_status":"published","citation":{"ieee":"Y. Shehu, A. Gibali, and S. Sagratella, “Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces,” <i>Journal of Optimization Theory and Applications</i>, vol. 184. Springer Nature, pp. 877–894, 2020.","short":"Y. Shehu, A. Gibali, S. Sagratella, Journal of Optimization Theory and Applications 184 (2020) 877–894.","apa":"Shehu, Y., Gibali, A., &#38; Sagratella, S. (2020). Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces. <i>Journal of Optimization Theory and Applications</i>. Springer Nature. <a href=\"https://doi.org/10.1007/s10957-019-01616-6\">https://doi.org/10.1007/s10957-019-01616-6</a>","chicago":"Shehu, Yekini, Aviv Gibali, and Simone Sagratella. “Inertial Projection-Type Methods for Solving Quasi-Variational Inequalities in Real Hilbert Spaces.” <i>Journal of Optimization Theory and Applications</i>. Springer Nature, 2020. <a href=\"https://doi.org/10.1007/s10957-019-01616-6\">https://doi.org/10.1007/s10957-019-01616-6</a>.","mla":"Shehu, Yekini, et al. “Inertial Projection-Type Methods for Solving Quasi-Variational Inequalities in Real Hilbert Spaces.” <i>Journal of Optimization Theory and Applications</i>, vol. 184, Springer Nature, 2020, pp. 877–894, doi:<a href=\"https://doi.org/10.1007/s10957-019-01616-6\">10.1007/s10957-019-01616-6</a>.","ama":"Shehu Y, Gibali A, Sagratella S. Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces. <i>Journal of Optimization Theory and Applications</i>. 2020;184:877–894. doi:<a href=\"https://doi.org/10.1007/s10957-019-01616-6\">10.1007/s10957-019-01616-6</a>","ista":"Shehu Y, Gibali A, Sagratella S. 2020. Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces. Journal of Optimization Theory and Applications. 184, 877–894."},"volume":184,"year":"2020","doi":"10.1007/s10957-019-01616-6","publication":"Journal of Optimization Theory and Applications","oa_version":"Submitted Version","intvolume":"       184","file_date_updated":"2021-03-16T23:30:04Z","oa":1,"date_updated":"2024-11-04T13:52:44Z","isi":1,"file":[{"date_updated":"2021-03-16T23:30:04Z","file_id":"8647","creator":"dernst","file_name":"2020_JourOptimizationTheoryApplic_Shehu.pdf","embargo":"2021-03-15","checksum":"9f6dc6c6bf2b48cb3a2091a9ed5feaf2","file_size":332641,"relation":"main_file","access_level":"open_access","date_created":"2020-10-12T10:40:27Z","content_type":"application/pdf"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","date_created":"2019-12-09T21:33:44Z","article_type":"original","department":[{"_id":"VlKo"}],"ec_funded":1,"_id":"7161","month":"03"},{"month":"09","_id":"8532","ec_funded":1,"department":[{"_id":"RySh"}],"article_type":"original","date_created":"2020-09-20T22:01:35Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","isi":1,"date_updated":"2026-10-29T23:30:49Z","file":[{"date_created":"2020-09-21T14:08:58Z","content_type":"application/pdf","access_level":"open_access","relation":"main_file","checksum":"2e4f62f3cfe945b7391fc3070e5a289f","file_size":5748456,"creator":"dernst","file_name":"2020_JournMolecSciences_Kleindienst.pdf","success":1,"file_id":"8551","date_updated":"2020-09-21T14:08:58Z"}],"oa":1,"related_material":{"record":[{"relation":"dissertation_contains","id":"9562","status":"public"}]},"file_date_updated":"2020-09-21T14:08:58Z","intvolume":"        21","publication":"International Journal of Molecular Sciences","oa_version":"Published Version","doi":"10.3390/ijms21186737","tmp":{"image":"/images/cc_by.png","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)"},"year":"2020","volume":21,"publication_status":"published","citation":{"chicago":"Kleindienst, David, Jacqueline-Claire Montanaro-Punzengruber, Pradeep Bhandari, Matthew J Case, Yugo Fukazawa, and Ryuichi Shigemoto. “Deep Learning-Assisted High-Throughput Analysis of Freeze-Fracture Replica Images Applied to Glutamate Receptors and Calcium Channels at Hippocampal Synapses.” <i>International Journal of Molecular Sciences</i>. MDPI, 2020. <a href=\"https://doi.org/10.3390/ijms21186737\">https://doi.org/10.3390/ijms21186737</a>.","apa":"Kleindienst, D., Montanaro-Punzengruber, J.-C., Bhandari, P., Case, M. J., Fukazawa, Y., &#38; Shigemoto, R. (2020). Deep learning-assisted high-throughput analysis of freeze-fracture replica images applied to glutamate receptors and calcium channels at hippocampal synapses. <i>International Journal of Molecular Sciences</i>. MDPI. <a href=\"https://doi.org/10.3390/ijms21186737\">https://doi.org/10.3390/ijms21186737</a>","short":"D. Kleindienst, J.-C. Montanaro-Punzengruber, P. Bhandari, M.J. Case, Y. Fukazawa, R. Shigemoto, International Journal of Molecular Sciences 21 (2020).","ieee":"D. Kleindienst, J.-C. Montanaro-Punzengruber, P. Bhandari, M. J. Case, Y. Fukazawa, and R. Shigemoto, “Deep learning-assisted high-throughput analysis of freeze-fracture replica images applied to glutamate receptors and calcium channels at hippocampal synapses,” <i>International Journal of Molecular Sciences</i>, vol. 21, no. 18. MDPI, 2020.","ista":"Kleindienst D, Montanaro-Punzengruber J-C, Bhandari P, Case MJ, Fukazawa Y, Shigemoto R. 2020. Deep learning-assisted high-throughput analysis of freeze-fracture replica images applied to glutamate receptors and calcium channels at hippocampal synapses. International Journal of Molecular Sciences. 21(18), 6737.","ama":"Kleindienst D, Montanaro-Punzengruber J-C, Bhandari P, Case MJ, Fukazawa Y, Shigemoto R. Deep learning-assisted high-throughput analysis of freeze-fracture replica images applied to glutamate receptors and calcium channels at hippocampal synapses. <i>International Journal of Molecular Sciences</i>. 2020;21(18). doi:<a href=\"https://doi.org/10.3390/ijms21186737\">10.3390/ijms21186737</a>","mla":"Kleindienst, David, et al. “Deep Learning-Assisted High-Throughput Analysis of Freeze-Fracture Replica Images Applied to Glutamate Receptors and Calcium Channels at Hippocampal Synapses.” <i>International Journal of Molecular Sciences</i>, vol. 21, no. 18, 6737, MDPI, 2020, doi:<a href=\"https://doi.org/10.3390/ijms21186737\">10.3390/ijms21186737</a>."},"abstract":[{"text":"The molecular anatomy of synapses defines their characteristics in transmission and plasticity. Precise measurements of the number and distribution of synaptic proteins are important for our understanding of synapse heterogeneity within and between brain regions. Freeze–fracture replica immunogold electron microscopy enables us to analyze them quantitatively on a two-dimensional membrane surface. Here, we introduce Darea software, which utilizes deep learning for analysis of replica images and demonstrate its usefulness for quick measurements of the pre- and postsynaptic areas, density and distribution of gold particles at synapses in a reproducible manner. We used Darea for comparing glutamate receptor and calcium channel distributions between hippocampal CA3-CA1 spine synapses on apical and basal dendrites, which differ in signaling pathways involved in synaptic plasticity. We found that apical synapses express a higher density of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors and a stronger increase of AMPA receptors with synaptic size, while basal synapses show a larger increase in N-methyl-D-aspartate (NMDA) receptors with size. Interestingly, AMPA and NMDA receptors are segregated within postsynaptic sites and negatively correlated in density among both apical and basal synapses. In the presynaptic sites, Cav2.1 voltage-gated calcium channels show similar densities in apical and basal synapses with distributions consistent with an exclusion zone model of calcium channel-release site topography.","lang":"eng"}],"title":"Deep learning-assisted high-throughput analysis of freeze-fracture replica images applied to glutamate receptors and calcium channels at hippocampal synapses","acknowledgement":"This research was funded by Austrian Academy of Sciences, DOC fellowship to D.K., European Research\r\nCouncil Advanced Grant 694539 and European Union Human Brain Project (HBP) SGA2 785907 to R.S.\r\nWe acknowledge Elena Hollergschwandtner for technical support.","status":"public","issue":"18","publisher":"MDPI","project":[{"name":"In situ analysis of single channel subunit composition in neurons: physiological implication in synaptic plasticity and behaviour","grant_number":"694539","_id":"25CA28EA-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"},{"name":"Mechanism of formation and maintenance of input side-dependent asymmetry in the hippocampus","_id":"25D32BC0-B435-11E9-9278-68D0E5697425"},{"name":"Human Brain Project Specific Grant Agreement 2","grant_number":"785907","_id":"26436750-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"}],"quality_controlled":"1","ddc":["570"],"fulldoi":"https://doi.org/10.3390/ijms21186737","has_accepted_license":"1","language":[{"iso":"eng"}],"external_id":{"isi":["000579945300001"]},"date_published":"2020-09-14T00:00:00Z","author":[{"full_name":"Kleindienst, David","id":"42E121A4-F248-11E8-B48F-1D18A9856A87","first_name":"David","last_name":"Kleindienst"},{"full_name":"Montanaro-Punzengruber, Jacqueline-Claire","id":"3786AB44-F248-11E8-B48F-1D18A9856A87","first_name":"Jacqueline-Claire","last_name":"Montanaro-Punzengruber"},{"orcid":"0000-0003-0863-4481","last_name":"Bhandari","id":"45EDD1BC-F248-11E8-B48F-1D18A9856A87","first_name":"Pradeep","full_name":"Bhandari, Pradeep"},{"last_name":"Case","first_name":"Matthew J","id":"44B7CA5A-F248-11E8-B48F-1D18A9856A87","full_name":"Case, Matthew J"},{"last_name":"Fukazawa","first_name":"Yugo","full_name":"Fukazawa, Yugo"},{"orcid":"0000-0001-8761-9444","last_name":"Shigemoto","full_name":"Shigemoto, Ryuichi","id":"499F3ABC-F248-11E8-B48F-1D18A9856A87","first_name":"Ryuichi"}],"scopus_import":"1","publication_identifier":{"issn":["1661-6596"],"eissn":["1422-0067"]},"corr_author":"1","article_number":"6737","article_processing_charge":"No","type":"journal_article","day":"14"},{"article_number":"100856","corr_author":"1","publication_identifier":{"issn":["1751-570X"]},"scopus_import":"1","author":[{"orcid":"0000−0003−2936−5719","last_name":"Garcia Soto","first_name":"Miriam","id":"4B3207F6-F248-11E8-B48F-1D18A9856A87","full_name":"Garcia Soto, Miriam"},{"last_name":"Prabhakar","full_name":"Prabhakar, Pavithra","first_name":"Pavithra"}],"day":"01","type":"journal_article","article_processing_charge":"No","has_accepted_license":"1","fulldoi":"https://doi.org/10.1016/j.nahs.2020.100856","ddc":["000"],"date_published":"2020-05-01T00:00:00Z","external_id":{"isi":["000528828600003"]},"language":[{"iso":"eng"}],"citation":{"ieee":"M. Garcia Soto and P. Prabhakar, “Abstraction based verification of stability of polyhedral switched systems,” <i>Nonlinear Analysis: Hybrid Systems</i>, vol. 36, no. 5. Elsevier, 2020.","short":"M. Garcia Soto, P. Prabhakar, Nonlinear Analysis: Hybrid Systems 36 (2020).","apa":"Garcia Soto, M., &#38; Prabhakar, P. (2020). Abstraction based verification of stability of polyhedral switched systems. <i>Nonlinear Analysis: Hybrid Systems</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.nahs.2020.100856\">https://doi.org/10.1016/j.nahs.2020.100856</a>","chicago":"Garcia Soto, Miriam, and Pavithra Prabhakar. “Abstraction Based Verification of Stability of Polyhedral Switched Systems.” <i>Nonlinear Analysis: Hybrid Systems</i>. Elsevier, 2020. <a href=\"https://doi.org/10.1016/j.nahs.2020.100856\">https://doi.org/10.1016/j.nahs.2020.100856</a>.","mla":"Garcia Soto, Miriam, and Pavithra Prabhakar. “Abstraction Based Verification of Stability of Polyhedral Switched Systems.” <i>Nonlinear Analysis: Hybrid Systems</i>, vol. 36, no. 5, 100856, Elsevier, 2020, doi:<a href=\"https://doi.org/10.1016/j.nahs.2020.100856\">10.1016/j.nahs.2020.100856</a>.","ama":"Garcia Soto M, Prabhakar P. Abstraction based verification of stability of polyhedral switched systems. <i>Nonlinear Analysis: Hybrid Systems</i>. 2020;36(5). doi:<a href=\"https://doi.org/10.1016/j.nahs.2020.100856\">10.1016/j.nahs.2020.100856</a>","ista":"Garcia Soto M, Prabhakar P. 2020. Abstraction based verification of stability of polyhedral switched systems. Nonlinear Analysis: Hybrid Systems. 36(5), 100856."},"OA_place":"repository","publication_status":"published","tmp":{"image":"/images/cc_by_nc_nd.png","short":"CC BY-NC-ND (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"},"year":"2020","volume":36,"doi":"10.1016/j.nahs.2020.100856","OA_type":"green","license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","quality_controlled":"1","project":[{"_id":"25863FF4-B435-11E9-9278-68D0E5697425","grant_number":"S11407","call_identifier":"FWF","name":"Game Theory"},{"call_identifier":"FWF","grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425","name":"Formal methods for the design and analysis of complex systems"}],"publisher":"Elsevier","status":"public","issue":"5","title":"Abstraction based verification of stability of polyhedral switched systems","abstract":[{"text":"This paper presents a novel abstraction technique for analyzing Lyapunov and asymptotic stability of polyhedral switched systems. A polyhedral switched system is a hybrid system in which the continuous dynamics is specified by polyhedral differential inclusions, the invariants and guards are specified by polyhedral sets and the switching between the modes do not involve reset of variables. A finite state weighted graph abstracting the polyhedral switched system is constructed from a finite partition of the state–space, such that the satisfaction of certain graph conditions, such as the absence of cycles with product of weights on the edges greater than (or equal) to 1, implies the stability of the system. However, the graph is in general conservative and hence, the violation of the graph conditions does not imply instability. If the analysis fails to establish stability due to the conservativeness in the approximation, a counterexample (cycle with product of edge weights greater than or equal to 1) indicating a potential reason for the failure is returned. Further, a more precise approximation of the switched system can be constructed by considering a finer partition of the state–space in the construction of the finite weighted graph. We present experimental results on analyzing stability of switched systems using the above method.","lang":"eng"}],"date_created":"2020-02-02T23:00:59Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_type":"original","department":[{"_id":"ToHe"}],"_id":"7426","month":"05","publication":"Nonlinear Analysis: Hybrid Systems","oa_version":"Submitted Version","intvolume":"        36","file_date_updated":"2022-05-16T22:30:04Z","oa":1,"date_updated":"2026-07-28T12:57:27Z","isi":1,"file":[{"checksum":"560abfddb53f9fe921b6744f59f2cfaa","file_size":818774,"relation":"main_file","access_level":"open_access","content_type":"application/pdf","date_created":"2020-10-21T13:16:45Z","file_id":"8688","date_updated":"2022-05-16T22:30:04Z","creator":"dernst","file_name":"2020_NAHS_GarciaSoto.pdf","embargo":"2022-05-15"}]},{"publication_identifier":{"eissn":["2663-337X"]},"author":[{"full_name":"Kainrath, Stephanie","first_name":"Stephanie","id":"32CFBA64-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6709-2195","last_name":"Kainrath"}],"page":"98","corr_author":"1","type":"dissertation","article_processing_charge":"No","day":"24","has_accepted_license":"1","degree_awarded":"PhD","ddc":["570"],"fulldoi":"https://doi.org/10.15479/AT:ISTA:7680","language":[{"iso":"eng"}],"date_published":"2020-04-24T00:00:00Z","alternative_title":["ISTA Thesis"],"doi":"10.15479/AT:ISTA:7680","citation":{"mla":"Kainrath, Stephanie. <i>Synthetic Tools for Optogenetic and Chemogenetic Inhibition of Cellular Signals</i>. Institute of Science and Technology Austria, 2020, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:7680\">10.15479/AT:ISTA:7680</a>.","ama":"Kainrath S. Synthetic tools for optogenetic and chemogenetic inhibition of cellular signals. 2020. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:7680\">10.15479/AT:ISTA:7680</a>","ista":"Kainrath S. 2020. Synthetic tools for optogenetic and chemogenetic inhibition of cellular signals. Institute of Science and Technology Austria.","ieee":"S. Kainrath, “Synthetic tools for optogenetic and chemogenetic inhibition of cellular signals,” Institute of Science and Technology Austria, 2020.","short":"S. Kainrath, Synthetic Tools for Optogenetic and Chemogenetic Inhibition of Cellular Signals, Institute of Science and Technology Austria, 2020.","apa":"Kainrath, S. (2020). <i>Synthetic tools for optogenetic and chemogenetic inhibition of cellular signals</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:7680\">https://doi.org/10.15479/AT:ISTA:7680</a>","chicago":"Kainrath, Stephanie. “Synthetic Tools for Optogenetic and Chemogenetic Inhibition of Cellular Signals.” Institute of Science and Technology Austria, 2020. <a href=\"https://doi.org/10.15479/AT:ISTA:7680\">https://doi.org/10.15479/AT:ISTA:7680</a>."},"publication_status":"published","year":"2020","abstract":[{"lang":"eng","text":"Proteins and their complex dynamic interactions regulate cellular mechanisms from sensing and transducing extracellular signals, to mediating genetic responses, and sustaining or changing cell morphology. To manipulate these protein-protein interactions (PPIs) that govern the behavior and fate of cells, synthetically constructed, genetically encoded tools provide the means to precisely target proteins of interest (POIs), and control their subcellular localization and activity in vitro and in vivo. Ideal synthetic tools react to an orthogonal cue, i.e. a trigger that does not activate any other endogenous process, thereby allowing manipulation of the POI alone.\r\nIn optogenetics, naturally occurring photosensory domain from plants, algae and bacteria are re-purposed and genetically fused to POIs. Illumination with light of a specific wavelength triggers a conformational change that can mediate PPIs, such as dimerization or oligomerization. By using light as a trigger, these tools can be activated with high spatial and temporal precision, on subcellular and millisecond scales. Chemogenetic tools consist of protein domains that recognize and bind small molecules. By genetic fusion to POIs, these domains can mediate PPIs upon addition of their specific ligands, which are often synthetically designed to provide highly specific interactions and exhibit good bioavailability.\r\nMost optogenetic tools to mediate PPIs are based on well-studied photoreceptors responding to red, blue or near-UV light, leaving a striking gap in the green band of the visible light spectrum. Among both optogenetic and chemogenetic tools, there is an abundance of methods to induce PPIs, but tools to disrupt them require UV illumination, rely on covalent linkage and subsequent enzymatic cleavage or initially result in protein clustering of unknown stoichiometry.\r\nThis work describes how the recently structurally and photochemically characterized green-light responsive cobalamin-binding domains (CBDs) from bacterial transcription factors were re-purposed to function as a green-light responsive optogenetic tool. In contrast to previously engineered optogenetic tools, CBDs do not induce PPI, but rather confer a PPI already upon expression, which can be rapidly disrupted by illumination. This was employed to mimic inhibition of constitutive activity of a growth factor receptor, and successfully implement for cell signalling in mammalian cells and in vivo to rescue development in zebrafish. This work further describes the development and application of a chemically induced de-dimerizer (CDD) based on a recently identified and structurally described bacterial oxyreductase. CDD forms a dimer upon expression in absence of its cofactor, the flavin derivative F420. Safety and of domain expression and ligand exposure are demonstrated in vitro and in vivo in zebrafish. The system is further applied to inhibit cell signalling output from a chimeric receptor upon F420 treatment.\r\nCBDs and CDD expand the repertoire of synthetic tools by providing novel mechanisms of mediating PPIs, and by recognizing previously not utilized cues. In the future, they can readily be combined with existing synthetic tools to functionally manipulate PPIs in vitro and in vivo."}],"title":"Synthetic tools for optogenetic and chemogenetic inhibition of cellular signals","supervisor":[{"orcid":"0000-0002-8023-9315","last_name":"Janovjak","full_name":"Janovjak, Harald L","first_name":"Harald L","id":"33BA6C30-F248-11E8-B48F-1D18A9856A87"}],"status":"public","publisher":"Institute of Science and Technology Austria","_id":"7680","month":"04","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2020-04-24T16:00:51Z","department":[{"_id":"CaGu"}],"related_material":{"record":[{"status":"public","id":"1028","relation":"dissertation_contains"}]},"date_updated":"2026-08-12T09:19:22Z","file":[{"file_id":"7692","date_updated":"2021-10-31T23:30:05Z","embargo":"2021-10-30","file_name":"Thesis_without-signatures_PDFA.pdf","creator":"stgingl","file_size":3268017,"checksum":"fb9a4468eb27be92690728e35c823796","relation":"main_file","access_level":"open_access","date_created":"2020-04-28T11:19:21Z","content_type":"application/pdf"},{"creator":"stgingl","file_name":"Thesis_without signatures.docx","date_updated":"2021-10-31T23:30:05Z","file_id":"7693","date_created":"2020-04-28T11:19:24Z","content_type":"application/octet-stream","access_level":"closed","relation":"source_file","file_size":5167703,"checksum":"f6c80ca97104a631a328cb79a2c53493","embargo_to":"open_access"}],"oa":1,"oa_version":"None","file_date_updated":"2021-10-31T23:30:05Z"},{"status":"public","publisher":"Institute of Science and Technology Austria","project":[{"grant_number":"W1232","_id":"2548AE96-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Molecular Drug Targets"},{"name":"Stem Cell Modulation in Neural Development and Regeneration/ P07-Neural stem cells in autism and epilepsy","_id":"05A0D778-7A3F-11EA-A408-12923DDC885E","grant_number":"F7807"}],"supervisor":[{"orcid":"0000-0002-7673-7178","last_name":"Novarino","full_name":"Novarino, Gaia","first_name":"Gaia","id":"3E57A680-F248-11E8-B48F-1D18A9856A87"}],"title":"Illuminating the role of Cul3 in autism spectrum disorder pathogenesis","abstract":[{"lang":"eng","text":"The development of the human brain occurs through a tightly regulated series of dynamic and adaptive processes during prenatal and postnatal life. A disruption of this strictly orchestrated series of events can lead to a number of neurodevelopmental conditions, including Autism Spectrum Disorders (ASDs). ASDs are a very common, etiologically and phenotypically heterogeneous group of disorders sharing the core symptoms of social interaction and communication deficits and restrictive and repetitive interests and behaviors. They are estimated to affect one in 59 individuals in the U.S. and, over the last three decades, mutations in more than a hundred genetic loci have been convincingly linked to ASD pathogenesis. Yet, for the vast majority of these ASD-risk genes their role during brain development and precise molecular function still remain elusive.\r\nDe novo loss of function mutations in the ubiquitin ligase-encoding gene Cullin 3 (CUL3) lead to ASD. In the study described here, we used Cul3 mouse models to evaluate the consequences of Cul3 mutations in vivo. Our results show that Cul3 heterozygous knockout mice exhibit deficits in motor coordination as well as ASD-relevant social and cognitive impairments. Cul3+/-, Cul3+/fl Emx1-Cre and Cul3fl/fl Emx1-Cre mutant brains display cortical lamination abnormalities due to defective migration of post-mitotic excitatory neurons, as well as reduced numbers of excitatory and inhibitory neurons. In line with the observed abnormal cortical organization, Cul3 heterozygous deletion is associated with decreased spontaneous excitatory and inhibitory activity in the cortex. At the molecular level we show that Cul3 regulates cytoskeletal and adhesion protein abundance in the mouse embryonic cortex. Abnormal regulation of cytoskeletal proteins in Cul3 mutant neural cells results in atypical organization of the actin mesh at the cell leading edge. Of note, heterozygous deletion of Cul3 in adult mice does not induce the majority of the behavioral defects observed in constitutive Cul3 haploinsufficient animals, pointing to a critical time-window for Cul3 deficiency.\r\nIn conclusion, our data indicate that Cul3 plays a critical role in the regulation of cytoskeletal proteins and neuronal migration. ASD-associated defects and behavioral abnormalities are primarily due to dosage sensitive Cul3 functions at early brain developmental stages."}],"acknowledgement":"I would like to especially thank Armel Nicolas from the Proteomics and Christoph Sommer from the Bioimaging Facilities for the data analysis, and to thank the team of the Preclinical Facility, especially Sabina Deixler, Angela Schlerka, Anita Lepold, Mihalea Mihai and Michael Schun for taking care of the mouse line maintenance and their great support.","year":"2020","OA_place":"publisher","publication_status":"published","citation":{"ista":"Morandell J. 2020. Illuminating the role of Cul3 in autism spectrum disorder pathogenesis. Institute of Science and Technology Austria.","ama":"Morandell J. Illuminating the role of Cul3 in autism spectrum disorder pathogenesis. 2020. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8620\">10.15479/AT:ISTA:8620</a>","mla":"Morandell, Jasmin. <i>Illuminating the Role of Cul3 in Autism Spectrum Disorder Pathogenesis</i>. Institute of Science and Technology Austria, 2020, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8620\">10.15479/AT:ISTA:8620</a>.","chicago":"Morandell, Jasmin. “Illuminating the Role of Cul3 in Autism Spectrum Disorder Pathogenesis.” Institute of Science and Technology Austria, 2020. <a href=\"https://doi.org/10.15479/AT:ISTA:8620\">https://doi.org/10.15479/AT:ISTA:8620</a>.","apa":"Morandell, J. (2020). <i>Illuminating the role of Cul3 in autism spectrum disorder pathogenesis</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:8620\">https://doi.org/10.15479/AT:ISTA:8620</a>","short":"J. Morandell, Illuminating the Role of Cul3 in Autism Spectrum Disorder Pathogenesis, Institute of Science and Technology Austria, 2020.","ieee":"J. Morandell, “Illuminating the role of Cul3 in autism spectrum disorder pathogenesis,” Institute of Science and Technology Austria, 2020."},"doi":"10.15479/AT:ISTA:8620","file_date_updated":"2021-10-16T22:30:04Z","oa_version":"Published Version","date_updated":"2026-08-12T09:55:08Z","file":[{"creator":"jmorande","file_name":"Jasmin_Morandell_Thesis-2020_final.pdf","embargo":"2021-10-15","file_id":"8621","date_updated":"2021-10-16T22:30:04Z","access_level":"open_access","date_created":"2020-10-07T14:41:49Z","content_type":"application/pdf","file_size":16155786,"checksum":"7ee83e42de3e5ce2fedb44dff472f75f","relation":"main_file"},{"creator":"jmorande","file_name":"Jasmin_Morandell_Thesis-2020_final.zip","date_updated":"2021-10-16T22:30:04Z","file_id":"8622","access_level":"closed","content_type":"application/x-zip-compressed","date_created":"2020-10-07T14:45:07Z","embargo_to":"open_access","file_size":24344152,"checksum":"5e0464af453734210ce7aab7b4a92e3a","relation":"source_file"}],"oa":1,"related_material":{"record":[{"relation":"part_of_dissertation","id":"7800","status":"public"},{"id":"8131","status":"public","relation":"part_of_dissertation"}]},"department":[{"_id":"GaNo"}],"user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","date_created":"2020-10-07T14:53:13Z","month":"10","_id":"8620","day":"12","acknowledged_ssus":[{"_id":"Bio"},{"_id":"PreCl"}],"article_processing_charge":"No","type":"dissertation","corr_author":"1","page":"138","author":[{"last_name":"Morandell","full_name":"Morandell, Jasmin","first_name":"Jasmin","id":"4739D480-F248-11E8-B48F-1D18A9856A87"}],"publication_identifier":{"issn":["2663-337X"]},"alternative_title":["ISTA Thesis"],"date_published":"2020-10-12T00:00:00Z","language":[{"iso":"eng"}],"degree_awarded":"PhD","ddc":["610"],"fulldoi":"https://doi.org/10.15479/AT:ISTA:8620","has_accepted_license":"1"},{"date_published":"2020-01-11T00:00:00Z","language":[{"iso":"eng"}],"fulldoi":"https://doi.org/10.1101/2020.01.10.902064 ","ddc":["570"],"has_accepted_license":"1","day":"11","article_processing_charge":"No","acknowledged_ssus":[{"_id":"PreCl"}],"type":"preprint","corr_author":"1","author":[{"first_name":"Jasmin","id":"4739D480-F248-11E8-B48F-1D18A9856A87","full_name":"Morandell, Jasmin","last_name":"Morandell"},{"last_name":"Schwarz","first_name":"Lena A","id":"29A8453C-F248-11E8-B48F-1D18A9856A87","full_name":"Schwarz, Lena A"},{"orcid":"0000-0003-1843-3173","last_name":"Basilico","full_name":"Basilico, Bernadette","id":"36035796-5ACA-11E9-A75E-7AF2E5697425","first_name":"Bernadette"},{"full_name":"Tasciyan, Saren","first_name":"Saren","id":"4323B49C-F248-11E8-B48F-1D18A9856A87","last_name":"Tasciyan","orcid":"0000-0003-1671-393X"},{"last_name":"Nicolas","first_name":"Armel","id":"2A103192-F248-11E8-B48F-1D18A9856A87","full_name":"Nicolas, Armel"},{"last_name":"Sommer","orcid":"0000-0003-1216-9105","first_name":"Christoph M","id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87","full_name":"Sommer, Christoph M"},{"last_name":"Kreuzinger","first_name":"Caroline","id":"382077BA-F248-11E8-B48F-1D18A9856A87","full_name":"Kreuzinger, Caroline"},{"first_name":"Lisa","id":"3B2ABCF4-F248-11E8-B48F-1D18A9856A87","full_name":"Knaus, Lisa","last_name":"Knaus"},{"last_name":"Dobler","full_name":"Dobler, Zoe","first_name":"Zoe","id":"D23090A2-9057-11EA-883A-A8396FC7A38F"},{"last_name":"Cacci","first_name":"Emanuele","full_name":"Cacci, Emanuele"},{"full_name":"Danzl, Johann G","id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87","first_name":"Johann G","orcid":"0000-0001-8559-3973","last_name":"Danzl"},{"last_name":"Novarino","orcid":"0000-0002-7673-7178","first_name":"Gaia","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","full_name":"Novarino, Gaia"}],"file_date_updated":"2020-07-14T12:48:03Z","publication":"bioRxiv","oa_version":"Preprint","oa":1,"date_updated":"2026-10-29T23:30:52Z","file":[{"date_created":"2020-05-05T14:31:19Z","content_type":"application/pdf","access_level":"open_access","relation":"main_file","checksum":"c6799ab5daba80efe8e2ed63c15f8c81","file_size":2931370,"creator":"rsix","file_name":"2020.01.10.902064v1.full.pdf","date_updated":"2020-07-14T12:48:03Z","file_id":"7801"}],"das_tickbox":"1","related_material":{"record":[{"relation":"later_version","id":"9429","status":"public"},{"status":"public","id":"8620","relation":"dissertation_contains"}]},"department":[{"_id":"JoDa"},{"_id":"GaNo"},{"_id":"LifeSc"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2020-05-05T14:31:33Z","month":"01","_id":"7800","project":[{"call_identifier":"FWF","grant_number":"I03600","_id":"265CB4D0-B435-11E9-9278-68D0E5697425","name":"Optical control of synaptic function via adhesion molecules"},{"call_identifier":"FWF","_id":"2548AE96-B435-11E9-9278-68D0E5697425","grant_number":"W1232","name":"Molecular Drug Targets"}],"status":"public","title":"Cul3 regulates cytoskeleton protein homeostasis and cell migration during a critical window of brain development","abstract":[{"text":"De novo loss of function mutations in the ubiquitin ligase-encoding gene Cullin3 (CUL3) lead to autism spectrum disorder (ASD). Here, we used Cul3 mouse models to evaluate the consequences of Cul3 mutations in vivo. Our results show that Cul3 haploinsufficient mice exhibit deficits in motor coordination as well as ASD-relevant social and cognitive impairments. Cul3 mutant brain displays cortical lamination abnormalities due to defective neuronal migration and reduced numbers of excitatory and inhibitory neurons. In line with the observed abnormal columnar organization, Cul3 haploinsufficiency is associated with decreased spontaneous excitatory and inhibitory activity in the cortex. At the molecular level, employing a quantitative proteomic approach, we show that Cul3 regulates cytoskeletal and adhesion protein abundance in mouse embryos. Abnormal regulation of cytoskeletal proteins in Cul3 mutant neuronal cells results in atypical organization of the actin mesh at the cell leading edge, likely causing the observed migration deficits. In contrast to these important functions early in development, Cul3 deficiency appears less relevant at adult stages. In fact, induction of Cul3 haploinsufficiency in adult mice does not result in the behavioral defects observed in constitutive Cul3 haploinsufficient animals. Taken together, our data indicate that Cul3 has a critical role in the regulation of cytoskeletal proteins and neuronal migration and that ASD-associated defects and behavioral abnormalities are primarily due to Cul3 functions at early developmental stages.","lang":"eng"}],"year":"2020","tmp":{"image":"/images/cc_by_nc_nd.png","short":"CC BY-NC-ND (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"},"publication_status":"draft","citation":{"ista":"Morandell J, Schwarz LA, Basilico B, Tasciyan S, Nicolas A, Sommer CM, Kreuzinger C, Knaus L, Dobler Z, Cacci E, Danzl JG, Novarino G. Cul3 regulates cytoskeleton protein homeostasis and cell migration during a critical window of brain development. bioRxiv, <a href=\"https://doi.org/10.1101/2020.01.10.902064 \">10.1101/2020.01.10.902064 </a>.","mla":"Morandell, Jasmin, et al. “Cul3 Regulates Cytoskeleton Protein Homeostasis and Cell Migration during a Critical Window of Brain Development.” <i>BioRxiv</i>, doi:<a href=\"https://doi.org/10.1101/2020.01.10.902064 \">10.1101/2020.01.10.902064 </a>.","ama":"Morandell J, Schwarz LA, Basilico B, et al. Cul3 regulates cytoskeleton protein homeostasis and cell migration during a critical window of brain development. <i>bioRxiv</i>. doi:<a href=\"https://doi.org/10.1101/2020.01.10.902064 \">10.1101/2020.01.10.902064 </a>","apa":"Morandell, J., Schwarz, L. A., Basilico, B., Tasciyan, S., Nicolas, A., Sommer, C. M., … Novarino, G. (n.d.). Cul3 regulates cytoskeleton protein homeostasis and cell migration during a critical window of brain development. <i>bioRxiv</i>. <a href=\"https://doi.org/10.1101/2020.01.10.902064 \">https://doi.org/10.1101/2020.01.10.902064 </a>","chicago":"Morandell, Jasmin, Lena A Schwarz, Bernadette Basilico, Saren Tasciyan, Armel Nicolas, Christoph M Sommer, Caroline Kreuzinger, et al. “Cul3 Regulates Cytoskeleton Protein Homeostasis and Cell Migration during a Critical Window of Brain Development.” <i>BioRxiv</i>, n.d. <a href=\"https://doi.org/10.1101/2020.01.10.902064 \">https://doi.org/10.1101/2020.01.10.902064 </a>.","ieee":"J. Morandell <i>et al.</i>, “Cul3 regulates cytoskeleton protein homeostasis and cell migration during a critical window of brain development,” <i>bioRxiv</i>. .","short":"J. Morandell, L.A. Schwarz, B. Basilico, S. Tasciyan, A. Nicolas, C.M. Sommer, C. Kreuzinger, L. Knaus, Z. Dobler, E. Cacci, J.G. Danzl, G. Novarino, BioRxiv (n.d.)."},"doi":"10.1101/2020.01.10.902064 "},{"scopus_import":"1","publication_identifier":{"eissn":["1879-0380"],"issn":["0959-437X"]},"author":[{"last_name":"Basilico","orcid":"0000-0003-1843-3173","full_name":"Basilico, Bernadette","id":"36035796-5ACA-11E9-A75E-7AF2E5697425","first_name":"Bernadette"},{"full_name":"Morandell, Jasmin","id":"4739D480-F248-11E8-B48F-1D18A9856A87","first_name":"Jasmin","last_name":"Morandell"},{"full_name":"Novarino, Gaia","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","first_name":"Gaia","orcid":"0000-0002-7673-7178","last_name":"Novarino"}],"page":"126-137","corr_author":"1","type":"journal_article","article_processing_charge":"Yes (via OA deal)","day":"01","has_accepted_license":"1","fulldoi":"https://doi.org/10.1016/j.gde.2020.06.004","ddc":["570"],"language":[{"iso":"eng"}],"date_published":"2020-12-01T00:00:00Z","external_id":{"isi":["000598918900019"],"pmid":["32659636"]},"pmid":1,"doi":"10.1016/j.gde.2020.06.004","publication_status":"published","citation":{"ista":"Basilico B, Morandell J, Novarino G. 2020. Molecular mechanisms for targeted ASD treatments. Current Opinion in Genetics &#38; Development. 65(12), 126–137.","mla":"Basilico, Bernadette, et al. “Molecular Mechanisms for Targeted ASD Treatments.” <i>Current Opinion in Genetics &#38; Development</i>, vol. 65, no. 12, Elsevier, 2020, pp. 126–37, doi:<a href=\"https://doi.org/10.1016/j.gde.2020.06.004\">10.1016/j.gde.2020.06.004</a>.","ama":"Basilico B, Morandell J, Novarino G. Molecular mechanisms for targeted ASD treatments. <i>Current Opinion in Genetics &#38; Development</i>. 2020;65(12):126-137. doi:<a href=\"https://doi.org/10.1016/j.gde.2020.06.004\">10.1016/j.gde.2020.06.004</a>","apa":"Basilico, B., Morandell, J., &#38; Novarino, G. (2020). Molecular mechanisms for targeted ASD treatments. <i>Current Opinion in Genetics &#38; Development</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.gde.2020.06.004\">https://doi.org/10.1016/j.gde.2020.06.004</a>","chicago":"Basilico, Bernadette, Jasmin Morandell, and Gaia Novarino. “Molecular Mechanisms for Targeted ASD Treatments.” <i>Current Opinion in Genetics &#38; Development</i>. Elsevier, 2020. <a href=\"https://doi.org/10.1016/j.gde.2020.06.004\">https://doi.org/10.1016/j.gde.2020.06.004</a>.","ieee":"B. Basilico, J. Morandell, and G. Novarino, “Molecular mechanisms for targeted ASD treatments,” <i>Current Opinion in Genetics &#38; Development</i>, vol. 65, no. 12. Elsevier, pp. 126–137, 2020.","short":"B. Basilico, J. Morandell, G. Novarino, Current Opinion in Genetics &#38; Development 65 (2020) 126–137."},"tmp":{"image":"/images/cc_by_nc_nd.png","short":"CC BY-NC-ND (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"},"volume":65,"year":"2020","title":"Molecular mechanisms for targeted ASD treatments","abstract":[{"lang":"eng","text":"The possibility to generate construct valid animal models enabled the development and testing of therapeutic strategies targeting the core features of autism spectrum disorders (ASDs). At the same time, these studies highlighted the necessity of identifying sensitive developmental time windows for successful therapeutic interventions. Animal and human studies also uncovered the possibility to stratify the variety of ASDs in molecularly distinct subgroups, potentially facilitating effective treatment design. Here, we focus on the molecular pathways emerging as commonly affected by mutations in diverse ASD-risk genes, on their role during critical windows of brain development and the potential treatments targeting these biological processes."}],"quality_controlled":"1","publisher":"Elsevier","project":[{"call_identifier":"H2020","_id":"260C2330-B435-11E9-9278-68D0E5697425","grant_number":"754411","name":"ISTplus - Postdoctoral Fellowships"},{"name":"Molecular Drug Targets","_id":"2548AE96-B435-11E9-9278-68D0E5697425","grant_number":"W1232","call_identifier":"FWF"},{"name":"Stem Cell Modulation in Neural Development and Regeneration/ P07-Neural stem cells in autism and epilepsy","_id":"05A0D778-7A3F-11EA-A408-12923DDC885E","grant_number":"F7807"}],"status":"public","issue":"12","_id":"8131","ec_funded":1,"month":"12","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2020-07-19T22:00:58Z","article_type":"original","department":[{"_id":"GaNo"}],"related_material":{"record":[{"relation":"dissertation_contains","id":"8620","status":"public"}]},"oa":1,"date_updated":"2026-10-29T23:30:52Z","file":[{"file_size":1381545,"relation":"main_file","access_level":"open_access","date_created":"2020-07-22T06:47:45Z","content_type":"application/pdf","success":1,"file_id":"8146","date_updated":"2020-07-22T06:47:45Z","file_name":"2020_CurrentOpGenetics_Basilico.pdf","creator":"dernst"}],"isi":1,"publication":"Current Opinion in Genetics & Development","oa_version":"Published Version","intvolume":"        65","file_date_updated":"2020-07-22T06:47:45Z"},{"ddc":["000"],"has_accepted_license":"1","arxiv":1,"external_id":{"arxiv":["1912.10095"]},"date_published":"2020-07-13T00:00:00Z","language":[{"iso":"eng"}],"page":"8773-8784","author":[{"last_name":"Shevchenko","first_name":"Aleksandr","id":"F2B06EC2-C99E-11E9-89F0-752EE6697425","full_name":"Shevchenko, Aleksandr"},{"full_name":"Mondelli, Marco","id":"27EB676C-8706-11E9-9510-7717E6697425","first_name":"Marco","orcid":"0000-0002-3242-7020","last_name":"Mondelli"}],"day":"13","article_processing_charge":"No","type":"conference","department":[{"_id":"MaMo"},{"_id":"DaAl"}],"date_created":"2021-02-25T09:36:22Z","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","month":"07","_id":"9198","file_date_updated":"2021-03-02T15:38:14Z","intvolume":"       119","publication":"Proceedings of the 37th International Conference on Machine Learning","oa_version":"Published Version","file":[{"access_level":"open_access","content_type":"application/pdf","date_created":"2021-03-02T15:38:14Z","file_size":5336380,"checksum":"f042c8d4316bd87c6361aa76f1fbdbbe","relation":"main_file","file_name":"2020_PMLR_Shevchenko.pdf","creator":"dernst","date_updated":"2021-03-02T15:38:14Z","file_id":"9217","success":1}],"date_updated":"2026-10-29T23:31:01Z","oa":1,"related_material":{"record":[{"status":"public","id":"17465","relation":"dissertation_contains"}]},"year":"2020","volume":119,"citation":{"mla":"Shevchenko, Aleksandr, and Marco Mondelli. “Landscape Connectivity and Dropout Stability of SGD Solutions for Over-Parameterized Neural Networks.” <i>Proceedings of the 37th International Conference on Machine Learning</i>, vol. 119, ML Research Press, 2020, pp. 8773–84.","ama":"Shevchenko A, Mondelli M. Landscape connectivity and dropout stability of SGD solutions for over-parameterized neural networks. In: <i>Proceedings of the 37th International Conference on Machine Learning</i>. Vol 119. ML Research Press; 2020:8773-8784.","ista":"Shevchenko A, Mondelli M. 2020. Landscape connectivity and dropout stability of SGD solutions for over-parameterized neural networks. Proceedings of the 37th International Conference on Machine Learning. vol. 119, 8773–8784.","ieee":"A. Shevchenko and M. Mondelli, “Landscape connectivity and dropout stability of SGD solutions for over-parameterized neural networks,” in <i>Proceedings of the 37th International Conference on Machine Learning</i>, 2020, vol. 119, pp. 8773–8784.","short":"A. Shevchenko, M. Mondelli, in:, Proceedings of the 37th International Conference on Machine Learning, ML Research Press, 2020, pp. 8773–8784.","apa":"Shevchenko, A., &#38; Mondelli, M. (2020). Landscape connectivity and dropout stability of SGD solutions for over-parameterized neural networks. In <i>Proceedings of the 37th International Conference on Machine Learning</i> (Vol. 119, pp. 8773–8784). ML Research Press.","chicago":"Shevchenko, Aleksandr, and Marco Mondelli. “Landscape Connectivity and Dropout Stability of SGD Solutions for Over-Parameterized Neural Networks.” In <i>Proceedings of the 37th International Conference on Machine Learning</i>, 119:8773–84. ML Research Press, 2020."},"publication_status":"published","status":"public","project":[{"name":"Prix Lopez-Loretta 2019 - Marco Mondelli","_id":"059876FA-7A3F-11EA-A408-12923DDC885E"}],"publisher":"ML Research Press","quality_controlled":"1","title":"Landscape connectivity and dropout stability of SGD solutions for over-parameterized neural networks","abstract":[{"text":"The optimization of multilayer neural networks typically leads to a solution\r\nwith zero training error, yet the landscape can exhibit spurious local minima\r\nand the minima can be disconnected. In this paper, we shed light on this\r\nphenomenon: we show that the combination of stochastic gradient descent (SGD)\r\nand over-parameterization makes the landscape of multilayer neural networks\r\napproximately connected and thus more favorable to optimization. More\r\nspecifically, we prove that SGD solutions are connected via a piecewise linear\r\npath, and the increase in loss along this path vanishes as the number of\r\nneurons grows large. This result is a consequence of the fact that the\r\nparameters found by SGD are increasingly dropout stable as the network becomes\r\nwider. We show that, if we remove part of the neurons (and suitably rescale the\r\nremaining ones), the change in loss is independent of the total number of\r\nneurons, and it depends only on how many neurons are left. Our results exhibit\r\na mild dependence on the input dimension: they are dimension-free for two-layer\r\nnetworks and depend linearly on the dimension for multilayer networks. We\r\nvalidate our theoretical findings with numerical experiments for different\r\narchitectures and classification tasks.","lang":"eng"}],"acknowledgement":"M. Mondelli was partially supported by the 2019 LopezLoreta Prize. The authors thank Phan-Minh Nguyen for helpful discussions and the IST Distributed Algorithms and Systems Lab for providing computational resources."},{"fulldoi":"https://doi.org/10.1038/s41588-020-00712-y","language":[{"iso":"eng"}],"date_published":"2020-10-19T00:00:00Z","external_id":{"pmid":["33077914"],"isi":["000579693500004"]},"pmid":1,"author":[{"last_name":" Galan","first_name":"Silvia","full_name":" Galan, Silvia"},{"orcid":"0000-0001-6617-9742","last_name":"Machnik","first_name":"Nick N","id":"3591A0AA-F248-11E8-B48F-1D18A9856A87","full_name":"Machnik, Nick N"},{"last_name":"Kruse","full_name":"Kruse, Kai","first_name":"Kai"},{"first_name":"Noelia","full_name":"Díaz, Noelia","last_name":"Díaz"},{"last_name":"Marti-Renom","full_name":"Marti-Renom, Marc A","first_name":"Marc A"},{"full_name":"Vaquerizas, Juan M","first_name":"Juan M","last_name":"Vaquerizas"}],"main_file_link":[{"open_access":"1","url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC7610641/"}],"publication_identifier":{"issn":["1061-4036"],"eissn":["1546-1718"]},"scopus_import":"1","page":"1247-1255","article_processing_charge":"No","type":"journal_article","day":"19","month":"10","_id":"8707","department":[{"_id":"FyKo"}],"article_type":"original","date_created":"2020-10-25T23:01:20Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2026-10-29T23:31:10Z","isi":1,"oa":1,"related_material":{"record":[{"status":"public","id":"18642","relation":"dissertation_contains"}]},"intvolume":"        52","oa_version":"Submitted Version","publication":"Nature Genetics","OA_type":"green","doi":"10.1038/s41588-020-00712-y","year":"2020","volume":52,"citation":{"apa":"Galan, S., Machnik, N. N., Kruse, K., Díaz, N., Marti-Renom, M. A., &#38; Vaquerizas, J. M. (2020). CHESS enables quantitative comparison of chromatin contact data and automatic feature extraction. <i>Nature Genetics</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41588-020-00712-y\">https://doi.org/10.1038/s41588-020-00712-y</a>","chicago":"Galan, Silvia, Nick N Machnik, Kai Kruse, Noelia Díaz, Marc A Marti-Renom, and Juan M Vaquerizas. “CHESS Enables Quantitative Comparison of Chromatin Contact Data and Automatic Feature Extraction.” <i>Nature Genetics</i>. Springer Nature, 2020. <a href=\"https://doi.org/10.1038/s41588-020-00712-y\">https://doi.org/10.1038/s41588-020-00712-y</a>.","ieee":"S.  Galan, N. N. Machnik, K. Kruse, N. Díaz, M. A. Marti-Renom, and J. M. Vaquerizas, “CHESS enables quantitative comparison of chromatin contact data and automatic feature extraction,” <i>Nature Genetics</i>, vol. 52. Springer Nature, pp. 1247–1255, 2020.","short":"S.  Galan, N.N. Machnik, K. Kruse, N. Díaz, M.A. Marti-Renom, J.M. Vaquerizas, Nature Genetics 52 (2020) 1247–1255.","ista":"Galan S, Machnik NN, Kruse K, Díaz N, Marti-Renom MA, Vaquerizas JM. 2020. CHESS enables quantitative comparison of chromatin contact data and automatic feature extraction. Nature Genetics. 52, 1247–1255.","mla":"Galan, Silvia, et al. “CHESS Enables Quantitative Comparison of Chromatin Contact Data and Automatic Feature Extraction.” <i>Nature Genetics</i>, vol. 52, Springer Nature, 2020, pp. 1247–55, doi:<a href=\"https://doi.org/10.1038/s41588-020-00712-y\">10.1038/s41588-020-00712-y</a>.","ama":"Galan S, Machnik NN, Kruse K, Díaz N, Marti-Renom MA, Vaquerizas JM. CHESS enables quantitative comparison of chromatin contact data and automatic feature extraction. <i>Nature Genetics</i>. 2020;52:1247-1255. doi:<a href=\"https://doi.org/10.1038/s41588-020-00712-y\">10.1038/s41588-020-00712-y</a>"},"publication_status":"published","OA_place":"repository","abstract":[{"text":"Dynamic changes in the three-dimensional (3D) organization of chromatin are associated with central biological processes, such as transcription, replication and development. Therefore, the comprehensive identification and quantification of these changes is fundamental to understanding of evolutionary and regulatory mechanisms. Here, we present Comparison of Hi-C Experiments using Structural Similarity (CHESS), an algorithm for the comparison of chromatin contact maps and automatic differential feature extraction. We demonstrate the robustness of CHESS to experimental variability and showcase its biological applications on (1) interspecies comparisons of syntenic regions in human and mouse models; (2) intraspecies identification of conformational changes in Zelda-depleted Drosophila embryos; (3) patient-specific aberrant chromatin conformation in a diffuse large B-cell lymphoma sample; and (4) the systematic identification of chromatin contact differences in high-resolution Capture-C data. In summary, CHESS is a computationally efficient method for the comparison and classification of changes in chromatin contact data.","lang":"eng"}],"title":"CHESS enables quantitative comparison of chromatin contact data and automatic feature extraction","acknowledgement":"Work in the Vaquerizas laboratory is funded by the Max Planck Society, the Deutsche Forschungsgemeinschaft (DFG) Priority Programme SPP 2202 ‘Spatial Genome Architecture in Development and Disease’ (project no. 422857230 to J.M.V.), the DFG Clinical Research Unit CRU326 ‘Male Germ Cells: from Genes to Function’ (project no. 329621271 to J.M.V.), the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 643062—ZENCODE-ITN to J.M.V.) and the Medical Research Council in the UK. This research was partially funded by the European Union’s H2020 Framework Programme through the European Research Council (grant no. 609989 to M.A.M.-R.). We thank the support of the Spanish Ministerio de Ciencia, Innovación y Universidades through grant no. BFU2017-85926-P to M.A.M.-R. The Centre for Genomic Regulation thanks the support of the Ministerio de Ciencia, Innovación y Universidades to the European Molecular Biology Laboratory partnership, the ‘Centro de Excelencia Severo Ochoa 2013–2017’, agreement no. SEV-2012-0208, the CERCA Programme/Generalitat de Catalunya, Spanish Ministerio de Ciencia, Innovación y Universidades through the Instituto de Salud Carlos III, the Generalitat de Catalunya through the Departament de Salut and Departament d’Empresa i Coneixement and cofinancing by the Spanish Ministerio de Ciencia, Innovación y Universidades with funds from the European Regional Development Fund corresponding to the 2014–2020 Smart Growth Operating Program. S.G. thanks the support from the Company of Biologists (grant no. JCSTF181158) and the European Molecular Biology Organization Short-Term Fellowship programme.","status":"public","publisher":"Springer Nature","quality_controlled":"1"}]