Humplik J, Tkadik G. Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. 2017;13(9). doi:10.1371/journal.pcbi.1005763
LibreCat: https://research-explorer.ista.ac.at/record/720
DOI: 10.1371/journal.pcbi.1005763

Harpaz R, Tkadik G, Schneidman E. Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. 2017;114(38):10149-10154. doi:10.1073/pnas.1703817114
LibreCat: https://research-explorer.ista.ac.at/record/725
DOI: 10.1073/pnas.1703817114
PMID: 28874581

Prentice J, Marre O, Ioffe M, Loback A, Tkadik G, Berry M. Data from: Error-robust modes of the retinal population code. 2017. doi:10.5061/dryad.1f1rc
LibreCat: https://research-explorer.ista.ac.at/record/9709
DOI: 10.5061/dryad.1f1rc

Chalk MJ, Masset P, Gutkin B, Denève S. Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. 2017;13(6). doi:10.1371/journal.pcbi.1005582
LibreCat: https://research-explorer.ista.ac.at/record/680
DOI: 10.1371/journal.pcbi.1005582

Chalk MJ, Masset P, Gutkin B, Denève S. Supplementary appendix. 2017. doi:10.1371/journal.pcbi.1005582.s001
LibreCat: https://research-explorer.ista.ac.at/record/9855
DOI: 10.1371/journal.pcbi.1005582.s001

Mitosch K, Rieckh G, Bollenbach MT. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. 2017;4(4):393-403. doi:10.1016/j.cels.2017.03.001
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Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. 2017;44(2):285-306. doi:10.1111/sjos.12251
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DOI: 10.1111/sjos.12251
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arXiv: 1410.1242

Deny S, Ferrari U, Mace E, et al. Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-02159-y
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DOI: 10.1038/s41467-017-02159-y
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Levina (Martius) A, Priesemann V. Subsampling scaling. Nature Communications. 2017;8. doi:10.1038/ncomms15140
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DOI: 10.1038/ncomms15140
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Friedlander T, Prizak R, Barton NH, Tkadik G. Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-00238-8
LibreCat: https://research-explorer.ista.ac.at/record/955
DOI: 10.1038/s41467-017-00238-8
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De Martino D. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. 10.1103/PhysRevE.95.062419__Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;95(6):062419. doi:10.1103/PhysRevE.95.062419
LibreCat: https://research-explorer.ista.ac.at/record/959
DOI: 10.1103/PhysRevE.95.062419
WoS: 000404546400004

De Martino D, Capuani F, De Martino A. Quantifying the entropic cost of cellular growth control. 10.1103/PhysRevE.96.010401__Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;96(1). doi:10.1103/PhysRevE.96.010401
LibreCat: https://research-explorer.ista.ac.at/record/947
DOI: 10.1103/PhysRevE.96.010401
WoS: 000405194200002

Zagórski MP, Tabata Y, Brandenberg N, et al. Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. 2017;356(6345):1379-1383. doi:10.1126/science.aam5887
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DOI: 10.1126/science.aam5887
WoS: 000404351500036
PMID: 28663499

Colabrese S, De Martino D, Leuzzi L, Marinari E. Phase transitions in integer linear problems. 10.1088/1742-5468/aa85c3__Journal of Statistical Mechanics: Theory and Experiment. 2017;2017(9). doi:10.1088/1742-5468/aa85c3
LibreCat: https://research-explorer.ista.ac.at/record/823
DOI: 10.1088/1742-5468/aa85c3
WoS: 000411842900001

Savin C, Tkadik G. Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. 2017;46:120-126. doi:10.1016/j.conb.2017.08.001
LibreCat: https://research-explorer.ista.ac.at/record/730
DOI: 10.1016/j.conb.2017.08.001
WoS: 000416196400016

De Martino D. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. 2017;96(6). doi:10.1103/PhysRevE.96.060401
LibreCat: https://research-explorer.ista.ac.at/record/548
DOI: 10.1103/PhysRevE.96.060401

Lang M, Sontag E. Zeros of nonlinear systems with input invariances. Automatica. 2017;81C:46-55. doi:10.1016/j.automatica.2017.03.030
LibreCat: https://research-explorer.ista.ac.at/record/1007
DOI: 10.1016/j.automatica.2017.03.030
WoS: 000403513900006

Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science. 2017;356(6335):311-315. doi:10.1126/science.aaf4762
LibreCat: https://research-explorer.ista.ac.at/record/665
DOI: 10.1126/science.aaf4762

Barone V, Lang M, Krens G, et al. An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate. Developmental Cell. 2017;43(2):198-211. doi:10.1016/j.devcel.2017.09.014
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DOI: 10.1016/j.devcel.2017.09.014
WoS: 000413443700011

Chalk MJ, Marre O, Tkadik G. Relevant sparse codes with variational information bottleneck. In: Vol 29. Neural Information Processing Systems; 2016:1965-1973.
LibreCat: https://research-explorer.ista.ac.at/record/1082