Humplik J, Tkadik G. 2017. Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. 13(9), e1005763.
LibreCat: https://research-explorer.ista.ac.at/record/720
DOI: 10.1371/journal.pcbi.1005763

Harpaz R, Tkadik G, Schneidman E. 2017. Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. 114(38), 10149–10154.
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. 2017. Data from: Error-robust modes of the retinal population code, Dryad,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. 2017. Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. 13(6), e1005582.
LibreCat: https://research-explorer.ista.ac.at/record/680
DOI: 10.1371/journal.pcbi.1005582

Chalk MJ, Masset P, Gutkin B, Denève S. 2017. Supplementary appendix, Public Library of Science,10.1371/journal.pcbi.1005582.s001 .
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Mitosch K, Rieckh G, Bollenbach MT. 2017. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. 4(4), 393–403.
LibreCat: https://research-explorer.ista.ac.at/record/666
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Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. 2017. Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. 44(2), 285–306.
LibreCat: https://research-explorer.ista.ac.at/record/2016
DOI: 10.1111/sjos.12251
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arXiv: 1410.1242

Deny S, Ferrari U, Mace E, Yger P, Caplette R, Picaud S, Tkadik G, Marre O. 2017. Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. 8(1), 1964.
LibreCat: https://research-explorer.ista.ac.at/record/1104
DOI: 10.1038/s41467-017-02159-y
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Levina (Martius) A, Priesemann V. 2017. Subsampling scaling. Nature Communications. 8, 15140.
LibreCat: https://research-explorer.ista.ac.at/record/993
DOI: 10.1038/ncomms15140
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Friedlander T, Prizak R, Barton NH, Tkadik G. 2017. Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. 8(1), 216.
LibreCat: https://research-explorer.ista.ac.at/record/955
DOI: 10.1038/s41467-017-00238-8
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De Martino D. 2017. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics.  Physical Review E Statistical Nonlinear and Soft Matter Physics . 95(6), 062419.
LibreCat: https://research-explorer.ista.ac.at/record/959
DOI: 10.1103/PhysRevE.95.062419
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De Martino D, Capuani F, De Martino A. 2017. Quantifying the entropic cost of cellular growth control.  Physical Review E Statistical Nonlinear and Soft Matter Physics . 96(1), 010401.
LibreCat: https://research-explorer.ista.ac.at/record/947
DOI: 10.1103/PhysRevE.96.010401
WoS: 000405194200002

Zagórski MP, Tabata Y, Brandenberg N, Lutolf M, Tkadik G, Bollenbach T, Briscoe J, Kicheva A. 2017. Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. 356(6345), 1379–1383.
LibreCat: https://research-explorer.ista.ac.at/record/943
DOI: 10.1126/science.aam5887
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PMID: 28663499

Colabrese S, De Martino D, Leuzzi L, Marinari E. 2017. Phase transitions in integer linear problems.  Journal of Statistical Mechanics: Theory and Experiment. 2017(9), 093404.
LibreCat: https://research-explorer.ista.ac.at/record/823
DOI: 10.1088/1742-5468/aa85c3
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Savin C, Tkadik G. 2017. Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. 46, 120–126.
LibreCat: https://research-explorer.ista.ac.at/record/730
DOI: 10.1016/j.conb.2017.08.001
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De Martino D. 2017. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes. Physical Review E. 96(6), 060401.
LibreCat: https://research-explorer.ista.ac.at/record/548
DOI: 10.1103/PhysRevE.96.060401

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

Marre O, Tkadik G, Amodei D, Schneidman E, Bialek W, Berry M. 2017. Multi-electrode array recording from salamander retinal ganglion cells, Institute of Science and Technology Austria,10.15479/AT:ISTA:61 .
LibreCat: https://research-explorer.ista.ac.at/record/5562
DOI: 10.15479/AT:ISTA:61

Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkadik G, Guet CC. 2017. Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity, Institute of Science and Technology Austria,10.15479/AT:ISTA:53 .
LibreCat: https://research-explorer.ista.ac.at/record/5560
DOI: 10.15479/AT:ISTA:53

Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkadik G, Guet CC. 2017. Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science. 356(6335), 311–315.
LibreCat: https://research-explorer.ista.ac.at/record/665
DOI: 10.1126/science.aaf4762