Misun P, Birchler A, Lang M, Hierlemann A, Frey O. Fabrication and operation of microfluidic hanging drop networks. Methods in Molecular Biology. 2018;1771:183-202. doi:10.1007/978-1-4939-7792-5_15
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DOI: 10.1007/978-1-4939-7792-5_15

Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkadik G, Swain P. Distributed and dynamic intracellular organization of extracellular information. PNAS. 2018;115(23):6088-6093. doi:10.1073/pnas.1716659115
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DOI: 10.1073/pnas.1716659115
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PMID: 29784812

Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. 2018;209(3):861-883. doi:10.1534/genetics.118.300748
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DOI: 10.1534/genetics.118.300748
WoS: 000437171700017

Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Supplemental material for Bodova et al., 2018. 2018. doi:10.25386/genetics.6148304.v1
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DOI: 10.25386/genetics.6148304.v1

Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkadik G. Probabilistic models of individual and collective animal behavior. PLoS One. 2018;13(3). doi:10.1371/journal.pone.0193049
LibreCat: https://research-explorer.ista.ac.at/record/406
DOI: 10.1371/journal.pone.0193049
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Pleska M, Lang M, Refardt D, Levin B, Guet CC. Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. Nature Ecology and Evolution. 2018;2(2):359-366. doi:10.1038/s41559-017-0424-z
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DOI: 10.1038/s41559-017-0424-z
WoS: 000426516400027

Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkadik G. Implementation of the inference method in Matlab. 2018. doi:10.1371/journal.pone.0193049.s001
LibreCat: https://research-explorer.ista.ac.at/record/9831
DOI: 10.1371/journal.pone.0193049.s001

Ferrari U, Deny S, Chalk MJ, Tkadik G, Marre O, Mora T. Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons. Physical Review E. 2018;98(4). doi:10.1103/PhysRevE.98.042410
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DOI: 10.1103/PhysRevE.98.042410
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Chalk MJ, Marre O, Tkadik G. Toward a unified theory of efficient, predictive, and sparse coding. PNAS. 2018;115(1):186-191. doi:10.1073/pnas.1711114115
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DOI: 10.1073/pnas.1711114115
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Bodova K, Haskovec J, Markowich P. Well posedness and maximum entropy approximation for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena. 2018;376-377:108-120. doi:10.1016/j.physd.2017.10.015
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DOI: 10.1016/j.physd.2017.10.015
WoS: 000437962900012
arXiv: 1704.08757

Palmer A, Chait RP, Kishony R. Nonoptimal gene expression creates latent potential for antibiotic resistance. Molecular Biology and Evolution. 2018;35(11):2669-2684. doi:10.1093/molbev/msy163
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DOI: 10.1093/molbev/msy163
WoS: 000452567200006
PMID: 30169679

Botella Soler V, Deny S, Martius GS, Marre O, Tkadik G. Nonlinear decoding of a complex movie from the mammalian retina. PLoS Computational Biology. 2018;14(5). doi:10.1371/journal.pcbi.1006057
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DOI: 10.1371/journal.pcbi.1006057
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Deny S, Marre O, Botella-Soler V, Martius GS, Tkadik G. Nonlinear decoding of a complex movie from the mammalian retina. 2018. doi:10.15479/AT:ISTA:98
LibreCat: https://research-explorer.ista.ac.at/record/5584
DOI: 10.15479/AT:ISTA:98

De Martino D, Mc AA, Bergmiller T, Guet CC, Tkadik G. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-05417-9
LibreCat: https://research-explorer.ista.ac.at/record/161
DOI: 10.1038/s41467-018-05417-9
WoS: 000440149300021

De Martino D, Tkadik G. Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.”10.15479/AT:ISTA:62__2018. doi:10.15479/AT:ISTA:62
LibreCat: https://research-explorer.ista.ac.at/record/5587
DOI: 10.15479/AT:ISTA:62

Igler C, Lagator M, Tkadik G, Bollback JP, Guet CC. Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. 2018;2(10):1633-1643. doi:10.1038/s41559-018-0651-y
LibreCat: https://research-explorer.ista.ac.at/record/67
DOI: 10.1038/s41559-018-0651-y
WoS: 000447947600021

Igler C, Lagator M, Tkadik G, Bollback JP, Guet CC. Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring. 2018. doi:10.15479/AT:ISTA:108
LibreCat: https://research-explorer.ista.ac.at/record/5585
DOI: 10.15479/AT:ISTA:108

Chait RP, Ruess J, Bergmiller T, Tkadik G, Guet CC. Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-01683-1
LibreCat: https://research-explorer.ista.ac.at/record/613
DOI: 10.1038/s41467-017-01683-1

Der R, Martius GS. Dynamical self consistency leads to behavioral development and emergent social interactions in robots. In: IEEE; 2017. doi:10.1109/DEVLRN.2016.7846789
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Der R, Martius GS. Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. 2017;11(MAR). doi:10.3389/fnbot.2017.00008
LibreCat: https://research-explorer.ista.ac.at/record/658
DOI: 10.3389/fnbot.2017.00008

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
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DOI: 10.1371/journal.pcbi.1005582

Chalk MJ, Masset P, Gutkin B, Denève S. Supplementary appendix. 2017. doi:10.1371/journal.pcbi.1005582.s001
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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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Levina (Martius) A, Priesemann V. Subsampling scaling. Nature Communications. 2017;8. 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
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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
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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
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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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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
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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
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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
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Lang M, Sontag E. Zeros of nonlinear systems with input invariances. Automatica. 2017;81C:46-55. doi:10.1016/j.automatica.2017.03.030
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Marre O, Tkadik G, Amodei D, Schneidman E, Bialek W, Berry M. Multi-electrode array recording from salamander retinal ganglion cells. 2017. doi:10.15479/AT:ISTA:61
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Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity. 2017. doi:10.15479/AT:ISTA:53
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DOI: 10.15479/AT:ISTA:53

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
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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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Chalk MJ, Marre O, Tkadik G. Relevant sparse codes with variational information bottleneck. In: Vol 29. Neural Information Processing Systems; 2016:1965-1973.
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Savin C, Tkadik G. Estimating nonlinear neural response functions using GP priors and Kronecker methods. In: Vol 29. Neural Information Processing Systems; 2016:3610-3618.
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Lang M, Stelling J. Modular parameter identification of biomolecular networks. SIAM Journal on Scientific Computing. 2016;38(6):8-08. doi:10.1137/15M103306X
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Tkadik G. Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on &;quot;Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function&;quot; by O. C. Martin et al. Physics of Life Reviews. 2016;17:166-167. doi:10.1016/j.plrev.2016.06.005
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De Martino D, Masoero D. Asymptotic analysis of noisy fitness maximization, applied to metabolism &;amp; growth. 10.1088/1742-5468/aa4e8f__Journal of Statistical Mechanics: Theory and Experiment. 2016;2016(12). doi:10.1088/1742-5468/aa4e8f
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Hu F, Rishishwar L, Sivadas A, et al. Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination. Journal of Clinical Microbiology. 2016;54(12):3010-3017. doi:10.1128/JCM.01511-16
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Martius GS, Hostettler R, Knoll A, Der R. Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm. In: Vol 2016-November. IEEE; 2016. doi:10.1109/IROS.2016.7759138
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Miki G, Stoll A, Bevirt J, Grah R, Moore M. Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency. In: AIAA; 2016:1-19. doi:10.2514/6.2016-3764
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Sokolowski TR, Walczak A, Bialek W, Tkadik G. Extending the dynamic range of transcription factor action by translational regulation. Physical Review E Statistical Nonlinear and Soft Matter Physics. 2016;93(2). doi:10.1103/PhysRevE.93.022404
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Recouvreux P, Sokolowski TR, Grammoustianou A, Tenwolde P, Dogterom M. Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells. PNAS. 2016;113(7):1811-1816. doi:10.1073/pnas.1419248113
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Tkadik G, Bialek W. Information processing in living systems. Annual Review of Condensed Matter Physics. 2016;7:89-117. doi:10.1146/annurev-conmatphys-031214-014803
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De Martino D. The dual of the space of interactions in neural network models. International Journal of Modern Physics C. 2016;27(6). doi:10.1142/S0129183116500674
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arXiv: 1505.02963

Chalk MJ, Gutkin B, Denève S. Neural oscillations as a signature of efficient coding in the presence of synaptic delays. eLife. 2016;5(2016JULY). doi:10.7554/eLife.13824
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Stone L, Baym M, Lieberman T, Chait RP, Clardy J, Kishony R. Compounds that select against the tetracycline-resistance efflux pump. Nature Chemical Biology. 2016;12(11):902-904. doi:10.1038/nchembio.2176
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Lang M, Sontag E. Scale-invariant systems realize nonlinear differential operators. In: Vol 2016-July. IEEE; 2016. doi:10.1109/ACC.2016.7526722
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Chait RP, Palmer A, Yelin I, Kishony R. Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments. Nature Communications. 2016;7. doi:10.1038/ncomms10333
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Baym M, Lieberman T, Kelsic E, et al. Spatiotemporal microbial evolution on antibiotic landscapes. Science. 2016;353(6304):1147-1151. doi:10.1126/science.aag0822
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De Martino D, Capuani F, De Martino A. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. 2016;13(3). doi:10.1088/1478-3975/13/3/036005
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Bodova K, Tkadik G, Barton NH. A general approximation for the dynamics of quantitative traits. Genetics. 2016;202(4):1523-1548. doi:10.1534/genetics.115.184127
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DOI: 10.1534/genetics.115.184127
arXiv: 1510.08344

De Martino D. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. 2016;13(1). doi:10.1088/1478-3975/13/1/016003
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Schilling C, Bogomolov S, Henzinger TA, Podelski A, Ruess J. Adaptive moment closure for parameter inference of biochemical reaction networks. Biosystems. 2016;149:15-25. doi:10.1016/j.biosystems.2016.07.005
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Martius GS, Hostettler R, Knoll A, Der R. Self-organized control of an tendon driven arm by differential extrinsic plasticity. In: Proceedings of the Artificial Life Conference 2016. Vol 28. MIT Press; 2016:142-143. doi:10.7551/978-0-262-33936-0-ch029
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Prentice J, Marre O, Ioffe M, Loback A, Tkadik G, Berry M. Error-robust modes of the retinal population code. PLoS Computational Biology. 2016;12(11). doi:10.1371/journal.pcbi.1005148
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Monk T, Savin C, Lücke J. Neurons equipped with intrinsic plasticity learn stimulus intensity statistics. In: Vol 29. Neural Information Processing Systems; 2016:4285-4293.
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Hillenbrand P, Gerland U, Tkadik G. Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information. PLoS One. 2016;11(9). doi:10.1371/journal.pone.0163628
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Hillenbrand P, Gerland U, Tkadik G. Computation of positional information in an Ising model. 2016. doi:10.1371/journal.pone.0163628.s002
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DOI: 10.1371/journal.pone.0163628.s002

Hillenbrand P, Gerland U, Tkadik G. Error bound on an estimator of position. 2016. doi:10.1371/journal.pone.0163628.s001
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Hillenbrand P, Gerland U, Tkadik G. Computation of positional information in a discrete morphogen field. 2016. doi:10.1371/journal.pone.0163628.s003
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Rieckh G. Studying the complexities of transcriptional regulation. 2016.
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Friedlander T, Prizak R, Guet CC, Barton NH, Tkadik G. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 2016;7. doi:10.1038/ncomms12307
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Parise F, Lygeros J, Ruess J. Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study. Frontiers in Environmental Science. 2015;3. doi:10.3389/fenvs.2015.00042
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Ruess J. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. 2015;143(24). doi:10.1063/1.4937937
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Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. 2015;112(26):8148-8153. doi:10.1073/pnas.1423947112
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PMID: 26085136

Gilson M, Savin C, Zenke F. Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. 2015;9(11). doi:10.3389/fncom.2015.00145
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Der R, Martius GS. Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. 2015;112(45):24-32. doi:10.1073/pnas.1508400112
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PMID: 26504200

Bogomolov S, Henzinger TA, Podelski A, Ruess J, Schilling C. Adaptive moment closure for parameter inference of biochemical reaction networks. 2015;9308:77-89. doi:10.1007/978-3-319-23401-4_8
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Marre O, Botella Soler V, Simmons K, Mora T, Tkadik G, Berry M. High accuracy decoding of dynamical motion from a large retinal population. PLoS Computational Biology. 2015;11(7). doi:10.1371/journal.pcbi.1004304
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DOI: 10.1371/journal.pcbi.1004304

Tkadik G, Mora T, Marre O, et al. Thermodynamics and signatures of criticality in a network of neurons. PNAS. 2015;112(37):11508-11513. doi:10.1073/pnas.1514188112
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PMID: 26330611

Ruess J, Lygeros J. Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks. ACM Transactions on Modeling and Computer Simulation. 2015;25(2). doi:10.1145/2688906
LibreCat: https://research-explorer.ista.ac.at/record/1861
DOI: 10.1145/2688906

Tkadik G, Dubuis J, Petkova M, Gregor T. Positional information, positional error, and readout precision in morphogenesis: A mathematical framework. Genetics. 2015;199(1):39-59. doi:10.1534/genetics.114.171850
LibreCat: https://research-explorer.ista.ac.at/record/1885
DOI: 10.1534/genetics.114.171850

Sokolowski TR, Tkadik G. Optimizing information flow in small genetic networks. IV. Spatial coupling. Physical Review E Statistical Nonlinear and Soft Matter Physics. 2015;91(6). doi:10.1103/PhysRevE.91.062710
LibreCat: https://research-explorer.ista.ac.at/record/1940
DOI: 10.1103/PhysRevE.91.062710

Friedlander T, Mayo AE, Tlusty T, Alon U. Supporting information text. 2015. doi:10.1371/journal.pcbi.1004055.s001
LibreCat: https://research-explorer.ista.ac.at/record/9718
DOI: 10.1371/journal.pcbi.1004055.s001

Friedlander T, Mayo A, Tlusty T, Alon U. Evolution of bow-tie architectures in biology. PLoS Computational Biology. 2015;11(3). doi:10.1371/journal.pcbi.1004055
LibreCat: https://research-explorer.ista.ac.at/record/1827
DOI: 10.1371/journal.pcbi.1004055

Friedlander T, Mayo AE, Tlusty T, Alon U. Evolutionary simulation code. 2015. doi:10.1371/journal.pcbi.1004055.s002
LibreCat: https://research-explorer.ista.ac.at/record/9773
DOI: 10.1371/journal.pcbi.1004055.s002

Tugrul M, Paixao T, Barton NH, Tkadik G. Other fitness models for comparison &; for interacting TFBSs. 2015. doi:10.1371/journal.pgen.1005639.s001
LibreCat: https://research-explorer.ista.ac.at/record/9712
DOI: 10.1371/journal.pgen.1005639.s001

Tugrul M, Paixao T, Barton NH, Tkadik G. Dynamics of transcription factor binding site evolution. PLoS Genetics. 2015;11(11). doi:10.1371/journal.pgen.1005639
LibreCat: https://research-explorer.ista.ac.at/record/1666
DOI: 10.1371/journal.pgen.1005639

Cepeda Humerez SA, Rieckh G, Tkadik G. Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation. Physical Review Letters. 2015;115(24). doi:10.1103/PhysRevLett.115.248101
LibreCat: https://research-explorer.ista.ac.at/record/1576
DOI: 10.1103/PhysRevLett.115.248101

Martius GS, Olbrich E. Quantifying emergent behavior of autonomous robots. Entropy. 2015;17(10):7266-7297. doi:10.3390/e17107266
LibreCat: https://research-explorer.ista.ac.at/record/1655
DOI: 10.3390/e17107266

Savin C, Denève S. Spatio-temporal representations of uncertainty in spiking neural networks. In: Vol 3. Neural Information Processing Systems; 2014:2024-2032.
LibreCat: https://research-explorer.ista.ac.at/record/1708

Hermundstad A, Briguglio J, Conte M, Victor J, Balasubramanian V, Tkadik G. Variance predicts salience in central sensory processing. eLife. 2014;(November). doi:10.7554/eLife.03722
LibreCat: https://research-explorer.ista.ac.at/record/1886
DOI: 10.7554/eLife.03722

Kollár R, Bodova K, Nosek J, Tomáska d. Mathematical model of alternative mechanism of telomere length maintenance. Physical Review E Statistical Nonlinear and Soft Matter Physics. 2014;89(3). doi:10.1103/PhysRevE.89.032701
LibreCat: https://research-explorer.ista.ac.at/record/1896
DOI: 10.1103/PhysRevE.89.032701

Ezard T, Prizak R, Hoyle R. The fitness costs of adaptation via phenotypic plasticity and maternal effects. Functional Ecology. 2014;28(3):693-701. doi:10.1111/1365-2435.12207
LibreCat: https://research-explorer.ista.ac.at/record/1909
DOI: 10.1111/1365-2435.12207

Humplik J, Hill A, Nowak M. Evolutionary dynamics of infectious diseases in finite populations. Journal of Theoretical Biology. 2014;360:149-162. doi:10.1016/j.jtbi.2014.06.039
LibreCat: https://research-explorer.ista.ac.at/record/1928
DOI: 10.1016/j.jtbi.2014.06.039

Savin C, Triesch J. Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. 2014;8(MAY). doi:10.3389/fncom.2014.00057
LibreCat: https://research-explorer.ista.ac.at/record/1931
DOI: 10.3389/fncom.2014.00057

Bodova K, Paydarfar D, Forger D. Characterizing spiking in noisy type II neurons. 10.1016/j.jtbi.2014.09.041__Journal of Theoretical Biology. 2014;365:40-54. doi:10.1016/j.jtbi.2014.09.041
LibreCat: https://research-explorer.ista.ac.at/record/2028
DOI: 10.1016/j.jtbi.2014.09.041

Botella Soler V, Glendinning P. Hierarchy and polysynchrony in an adaptive network . Physical Review E Statistical Nonlinear and Soft Matter Physics. 2014;89(6). doi:10.1103/PhysRevE.89.062809
LibreCat: https://research-explorer.ista.ac.at/record/2183
DOI: 10.1103/PhysRevE.89.062809

Rieckh G, Tkadik G. Noise and information transmission in promoters with multiple internal states. Biophysical Journal. 2014;106(5):1194-1204. doi:10.1016/j.bpj.2014.01.014
LibreCat: https://research-explorer.ista.ac.at/record/2231
DOI: 10.1016/j.bpj.2014.01.014
PMID: 24606943

Tkadik G, Ghosh A, Schneidman E, Segev R. Adaptation to changes in higher-order stimulus statistics in the salamander retina. PLoS One. 2014;9(1). doi:10.1371/journal.pone.0085841
LibreCat: https://research-explorer.ista.ac.at/record/3263
DOI: 10.1371/journal.pone.0085841

Prizak R, Ezard T, Hoyle R. Fitness consequences of maternal and grandmaternal effects. Ecology and Evolution. 2014;4(15):3139-3145. doi:10.1002/ece3.1150
LibreCat: https://research-explorer.ista.ac.at/record/537
DOI: 10.1002/ece3.1150