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Schilling C, Bogomolov S, Henzinger TA, Podelski A, Ruess J. 2016. Adaptive moment closure for parameter inference of biochemical reaction networks. Biosystems. 149, 15–25.
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Martius GS, Hostettler R, Knoll A, Der R. 2016. Self-organized control of an tendon driven arm by differential extrinsic plasticity. Proceedings of the Artificial Life Conference 2016. ALIFE 2016: 15th International Conference on the Synthesis and Simulation of Living Systems vol. 28, 142–143.
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Prentice J, Marre O, Ioffe M, Loback A, Tkadik G, Berry M. 2016. Error-robust modes of the retinal population code. PLoS Computational Biology. 12(11), e1005855.
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Hillenbrand P, Gerland U, Tkadik G. 2016. Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information. PLoS One. 11(9), e0163628.
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Hillenbrand P, Gerland U, Tkadik G. 2016. Computation of positional information in an Ising model, Public Library of Science,10.1371/journal.pone.0163628.s002 .
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Hillenbrand P, Gerland U, Tkadik G. 2016. Error bound on an estimator of position, Public Library of Science,10.1371/journal.pone.0163628.s001 .
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Hillenbrand P, Gerland U, Tkadik G. 2016. Computation of positional information in a discrete morphogen field, Public Library of Science,10.1371/journal.pone.0163628.s003 .
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Rieckh G. 2016. Studying the complexities of transcriptional regulation. Institute of Science and Technology Austria.
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Friedlander T, Prizak R, Guet CC, Barton NH, Tkadik G. 2016. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 7, 12307.
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Parise F, Lygeros J, Ruess J. 2015. Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study. Frontiers in Environmental Science. 3, 42.
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Ruess J. 2015. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. 143(24), 244103.
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Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. 2015. Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. 112(26), 8148–8153.
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Der R, Martius GS. 2015. Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. 112(45), 24–32.
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Bogomolov S, Henzinger TA, Podelski A, Ruess J, Schilling C. 2015. Adaptive moment closure for parameter inference of biochemical reaction networks. 9308, 77–89.
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Marre O, Botella Soler V, Simmons K, Mora T, Tkadik G, Berry M. 2015. High accuracy decoding of dynamical motion from a large retinal population. PLoS Computational Biology. 11(7), e1004304.
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Tkadik G, Mora T, Marre O, Amodei D, Palmer S, Berry Ii M, Bialek W. 2015. Thermodynamics and signatures of criticality in a network of neurons. PNAS. 112(37), 11508–11513.
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Tkadik G, Dubuis J, Petkova M, Gregor T. 2015. Positional information, positional error, and readout precision in morphogenesis: A mathematical framework. Genetics. 199(1), 39–59.
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Sokolowski TR, Tkadik G. 2015. Optimizing information flow in small genetic networks. IV. Spatial coupling. Physical Review E Statistical Nonlinear and Soft Matter Physics. 91(6), 062710.
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Friedlander T, Mayo AE, Tlusty T, Alon U. 2015. Supporting information text, Public Library of Science,10.1371/journal.pcbi.1004055.s001 .
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Friedlander T, Mayo A, Tlusty T, Alon U. 2015. Evolution of bow-tie architectures in biology. PLoS Computational Biology. 11(3).
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Friedlander T, Mayo AE, Tlusty T, Alon U. 2015. Evolutionary simulation code, Public Library of Science,10.1371/journal.pcbi.1004055.s002 .
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Tugrul M, Paixao T, Barton NH, Tkadik G. 2015. Other fitness models for comparison &; for interacting TFBSs, Public Library of Science,10.1371/journal.pgen.1005639.s001 .
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Tugrul M, Paixao T, Barton NH, Tkadik G. 2015. Dynamics of transcription factor binding site evolution. PLoS Genetics. 11(11).
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Cepeda Humerez SA, Rieckh G, Tkadik G. 2015. Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation. Physical Review Letters. 115(24), 248101.
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Martius GS, Olbrich E. 2015. Quantifying emergent behavior of autonomous robots. Entropy. 17(10), 7266–7297.
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Savin C, Denève S. 2014. Spatio-temporal representations of uncertainty in spiking neural networks. NIPS: Neural Information Processing Systems vol. 3, 2024–2032.
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Hermundstad A, Briguglio J, Conte M, Victor J, Balasubramanian V, Tkadik G. 2014. Variance predicts salience in central sensory processing. eLife. (November), e03722.
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Kollár R, Bodova K, Nosek J, Tomáska d. 2014. Mathematical model of alternative mechanism of telomere length maintenance. Physical Review E Statistical Nonlinear and Soft Matter Physics. 89(3), 032701.
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Ezard T, Prizak R, Hoyle R. 2014. The fitness costs of adaptation via phenotypic plasticity and maternal effects. Functional Ecology. 28(3), 693–701.
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Humplik J, Hill A, Nowak M. 2014. Evolutionary dynamics of infectious diseases in finite populations. Journal of Theoretical Biology. 360, 149–162.
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Savin C, Triesch J. 2014. Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. 8(MAY), 57.
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Botella Soler V, Glendinning P. 2014. Hierarchy and polysynchrony in an adaptive network . Physical Review E Statistical Nonlinear and Soft Matter Physics. 89(6), 062809.
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Rieckh G, Tkadik G. 2014. Noise and information transmission in promoters with multiple internal states. Biophysical Journal. 106(5), 1194–1204.
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Tkadik G, Ghosh A, Schneidman E, Segev R. 2014. Adaptation to changes in higher-order stimulus statistics in the salamander retina. PLoS One. 9(1), e85841.
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Prizak R, Ezard T, Hoyle R. 2014. Fitness consequences of maternal and grandmaternal effects. Ecology and Evolution. 4(15), 3139–3145.
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Simmons K, Prentice J, Tkadik G, Homann J, Yee H, Palmer S, Nelson P, Balasubramanian V. 2014. Data from: Transformation of stimulus correlations by the retina, Dryad,10.5061/dryad.246qg .
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Tkadik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry M. 2014. Searching for collective behavior in a large network of sensory neurons. PLoS Computational Biology. 10(1), e1003408.
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Valderrama M, Botella Soler V, Le Van Quyen M. 2013.Neuronal oscillations scale up and scale down the brain dynamics . In: Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain. Reviews of Nonlinear Dynamics and Complexity, .
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Rajan K, Marre O, Tkadik G. 2013. Learning quadratic receptive fields from neural responses to natural stimuli. Neural Computation. 25(7), 1661–1692.
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Tkadik G, Marre O, Mora T, Amodei D, Berry M, Bialek W. 2013. The simplest maximum entropy model for collective behavior in a neural network. Journal of Statistical Mechanics Theory and Experiment. 2013(3), 011.
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Berry M, Tkadik G, Dubuis J, Marre O, Da Silveira R. 2013. A simple method for estimating the entropy of neural activity. Journal of Statistical Mechanics Theory and Experiment. 2013(3), 015.
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Granot Atedgi E, Tkadik G, Segev R, Schneidman E. 2013. Stimulus-dependent maximum entropy models of neural population codes. PLoS Computational Biology. 9(3), e1002922.
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Botella Soler V, Oteo J, Ros J, Glendinning P. 2013. Lyapunov exponent and topological entropy plateaus in piecewise linear maps. Journal of Physics A: Mathematical and Theoretical. 46(12), 125101.
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Tkadik G, Granot Atedgi E, Segev R, Schneidman E. 2013. Retinal metric: a stimulus distance measure derived from population neural responses. Physical Review Letters. 110(5), 058104.
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Dubuis J, Tkadik G, Wieschaus E, Gregor T, Bialek W. 2013. Positional information, in bits. PNAS. 110(41), 16301–16308.
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