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Grah R, Friedlander T. Maximizing crosstalk. 2020. doi:10.1371/journal.pcbi.1007642.s002

Kavcic B. Perturbations of protein synthesis: from antibiotics to genetics and physiology. 2020. doi:10.15479/AT:ISTA:8657

Kavcic B, Tkadik G, Bollenbach MT. Mechanisms of drug interactions between translation-inhibiting antibiotics. Nature Communications. 2020;11. doi:10.1038/s41467-020-17734-z

Kavcic B, Tkadik G, Bollenbach MT. A minimal biophysical model of combined antibiotic action. bioRxiv. 2020. doi:10.1101/2020.04.18.047886

Tomanek I, Grah R, Lagator M, et al. Gene amplification as a form of population-level gene expression regulation. Nature Ecology &; Evolution. 2020;4(4):612-625. doi:10.1038/s41559-020-1132-7

Bialek W, Gregor T, Tkadik G. Action at a distance in transcriptional regulation. arXiv:191208579.

Petkova MD, Tkadik G, Bialek W, Wieschaus EF, Gregor T. Optimal decoding of cellular identities in a genetic network. Cell. 2019;176(4):844-855.e15. doi:10.1016/j.cell.2019.01.007

De Martino D. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 2019;52(4). doi:10.1088/1751-8121/aaf2dd

Mitosch K, Rieckh G, Bollenbach MT. Temporal order and precision of complex stress responses in individual bacteria. Molecular systems biology. 2019;15(2). doi:10.15252/msb.20188470

Ruess J, Pleska M, Guet CC, Tkadik G. Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. 2019;15(7). doi:10.1371/journal.pcbi.1007168

Ruess J, Pleska M, Guet CC, Tkadik G. Supporting text and results. 2019. doi:10.1371/journal.pcbi.1007168.s001

Sokolowski TR, Paijmans J, Bossen L, et al. eGFRD in all dimensions. The Journal of Chemical Physics. 2019;150(5). doi:10.1063/1.5064867

Cepeda Humerez SA, Ruess J, Tkadik G. Estimating information in time-varying signals. PLoS computational biology. 2019;15(9):e1007290. doi:10.1371/journal.pcbi.1007290

Lang M, Shkolnikov M. Harmonic dynamics of the Abelian sandpile. Proceedings of the National Academy of Sciences. 2019;116(8):2821-2830. doi:10.1073/pnas.1812015116

Kavcic B, Sakashita A, Noguchi H, Ziherl P. Limiting shapes of confined lipid vesicles. Soft Matter. 2019;15(4):602-614. doi:10.1039/c8sm01956h

Cepeda Humerez SA. Estimating information flow in single cells. 2019. doi:10.15479/AT:ISTA:6473

Prizak R. Coevolution of transcription factors and their binding sites in sequence space. 2019. doi:10.15479/at:ista:th6071

Wang JWJL, Lombardi F, Zhang X, Anaclet C, Ivanov PC. Non-equilibrium critical dynamics of bursts in ;8 and ;4 rhythms as fundamental characteristic of sleep and wake micro-architecture. PLoS Computational Biology. 2019;15(11). doi:10.1371/journal.pcbi.1007268

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Hledik M, Sokolowski TR, Tkadik G. A tight upper bound on mutual information. In: IEEE Information Theory Workshop, ITW 2019. IEEE; 2019. doi:10.1109/ITW44776.2019.8989292

De Martino A, De Martino D. An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. 2018;4(4). doi:10.1016/j.heliyon.2018.e00596

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

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

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

Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Supplemental material for Bodova et al., 2018. 2018. 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

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

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

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

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

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

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

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

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

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

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

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

Der R, Martius GS. Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. 2017;11(MAR). 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

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

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

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

Chalk MJ, Masset P, Gutkin B, Denève S. Supplementary appendix. 2017. 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

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

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

Levina (Martius) A, Priesemann V. Subsampling scaling. Nature Communications. 2017;8. doi:10.1038/ncomms15140

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

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

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

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

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

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

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

Lang M, Sontag E. Zeros of nonlinear systems with input invariances. Automatica. 2017;81C:46-55. doi:10.1016/j.automatica.2017.03.030

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

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

Chalk MJ, Marre O, Tkadik G. Relevant sparse codes with variational information bottleneck. In: Vol 29. Neural Information Processing Systems; 2016:1965-1973.

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.

Lang M, Stelling J. Modular parameter identification of biomolecular networks. SIAM Journal on Scientific Computing. 2016;38(6):8-08. doi:10.1137/15M103306X

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

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

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

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

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

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

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

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

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

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

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

Lang M, Sontag E. Scale-invariant systems realize nonlinear differential operators. In: Vol 2016-July. IEEE; 2016. doi:10.1109/ACC.2016.7526722

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

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

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

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

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

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

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

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

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.

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

Hillenbrand P, Gerland U, Tkadik G. Computation of positional information in an Ising model. 2016. 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

Hillenbrand P, Gerland U, Tkadik G. Computation of positional information in a discrete morphogen field. 2016. doi:10.1371/journal.pone.0163628.s003

Rieckh G. Studying the complexities of transcriptional regulation. 2016.

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

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

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

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

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

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

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

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

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

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

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

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

Friedlander T, Mayo AE, Tlusty T, Alon U. Supporting information text. 2015. doi:10.1371/journal.pcbi.1004055.s001