K. Nomura et al., “Tipping points of space debris in low earth orbit,” International Journal of the Commons, vol. 18, no. 1. Ubiquity Press, 2024.

M. Hledik, “Genetic information and biological optimization,” Institute of Science and Technology Austria, 2024.

B. E. Casillas Perez, K. Bodova, A. V. Grasse, G. Tkadik, and S. Cremer, “Dynamic pathogen detection and social feedback shape collective hygiene in ants,” Nature Communications, vol. 14. Springer Nature, 2023.

F. Lombardi, S. Pepic, O. Shriki, G. Tkadik, and D. De Martino, “Statistical modeling of adaptive neural networks explains co-existence of avalanches and oscillations in resting human brain,” Nature Computational Science, vol. 3. Springer Nature, pp. 254–263, 2023.

M. Reinhardt, G. Tkadik, and P. R. Ten Wolde, “Path weight sampling: Exact Monte Carlo computation of the mutual information between stochastic trajectories,” Physical Review X, vol. 13, no. 4. American Physical Society, 2023.

M. Nardin, J. L. Csicsvari, G. Tkadik, and C. Savin, “The structure of hippocampal C interactions optimizes spatial coding across experience,” The Journal of Neuroscience, vol. 43, no. 48. Society of Neuroscience, pp. 8140–8156, 2023.

S. Scarpetta et al., “Criticality of neuronal avalanches in human sleep and their relationship with sleep macro- and micro-architecture,” iScience, vol. 26, no. 10. Elsevier, p. 107840, 2023.

S. Rella, Y. Kulikova, A. Minnegalieva, and F. Kondrashov, “Complex vaccination strategies prevent the emergence of vaccine resistance,” in European Journal of Public Health, 2023, vol. 33, no. Supplement_2.

F. Lombardi et al., “Beyond pulsed inhibition: Alpha oscillations modulate attenuation and amplification of neural activity in the awake resting state,” Cell Reports, vol. 42, no. 10. Elsevier, 2023.

F. Lombardi et al., “Alpha rhythm induces attenuation-amplification dynamics in neural activity cascades,” bioRxiv. Cold Spring Harbor Laboratory, 2022.

V. Ngampruetikorn, V. Sachdeva, J. Torrence, J. Humplik, D. J. Schwab, and S. E. Palmer, “Inferring couplings in networks across order-disorder phase transitions,” Physical Review Research, vol. 4, no. 2. American Physical Society, 2022.

B. Zoller, T. Gregor, and G. Tkadik, “Eukaryotic gene regulation at equilibrium, or non?,” Current Opinion in Systems Biology, vol. 31, no. 9. Elsevier, 2022.

T. Zisis et al., “Disentangling cadherin-mediated cell-cell interactions in collective cancer cell migration,” Biophysical Journal, vol. 121, no. 1. Elsevier, pp. -60, 2022.

M. Lagator et al., “Predicting bacterial promoter function and evolution from random sequences,” eLife, vol. 11. eLife Sciences Publications, 2022.

W. F. Mlynarski and G. Tkadik, “Efficient coding theory of dynamic attentional modulation,” PLoS Biology, vol. 20, no. 12. Public Library of Science, p. e3001889, 2022.

M. Hledik, N. H. Barton, and G. Tkadik, “Accumulation and maintenance of information in evolution,” Proceedings of the National Academy of Sciences, vol. 119, no. 36. Proceedings of the National Academy of Sciences, 2022.

K. Bodova, E. Szep, and N. H. Barton, “Dynamic maximum entropy provides accurate approximation of structured population dynamics,” PLoS Computational Biology, vol. 17, no. 12. Public Library of Science, 2021.

F. Lombardi, S. Pepic, O. Shriki, G. Tkadik, and D. De Martino, “Quantifying the coexistence of neuronal oscillations and avalanches.” arXiv.

B. Kavcic and G. Tkadik, “Token-driven totally asymmetric simple exclusion process,” arXiv. .

F. Lombardi, O. Shriki, H. J. Herrmann, and L. de Arcangelis, “Long-range temporal correlations in the broadband resting state activity of the human brain revealed by neuronal avalanches,” Neurocomputing, vol. 461. Elsevier, pp. 657–666, 2021.

G. Tkadik and T. Gregor, “The many bits of positional information,” Development, vol. 148, no. 2. The Company of Biologists, 2021.

W. F. Mlynarski and A. M. Hermundstad, “Efficient and adaptive sensory codes,” Nature Neuroscience, vol. 24. Springer Nature, pp. 998–1009, 2021.

T. Zisis et al., “Sequential and switchable patterning for studying cellular processes under spatiotemporal control,” ACS Applied Materials and Interfaces, vol. 13, no. 30. American Chemical Society, pp. 35545–35560, 2021.

M. Gabrielaitis, “Fast and accurate amplitude demodulation of wideband signals,” IEEE Transactions on Signal Processing, vol. 69. Institute of Electrical and Electronics Engineers, pp. 4039–4054, 2021.

M. J. Chalk, G. Tkadik, and O. Marre, “Inferring the function performed by a recurrent neural network,” PLoS ONE, vol. 16, no. 4. Public Library of Science, 2021.

B. Kavcic, G. Tkadik, and M. T. Bollenbach, “Minimal biophysical model of combined antibiotic action,” PLOS Computational Biology, vol. 17. Public Library of Science, 2021.

A. A. Nagy-Staron et al., “Local genetic context shapes the function of a gene regulatory network,” eLife, vol. 10. eLife Sciences Publications, 2021.

W. F. Mlynarski, M. Hledik, T. R. Sokolowski, and G. Tkadik, “Statistical analysis and optimality of neural systems,” Neuron, vol. 109, no. 7. Cell Press, p. 1227–1241.e5, 2021.

M. Nardin, J. L. Csicsvari, G. Tkadik, and C. Savin, “The structure of hippocampal C interactions optimizes spatial coding across experience,” bioRxiv. Cold Spring Harbor Laboratory.

F. Lombardi, J. W. J. L. Wang, X. Zhang, and P. C. Ivanov, “Power-law correlations and coupling of active and quiet states underlie a class of complex systems with self-organization at criticality,” EPJ Web of Conferences, vol. 230. EDP Sciences, 2020.

M. Narasimhan et al., “Evolutionarily unique mechanistic framework of clathrin-mediated endocytosis in plants,” eLife, vol. 9. eLife Sciences Publications, 2020.

R. Grah and T. Friedlander, “Distribution of crosstalk values.” Public Library of Science, 2020.

R. Grah and T. Friedlander, “Supporting information.” Public Library of Science, 2020.

M. J. Berry and G. Tkadik, “Clustering of neural activity: A design principle for population codes,” Frontiers in Computational Neuroscience, vol. 14. Frontiers, 2020.

O. Maoz, G. Tkadik, M. S. Esteki, R. Kiani, and E. Schneidman, “Learning probabilistic neural representations with randomly connected circuits,” Proceedings of the National Academy of Sciences of the United States of America, vol. 117, no. 40. National Academy of Sciences, pp. 25066–25073, 2020.

R. Rizzo, X. Zhang, J. W. J. L. Wang, F. Lombardi, and P. C. Ivanov, “Network physiology of cortico–muscular interactions,” Frontiers in Physiology, vol. 11. Frontiers, 2020.

R. Grah, B. Zoller, and G. Tkadik, “Nonequilibrium models of optimal enhancer function,” PNAS, vol. 117, no. 50. National Academy of Sciences, pp. 31614–31622, 2020.

F. Lombardi et al., “Critical dynamics and coupling in bursts of cortical rhythms indicate non-homeostatic mechanism for sleep-stage transitions and dual role of VLPO neurons in both sleep and wake,” Journal of Neuroscience, vol. 40, no. 1. Society for Neuroscience, pp. 171–190, 2020.

R. Grah, “Gene regulation across scales – how biophysical constraints shape evolution,” Institute of Science and Technology Austria, 2020.

R. Grah, B. Zoller, and G. Tkadik, “Normative models of enhancer function,” bioRxiv. Cold Spring Harbor Laboratory, 2020.

R. Grah and T. Friedlander, “The relation between crosstalk and gene regulation form revisited,” PLOS Computational Biology, vol. 16, no. 2. Public Library of Science, 2020.

R. Grah and T. Friedlander, “Maximizing crosstalk.” Public Library of Science, 2020.

B. Kavcic, “Analysis scripts and research data for the paper ‘Mechanisms of drug interactions between translation-inhibiting antibiotics.’” Institute of Science and Technology Austria, 2020.

B. Kavcic, “Analysis scripts and research data for the paper ‘Minimal biophysical model of combined antibiotic action.’” Institute of Science and Technology Austria, 2020.

R. Grah, “Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level Gene Expression regulation.” Institute of Science and Technology Austria, 2020.

B. Kavcic, “Perturbations of protein synthesis: from antibiotics to genetics and physiology,” Institute of Science and Technology Austria, 2020.

B. Kavcic, G. Tkadik, and M. T. Bollenbach, “Mechanisms of drug interactions between translation-inhibiting antibiotics,” Nature Communications, vol. 11. Springer Nature, 2020.

B. Kavcic, G. Tkadik, and M. T. Bollenbach, “A minimal biophysical model of combined antibiotic action,” bioRxiv. Cold Spring Harbor Laboratory, 2020.

I. Tomanek et al., “Gene amplification as a form of population-level gene expression regulation,” Nature Ecology &; Evolution, vol. 4, no. 4. Springer Nature, pp. 612–625, 2020.

W. Bialek, T. Gregor, and G. Tkadik, “Action at a distance in transcriptional regulation,” arXiv:1912.08579. ArXiv.

M. D. Petkova, G. Tkadik, W. Bialek, E. F. Wieschaus, and T. Gregor, “Optimal decoding of cellular identities in a genetic network,” Cell, vol. 176, no. 4. Cell Press, p. 844–855.e15, 2019.

D. De Martino, “Feedback-induced self-oscillations in large interacting systems subjected to phase transitions,” Journal of Physics A: Mathematical and Theoretical, vol. 52, no. 4. IOP Publishing, 2019.

K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Temporal order and precision of complex stress responses in individual bacteria,” Molecular systems biology, vol. 15, no. 2. Embo Press, 2019.

J. Ruess, M. Pleska, C. C. Guet, and G. Tkadik, “Molecular noise of innate immunity shapes bacteria-phage ecologies,” PLoS Computational Biology, vol. 15, no. 7. Public Library of Science, 2019.

J. Ruess, M. Pleska, C. C. Guet, and G. Tkadik, “Supporting text and results.” Public Library of Science, 2019.

T. R. Sokolowski et al., GFRD in all dimensions,” The Journal of Chemical Physics, vol. 150, no. 5. AIP Publishing, 2019.

S. A. Cepeda Humerez, J. Ruess, and G. Tkadik, “Estimating information in time-varying signals,” PLoS computational biology, vol. 15, no. 9. Public Library of Science, p. e1007290, 2019.

M. Lang and M. Shkolnikov, “Harmonic dynamics of the Abelian sandpile,” Proceedings of the National Academy of Sciences, vol. 116, no. 8. National Academy of Sciences, pp. 2821–2830, 2019.

B. Kavcic, A. Sakashita, H. Noguchi, and P. Ziherl, “Limiting shapes of confined lipid vesicles,” Soft Matter, vol. 15, no. 4. Royal Society of Chemistry, pp. 602–614, 2019.

S. A. Cepeda Humerez, “Estimating information flow in single cells,” Institute of Science and Technology Austria, 2019.

R. Prizak, “Coevolution of transcription factors and their binding sites in sequence space,” Institute of Science and Technology Austria, 2019.

J. W. J. L. Wang, F. Lombardi, X. Zhang, C. Anaclet, and P. C. Ivanov, “Non-equilibrium critical dynamics of bursts in ;8 and ;4 rhythms as fundamental characteristic of sleep and wake micro-architecture,” PLoS Computational Biology, vol. 15, no. 11. Public Library of Science, 2019.

M. Carballo-Pacheco et al., “Receptor crosstalk improves concentration sensing of multiple ligands,” Physical Review E, vol. 99, no. 2. American Physical Society, 2019.

M. Hledik, T. R. Sokolowski, and G. Tkadik, “A tight upper bound on mutual information,” in IEEE Information Theory Workshop, ITW 2019, Visby, Sweden, 2019.

A. De Martino and D. De Martino, “An introduction to the maximum entropy approach and its application to inference problems in biology,” Heliyon, vol. 4, no. 4. Elsevier, 2018.

P. Misun, A. Birchler, M. Lang, A. Hierlemann, and O. Frey, “Fabrication and operation of microfluidic hanging drop networks,” Methods in Molecular Biology, vol. 1771. Springer, pp. 183–202, 2018.

A. Granados, J. Pietsch, S. A. Cepeda Humerez, I. Farquhar, G. Tkadik, and P. Swain, “Distributed and dynamic intracellular organization of extracellular information,” PNAS, vol. 115, no. 23. National Academy of Sciences, pp. 6088–6093, 2018.

K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system,” Genetics, vol. 209, no. 3. Genetics Society of America, pp. 861–883, 2018.

K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Supplemental material for Bodova et al., 2018.” Genetics Society of America, 2018.

K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, and G. Tkadik, “Probabilistic models of individual and collective animal behavior,” PLoS One, vol. 13, no. 3. Public Library of Science, 2018.

M. Pleska, M. Lang, D. Refardt, B. Levin, and C. C. Guet, “Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity,” Nature Ecology and Evolution, vol. 2, no. 2. Springer Nature, pp. 359–366, 2018.

K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, and G. Tkadik, “Implementation of the inference method in Matlab.” Public Library of Science, 2018.

U. Ferrari, S. Deny, M. J. Chalk, G. Tkadik, O. Marre, and T. Mora, “Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons,” Physical Review E, vol. 98, no. 4. American Physical Society, 2018.

M. J. Chalk, O. Marre, and G. Tkadik, “Toward a unified theory of efficient, predictive, and sparse coding,” PNAS, vol. 115, no. 1. National Academy of Sciences, pp. 186–191, 2018.

K. Bodova, J. Haskovec, and P. Markowich, “Well posedness and maximum entropy approximation for the dynamics of quantitative traits,” Physica D: Nonlinear Phenomena, vol. 376–377. Elsevier, pp. 108–120, 2018.

A. Palmer, R. P. Chait, and R. Kishony, “Nonoptimal gene expression creates latent potential for antibiotic resistance,” Molecular Biology and Evolution, vol. 35, no. 11. Oxford University Press, pp. 2669–2684, 2018.

V. Botella Soler, S. Deny, G. S. Martius, O. Marre, and G. Tkadik, “Nonlinear decoding of a complex movie from the mammalian retina,” PLoS Computational Biology, vol. 14, no. 5. Public Library of Science, 2018.

S. Deny, O. Marre, V. Botella-Soler, G. S. Martius, and G. Tkadik, “Nonlinear decoding of a complex movie from the mammalian retina.” Institute of Science and Technology Austria, 2018.

D. De Martino, A. A. Mc, T. Bergmiller, C. C. Guet, and G. Tkadik, “Statistical mechanics for metabolic networks during steady state growth,” Nature Communications, vol. 9, no. 1. Springer Nature, 2018.

D. De Martino and G. Tkadik, “Supporting materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology Austria, 2018.

C. Igler, M. Lagator, G. Tkadik, J. P. Bollback, and C. C. Guet, “Evolutionary potential of transcription factors for gene regulatory rewiring,” Nature Ecology and Evolution, vol. 2, no. 10. Nature Publishing Group, pp. 1633–1643, 2018.

C. Igler, M. Lagator, G. Tkadik, J. P. Bollback, and C. C. Guet, “Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring.” Institute of Science and Technology Austria, 2018.

R. P. Chait, J. Ruess, T. Bergmiller, G. Tkadik, and C. C. Guet, “Shaping bacterial population behavior through computer interfaced control of individual cells,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017.

R. Der and G. S. Martius, “Dynamical self consistency leads to behavioral development and emergent social interactions in robots,” presented at the ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , Cergy-Pontoise, France, 2017.

R. Der and G. S. Martius, “Self organized behavior generation for musculoskeletal robots,” Frontiers in Neurorobotics, vol. 11, no. MAR. Frontiers Research Foundation, 2017.

J. Humplik and G. Tkadik, “Probabilistic models for neural populations that naturally capture global coupling and criticality,” PLoS Computational Biology, vol. 13, no. 9. Public Library of Science, 2017.

R. Harpaz, G. Tkadik, and E. Schneidman, “Discrete modes of social information processing predict individual behavior of fish in a group,” PNAS, vol. 114, no. 38. National Academy of Sciences, pp. 10149–10154, 2017.

J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkadik, and M. Berry, “Data from: Error-robust modes of the retinal population code.” Dryad, 2017.

M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Sensory noise predicts divisive reshaping of receptive fields,” PLoS Computational Biology, vol. 13, no. 6. Public Library of Science, 2017.

M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Supplementary appendix.” Public Library of Science, 2017.

K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment,” Cell Systems, vol. 4, no. 4. Cell Press, pp. 393–403, 2017.

A. Martin Del Campo Sanchez, S. A. Cepeda Humerez, and C. Uhler, “Exact goodness-of-fit testing for the Ising model,” Scandinavian Journal of Statistics, vol. 44, no. 2. Wiley-Blackwell, pp. 285–306, 2017.

S. Deny et al., “Multiplexed computations in retinal ganglion cells of a single type,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017.

A. Levina (Martius) and V. Priesemann, “Subsampling scaling,” Nature Communications, vol. 8. Nature Publishing Group, 2017.

T. Friedlander, R. Prizak, N. H. Barton, and G. Tkadik, “Evolution of new regulatory functions on biophysically realistic fitness landscapes,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017.

D. De Martino, “Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics,”  Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 95, no. 6. American Institute of Physics, p. 062419, 2017.

D. De Martino, F. Capuani, and A. De Martino, “Quantifying the entropic cost of cellular growth control,”  Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 96, no. 1. American Institute of Physics, 2017.

M. P. Zagórski et al., “Decoding of position in the developing neural tube from antiparallel morphogen gradients,” Science, vol. 356, no. 6345. American Association for the Advancement of Science, pp. 1379–1383, 2017.

S. Colabrese, D. De Martino, L. Leuzzi, and E. Marinari, “Phase transitions in integer linear problems,”  Journal of Statistical Mechanics: Theory and Experiment, vol. 2017, no. 9. IOPscience, 2017.

C. Savin and G. Tkadik, “Maximum entropy models as a tool for building precise neural controls,” Current Opinion in Neurobiology, vol. 46. Elsevier, pp. 120–126, 2017.

D. De Martino, “Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes,” Physical Review E, vol. 96, no. 6. American Physical Society, 2017.

M. Lang and E. Sontag, “Zeros of nonlinear systems with input invariances,” Automatica, vol. 81C. International Federation of Automatic Control, pp. 46–55, 2017.

O. Marre, G. Tkadik, D. Amodei, E. Schneidman, W. Bialek, and M. Berry, “Multi-electrode array recording from salamander retinal ganglion cells.” Institute of Science and Technology Austria, 2017.

T. Bergmiller et al., “Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity.” Institute of Science and Technology Austria, 2017.

T. Bergmiller et al., “Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity,” Science, vol. 356, no. 6335. American Association for the Advancement of Science, pp. 311–315, 2017.

V. Barone et al., “An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate,” Developmental Cell, vol. 43, no. 2. Cell Press, pp. 198–211, 2017.

M. J. Chalk, O. Marre, and G. Tkadik, “Relevant sparse codes with variational information bottleneck,” presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain, 2016, vol. 29, pp. 1965–1973.

C. Savin and G. Tkadik, “Estimating nonlinear neural response functions using GP priors and Kronecker methods,” presented at the NIPS: Neural Information Processing Systems, Barcelona; Spain, 2016, vol. 29, pp. 3610–3618.

M. Lang and J. Stelling, “Modular parameter identification of biomolecular networks,” SIAM Journal on Scientific Computing, vol. 38, no. 6. Society for Industrial and Applied Mathematics , pp. 8–08, 2016.

G. Tkadik, “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, vol. 17. Elsevier, pp. 166–167, 2016.

D. De Martino and D. Masoero, “Asymptotic analysis of noisy fitness maximization, applied to metabolism &;amp; growth,”  Journal of Statistical Mechanics: Theory and Experiment, vol. 2016, no. 12. IOPscience, 2016.

F. Hu et al., “Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination,” Journal of Clinical Microbiology, vol. 54, no. 12. American Society for Microbiology, pp. 3010–3017, 2016.

G. S. Martius, R. Hostettler, A. Knoll, and R. Der, “Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm,” presented at the IEEE RSJ International Conference on Intelligent Robots and Systems IROS , Daejeon, Korea, 2016, vol. 2016–November.

G. Miki, A. Stoll, J. Bevirt, R. Grah, and M. Moore, “Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency,” presented at the AIAA: Aviation Technology, Integration, and Operations Conference, Washington, D.C., USA, 2016, pp. 1–19.

T. R. Sokolowski, A. Walczak, W. Bialek, and G. Tkadik, “Extending the dynamic range of transcription factor action by translational regulation,” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 93, no. 2. American Institute of Physics, 2016.

P. Recouvreux, T. R. Sokolowski, A. Grammoustianou, P. Tenwolde, and M. Dogterom, “Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells,” PNAS, vol. 113, no. 7. National Academy of Sciences, pp. 1811–1816, 2016.

G. Tkadik and W. Bialek, “Information processing in living systems,” Annual Review of Condensed Matter Physics, vol. 7. Annual Reviews, pp. 89–117, 2016.

D. De Martino, “The dual of the space of interactions in neural network models,” International Journal of Modern Physics C, vol. 27, no. 6. World Scientific Publishing, 2016.

M. J. Chalk, B. Gutkin, and S. Denève, “Neural oscillations as a signature of efficient coding in the presence of synaptic delays,” eLife, vol. 5, no. 2016JULY. eLife Sciences Publications, 2016.

L. Stone, M. Baym, T. Lieberman, R. P. Chait, J. Clardy, and R. Kishony, “Compounds that select against the tetracycline-resistance efflux pump,” Nature Chemical Biology, vol. 12, no. 11. Nature Publishing Group, pp. 902–904, 2016.

M. Lang and E. Sontag, “Scale-invariant systems realize nonlinear differential operators,” presented at the ACC: American Control Conference, Boston, MA, USA, 2016, vol. 2016–July.

R. P. Chait, A. Palmer, I. Yelin, and R. Kishony, “Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments,” Nature Communications, vol. 7. Nature Publishing Group, 2016.

M. Baym et al., “Spatiotemporal microbial evolution on antibiotic landscapes,” Science, vol. 353, no. 6304. American Association for the Advancement of Science, pp. 1147–1151, 2016.

D. De Martino, F. Capuani, and A. De Martino, “Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli,” Physical Biology, vol. 13, no. 3. IOP Publishing Ltd., 2016.

K. Bodova, G. Tkadik, and N. H. Barton, “A general approximation for the dynamics of quantitative traits,” Genetics, vol. 202, no. 4. Genetics Society of America, pp. 1523–1548, 2016.

D. De Martino, “Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis,” Physical Biology, vol. 13, no. 1. IOP Publishing Ltd., 2016.

C. Schilling, S. Bogomolov, T. A. Henzinger, A. Podelski, and J. Ruess, “Adaptive moment closure for parameter inference of biochemical reaction networks,” Biosystems, vol. 149. Elsevier, pp. 15–25, 2016.

G. S. Martius, R. Hostettler, A. Knoll, and R. Der, “Self-organized control of an tendon driven arm by differential extrinsic plasticity,” in Proceedings of the Artificial Life Conference 2016, Cancun, Mexico, 2016, vol. 28, pp. 142–143.

J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkadik, and M. Berry, “Error-robust modes of the retinal population code,” PLoS Computational Biology, vol. 12, no. 11. Public Library of Science, 2016.

T. Monk, C. Savin, and J. Lücke, “Neurons equipped with intrinsic plasticity learn stimulus intensity statistics,” presented at the NIPS: Neural Information Processing Systems, Barcelona, Spaine, 2016, vol. 29, pp. 4285–4293.

P. Hillenbrand, U. Gerland, and G. Tkadik, “Beyond the French flag model: Exploiting spatial and gene regulatory interactions for positional information,” PLoS One, vol. 11, no. 9. Public Library of Science, 2016.

P. Hillenbrand, U. Gerland, and G. Tkadik, “Computation of positional information in an Ising model.” Public Library of Science, 2016.

P. Hillenbrand, U. Gerland, and G. Tkadik, “Error bound on an estimator of position.” Public Library of Science, 2016.

P. Hillenbrand, U. Gerland, and G. Tkadik, “Computation of positional information in a discrete morphogen field.” Public Library of Science, 2016.

G. Rieckh, “Studying the complexities of transcriptional regulation,” Institute of Science and Technology Austria, 2016.

T. Friedlander, R. Prizak, C. C. Guet, N. H. Barton, and G. Tkadik, “Intrinsic limits to gene regulation by global crosstalk,” Nature Communications, vol. 7. Nature Publishing Group, 2016.

F. Parise, J. Lygeros, and J. Ruess, “Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study,” Frontiers in Environmental Science, vol. 3. Frontiers, 2015.

J. Ruess, “Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space,” Journal of Chemical Physics, vol. 143, no. 24. American Institute of Physics, 2015.

J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, and J. Lygeros, “Iterative experiment design guides the characterization of a light-inducible gene expression circuit,” PNAS, vol. 112, no. 26. National Academy of Sciences, pp. 8148–8153, 2015.

M. Gilson, C. Savin, and F. Zenke, “Editorial: Emergent neural computation from the interaction of different forms of plasticity,” Frontiers in Computational Neuroscience, vol. 9, no. 11. Frontiers Research Foundation, 2015.

R. Der and G. S. Martius, “Novel plasticity rule can explain the development of sensorimotor intelligence,” PNAS, vol. 112, no. 45. National Academy of Sciences, pp. 24–32, 2015.

S. Bogomolov, T. A. Henzinger, A. Podelski, J. Ruess, and C. Schilling, “Adaptive moment closure for parameter inference of biochemical reaction networks,” vol. 9308. Springer, pp. 77–89, 2015.

O. Marre, V. Botella Soler, K. Simmons, T. Mora, G. Tkadik, and M. Berry, “High accuracy decoding of dynamical motion from a large retinal population,” PLoS Computational Biology, vol. 11, no. 7. Public Library of Science, 2015.

G. Tkadik et al., “Thermodynamics and signatures of criticality in a network of neurons,” PNAS, vol. 112, no. 37. National Academy of Sciences, pp. 11508–11513, 2015.

J. Ruess and J. Lygeros, “Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks,” ACM Transactions on Modeling and Computer Simulation, vol. 25, no. 2. ACM, 2015.

G. Tkadik, J. Dubuis, M. Petkova, and T. Gregor, “Positional information, positional error, and readout precision in morphogenesis: A mathematical framework,” Genetics, vol. 199, no. 1. Genetics Society of America, pp. 39–59, 2015.

T. R. Sokolowski and G. Tkadik, “Optimizing information flow in small genetic networks. IV. Spatial coupling,” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 91, no. 6. American Institute of Physics, 2015.

T. Friedlander, A. E. Mayo, T. Tlusty, and U. Alon, “Supporting information text.” Public Library of Science, 2015.

T. Friedlander, A. Mayo, T. Tlusty, and U. Alon, “Evolution of bow-tie architectures in biology,” PLoS Computational Biology, vol. 11, no. 3. Public Library of Science, 2015.

T. Friedlander, A. E. Mayo, T. Tlusty, and U. Alon, “Evolutionary simulation code.” Public Library of Science, 2015.

M. Tugrul, T. Paixao, N. H. Barton, and G. Tkadik, “Other fitness models for comparison &; for interacting TFBSs.” Public Library of Science, 2015.

M. Tugrul, T. Paixao, N. H. Barton, and G. Tkadik, “Dynamics of transcription factor binding site evolution,” PLoS Genetics, vol. 11, no. 11. Public Library of Science, 2015.

S. A. Cepeda Humerez, G. Rieckh, and G. Tkadik, “Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation,” Physical Review Letters, vol. 115, no. 24. American Physical Society, 2015.

G. S. Martius and E. Olbrich, “Quantifying emergent behavior of autonomous robots,” Entropy, vol. 17, no. 10. MDPI, pp. 7266–7297, 2015.

C. Savin and S. Denève, “Spatio-temporal representations of uncertainty in spiking neural networks,” presented at the NIPS: Neural Information Processing Systems, Montreal, Canada, 2014, vol. 3, no. January, pp. 2024–2032.

A. Hermundstad, J. Briguglio, M. Conte, J. Victor, V. Balasubramanian, and G. Tkadik, “Variance predicts salience in central sensory processing,” eLife, no. November. eLife Sciences Publications, 2014.

R. Kollár, K. Bodova, J. Nosek, and d. Tomáska, “Mathematical model of alternative mechanism of telomere length maintenance,” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 89, no. 3. American Institute of Physics, 2014.

T. Ezard, R. Prizak, and R. Hoyle, “The fitness costs of adaptation via phenotypic plasticity and maternal effects,” Functional Ecology, vol. 28, no. 3. Wiley-Blackwell, pp. 693–701, 2014.

J. Humplik, A. Hill, and M. Nowak, “Evolutionary dynamics of infectious diseases in finite populations,” Journal of Theoretical Biology, vol. 360. Elsevier, pp. 149–162, 2014.

C. Savin and J. Triesch, “Emergence of task-dependent representations in working memory circuits,” Frontiers in Computational Neuroscience, vol. 8, no. MAY. Frontiers Research Foundation, 2014.

K. Bodova, D. Paydarfar, and D. Forger, “Characterizing spiking in noisy type II neurons,”  Journal of Theoretical Biology, vol. 365. Academic Press, pp. 40–54, 2014.

V. Botella Soler and P. Glendinning, “Hierarchy and polysynchrony in an adaptive network ,” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 89, no. 6. American Institute of Physics, 2014.

G. Rieckh and G. Tkadik, “Noise and information transmission in promoters with multiple internal states,” Biophysical Journal, vol. 106, no. 5. Biophysical Society, pp. 1194–1204, 2014.

G. Tkadik, A. Ghosh, E. Schneidman, and R. Segev, “Adaptation to changes in higher-order stimulus statistics in the salamander retina,” PLoS One, vol. 9, no. 1. Public Library of Science, 2014.

R. Prizak, T. Ezard, and R. Hoyle, “Fitness consequences of maternal and grandmaternal effects,” Ecology and Evolution, vol. 4, no. 15. Wiley-Blackwell, pp. 3139–3145, 2014.

K. Simmons et al., “Data from: Transformation of stimulus correlations by the retina.” Dryad, 2014.

G. Tkadik, O. Marre, D. Amodei, E. Schneidman, W. Bialek, and M. Berry, “Searching for collective behavior in a large network of sensory neurons,” PLoS Computational Biology, vol. 10, no. 1. Public Library of Science, 2014.

M. Valderrama, V. Botella Soler, and M. Le Van Quyen, “Neuronal oscillations scale up and scale down the brain dynamics ,” in Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain, M. Meyer and Z. Pesenson, Eds. Wiley-VCH, 2013.

K. Rajan, O. Marre, and G. Tkadik, “Learning quadratic receptive fields from neural responses to natural stimuli,” Neural Computation, vol. 25, no. 7. MIT Press , pp. 1661–1692, 2013.

G. Tkadik, O. Marre, T. Mora, D. Amodei, M. Berry, and W. Bialek, “The simplest maximum entropy model for collective behavior in a neural network,” Journal of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3. IOP Publishing Ltd., 2013.

M. Berry, G. Tkadik, J. Dubuis, O. Marre, and R. Da Silveira, “A simple method for estimating the entropy of neural activity,” Journal of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3. IOP Publishing Ltd., 2013.

E. Granot Atedgi, G. Tkadik, R. Segev, and E. Schneidman, “Stimulus-dependent maximum entropy models of neural population codes,” PLoS Computational Biology, vol. 9, no. 3. Public Library of Science, 2013.

V. Botella Soler, J. Oteo, J. Ros, and P. Glendinning, “Lyapunov exponent and topological entropy plateaus in piecewise linear maps,” Journal of Physics A: Mathematical and Theoretical, vol. 46, no. 12. IOP Publishing Ltd., 2013.

G. Tkadik, E. Granot Atedgi, R. Segev, and E. Schneidman, “Retinal metric: a stimulus distance measure derived from population neural responses,” Physical Review Letters, vol. 110, no. 5. American Physical Society, 2013.

J. Dubuis, G. Tkadik, E. Wieschaus, T. Gregor, and W. Bialek, “Positional information, in bits,” PNAS, vol. 110, no. 41. National Academy of Sciences, pp. 16301–16308, 2013.

Y. Wakamoto et al., “Dynamic persistence of antibiotic-stressed mycobacteria,” Science, vol. 339, no. 6115. American Association for the Advancement of Science, pp. 91–95, 2013.

K. Simmons et al., “Transformation of stimulus correlations by the retina,” PLoS Computational Biology, vol. 9, no. 12. Public Library of Science, 2013.

G. Stephens, T. Mora, G. Tkadik, and W. Bialek, “Statistical thermodynamics of natural images,” Physical Review Letters, vol. 110, no. 1. American Physical Society, 2013.

G. Tkadik, A. Walczak, and W. Bialek, “Optimizing information flow in small genetic networks. III. A self-interacting gene,”  Physical Review E statistical nonlinear and soft matter physics , vol. 85, no. 4. American Institute of Physics, 2012.

G. Rieckh, W. Kreuzer, H. Waubke, and P. Balazs, “A 2.5D-Fourier-BEM model for vibrations in a tunnel running through layered anisotropic soil,”  Engineering Analysis with Boundary Elements, vol. 36, no. 6. Elsevier, pp. 960–967, 2012.

G. Tkadik and A. Walczak, “Information transmission in genetic regulatory networks a review,” Journal of Physics: Condensed Matter, vol. 23, no. 15. IOP Publishing Ltd., 2011.

G. Tkadik et al., “Natural images from the birthplace of the human eye,” PLoS One, vol. 6, no. 6. Public Library of Science, 2011.