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, “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.

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.

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.

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.

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.