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.
LibreCat: https://research-explorer.ista.ac.at/record/2016
DOI: 10.1111/sjos.12251
WoS: 000400985000001
arXiv: 1410.1242

S. Deny et al., “Multiplexed computations in retinal ganglion cells of a single type,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017.
LibreCat: https://research-explorer.ista.ac.at/record/1104
DOI: 10.1038/s41467-017-02159-y
WoS: 000417241200004

A. Levina (Martius) and V. Priesemann, “Subsampling scaling,” Nature Communications, vol. 8. Nature Publishing Group, 2017.
LibreCat: https://research-explorer.ista.ac.at/record/993
DOI: 10.1038/ncomms15140
WoS: 000400560700001

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.
LibreCat: https://research-explorer.ista.ac.at/record/955
DOI: 10.1038/s41467-017-00238-8
WoS: 000407198800005

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.
LibreCat: https://research-explorer.ista.ac.at/record/959
DOI: 10.1103/PhysRevE.95.062419
WoS: 000404546400004

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.
LibreCat: https://research-explorer.ista.ac.at/record/947
DOI: 10.1103/PhysRevE.96.010401
WoS: 000405194200002

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.
LibreCat: https://research-explorer.ista.ac.at/record/943
DOI: 10.1126/science.aam5887
WoS: 000404351500036
PMID: 28663499

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.
LibreCat: https://research-explorer.ista.ac.at/record/823
DOI: 10.1088/1742-5468/aa85c3
WoS: 000411842900001

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.
LibreCat: https://research-explorer.ista.ac.at/record/730
DOI: 10.1016/j.conb.2017.08.001
WoS: 000416196400016

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.
LibreCat: https://research-explorer.ista.ac.at/record/548
DOI: 10.1103/PhysRevE.96.060401

M. Lang and E. Sontag, “Zeros of nonlinear systems with input invariances,” Automatica, vol. 81C. International Federation of Automatic Control, pp. 46–55, 2017.
LibreCat: https://research-explorer.ista.ac.at/record/1007
DOI: 10.1016/j.automatica.2017.03.030
WoS: 000403513900006

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.
LibreCat: https://research-explorer.ista.ac.at/record/665
DOI: 10.1126/science.aaf4762

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.
LibreCat: https://research-explorer.ista.ac.at/record/735
DOI: 10.1016/j.devcel.2017.09.014
WoS: 000413443700011

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.
LibreCat: https://research-explorer.ista.ac.at/record/1082

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.
LibreCat: https://research-explorer.ista.ac.at/record/1105

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.
LibreCat: https://research-explorer.ista.ac.at/record/1170
DOI: 10.1137/15M103306X

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.
LibreCat: https://research-explorer.ista.ac.at/record/1171
DOI: 10.1016/j.plrev.2016.06.005

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.
LibreCat: https://research-explorer.ista.ac.at/record/1188
DOI: 10.1088/1742-5468/aa4e8f

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.
LibreCat: https://research-explorer.ista.ac.at/record/1203
DOI: 10.1128/JCM.01511-16

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.
LibreCat: https://research-explorer.ista.ac.at/record/1214
DOI: 10.1109/IROS.2016.7759138

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.
LibreCat: https://research-explorer.ista.ac.at/record/1220
DOI: 10.2514/6.2016-3764

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.
LibreCat: https://research-explorer.ista.ac.at/record/1242
DOI: 10.1103/PhysRevE.93.022404

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.
LibreCat: https://research-explorer.ista.ac.at/record/1244
DOI: 10.1073/pnas.1419248113

G. Tkadik and W. Bialek, “Information processing in living systems,” Annual Review of Condensed Matter Physics, vol. 7. Annual Reviews, pp. 89–117, 2016.
LibreCat: https://research-explorer.ista.ac.at/record/1248
DOI: 10.1146/annurev-conmatphys-031214-014803

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.
LibreCat: https://research-explorer.ista.ac.at/record/1260
DOI: 10.1142/S0129183116500674
arXiv: 1505.02963

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.
LibreCat: https://research-explorer.ista.ac.at/record/1266
DOI: 10.7554/eLife.13824

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.
LibreCat: https://research-explorer.ista.ac.at/record/1290
DOI: 10.1038/nchembio.2176

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.
LibreCat: https://research-explorer.ista.ac.at/record/1320
DOI: 10.1109/ACC.2016.7526722

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.
LibreCat: https://research-explorer.ista.ac.at/record/1332
DOI: 10.1038/ncomms10333

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.
LibreCat: https://research-explorer.ista.ac.at/record/1342
DOI: 10.1126/science.aag0822

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.
LibreCat: https://research-explorer.ista.ac.at/record/1394
DOI: 10.1088/1478-3975/13/3/036005

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.
LibreCat: https://research-explorer.ista.ac.at/record/1420
DOI: 10.1534/genetics.115.184127
arXiv: 1510.08344

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.
LibreCat: https://research-explorer.ista.ac.at/record/1485
DOI: 10.1088/1478-3975/13/1/016003

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.
LibreCat: https://research-explorer.ista.ac.at/record/1148
DOI: 10.1016/j.biosystems.2016.07.005

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.
LibreCat: https://research-explorer.ista.ac.at/record/8094
DOI: 10.7551/978-0-262-33936-0-ch029

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.
LibreCat: https://research-explorer.ista.ac.at/record/1197
DOI: 10.1371/journal.pcbi.1005148

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.
LibreCat: https://research-explorer.ista.ac.at/record/948

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.
LibreCat: https://research-explorer.ista.ac.at/record/1270
DOI: 10.1371/journal.pone.0163628

P. Hillenbrand, U. Gerland, and G. Tkadik, “Computation of positional information in an Ising model.” Public Library of Science, 2016.
LibreCat: https://research-explorer.ista.ac.at/record/9870
DOI: 10.1371/journal.pone.0163628.s002

P. Hillenbrand, U. Gerland, and G. Tkadik, “Error bound on an estimator of position.” Public Library of Science, 2016.
LibreCat: https://research-explorer.ista.ac.at/record/9869
DOI: 10.1371/journal.pone.0163628.s001

P. Hillenbrand, U. Gerland, and G. Tkadik, “Computation of positional information in a discrete morphogen field.” Public Library of Science, 2016.
LibreCat: https://research-explorer.ista.ac.at/record/9871
DOI: 10.1371/journal.pone.0163628.s003

G. Rieckh, “Studying the complexities of transcriptional regulation,” Institute of Science and Technology Austria, 2016.
LibreCat: https://research-explorer.ista.ac.at/record/1128

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.
LibreCat: https://research-explorer.ista.ac.at/record/1358
DOI: 10.1038/ncomms12307

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.
LibreCat: https://research-explorer.ista.ac.at/record/10794
DOI: 10.3389/fenvs.2015.00042

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.
LibreCat: https://research-explorer.ista.ac.at/record/1539
DOI: 10.1063/1.4937937

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.
LibreCat: https://research-explorer.ista.ac.at/record/1538
DOI: 10.1073/pnas.1423947112
PMID: 26085136

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.
LibreCat: https://research-explorer.ista.ac.at/record/1564
DOI: 10.3389/fncom.2015.00145

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.
LibreCat: https://research-explorer.ista.ac.at/record/1570
DOI: 10.1073/pnas.1508400112
PMID: 26504200

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.
LibreCat: https://research-explorer.ista.ac.at/record/1658
DOI: 10.1007/978-3-319-23401-4_8

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.
LibreCat: https://research-explorer.ista.ac.at/record/1697
DOI: 10.1371/journal.pcbi.1004304

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.
LibreCat: https://research-explorer.ista.ac.at/record/1701
DOI: 10.1073/pnas.1514188112
PMID: 26330611

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.
LibreCat: https://research-explorer.ista.ac.at/record/1861
DOI: 10.1145/2688906

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.
LibreCat: https://research-explorer.ista.ac.at/record/1885
DOI: 10.1534/genetics.114.171850

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.
LibreCat: https://research-explorer.ista.ac.at/record/1940
DOI: 10.1103/PhysRevE.91.062710

T. Friedlander, A. E. Mayo, T. Tlusty, and U. Alon, “Supporting information text.” Public Library of Science, 2015.
LibreCat: https://research-explorer.ista.ac.at/record/9718
DOI: 10.1371/journal.pcbi.1004055.s001

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.
LibreCat: https://research-explorer.ista.ac.at/record/1827
DOI: 10.1371/journal.pcbi.1004055

T. Friedlander, A. E. Mayo, T. Tlusty, and U. Alon, “Evolutionary simulation code.” Public Library of Science, 2015.
LibreCat: https://research-explorer.ista.ac.at/record/9773
DOI: 10.1371/journal.pcbi.1004055.s002

M. Tugrul, T. Paixao, N. H. Barton, and G. Tkadik, “Other fitness models for comparison &; for interacting TFBSs.” Public Library of Science, 2015.
LibreCat: https://research-explorer.ista.ac.at/record/9712
DOI: 10.1371/journal.pgen.1005639.s001

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.
LibreCat: https://research-explorer.ista.ac.at/record/1666
DOI: 10.1371/journal.pgen.1005639

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.
LibreCat: https://research-explorer.ista.ac.at/record/1576
DOI: 10.1103/PhysRevLett.115.248101

G. S. Martius and E. Olbrich, “Quantifying emergent behavior of autonomous robots,” Entropy, vol. 17, no. 10. MDPI, pp. 7266–7297, 2015.
LibreCat: https://research-explorer.ista.ac.at/record/1655
DOI: 10.3390/e17107266

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.
LibreCat: https://research-explorer.ista.ac.at/record/1708

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.
LibreCat: https://research-explorer.ista.ac.at/record/1886
DOI: 10.7554/eLife.03722

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.
LibreCat: https://research-explorer.ista.ac.at/record/1896
DOI: 10.1103/PhysRevE.89.032701

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.
LibreCat: https://research-explorer.ista.ac.at/record/1909
DOI: 10.1111/1365-2435.12207

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.
LibreCat: https://research-explorer.ista.ac.at/record/1928
DOI: 10.1016/j.jtbi.2014.06.039

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.
LibreCat: https://research-explorer.ista.ac.at/record/1931
DOI: 10.3389/fncom.2014.00057

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.
LibreCat: https://research-explorer.ista.ac.at/record/2028
DOI: 10.1016/j.jtbi.2014.09.041

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.
LibreCat: https://research-explorer.ista.ac.at/record/2183
DOI: 10.1103/PhysRevE.89.062809

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.
LibreCat: https://research-explorer.ista.ac.at/record/2231
DOI: 10.1016/j.bpj.2014.01.014
PMID: 24606943

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.
LibreCat: https://research-explorer.ista.ac.at/record/3263
DOI: 10.1371/journal.pone.0085841

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.
LibreCat: https://research-explorer.ista.ac.at/record/537
DOI: 10.1002/ece3.1150

K. Simmons et al., “Data from: Transformation of stimulus correlations by the retina.” Dryad, 2014.
LibreCat: https://research-explorer.ista.ac.at/record/9752
DOI: 10.5061/dryad.246qg

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.
LibreCat: https://research-explorer.ista.ac.at/record/2257
DOI: 10.1371/journal.pcbi.1003408

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.
LibreCat: https://research-explorer.ista.ac.at/record/2413
DOI: 10.1002/9783527671632.ch08

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.
LibreCat: https://research-explorer.ista.ac.at/record/2818
DOI: 10.1162/NECO_a_00463
arXiv: 1209.0121

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.
LibreCat: https://research-explorer.ista.ac.at/record/2850
DOI: 10.1088/1742-5468/2013/03/P03011
arXiv: 1207.6319

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.
LibreCat: https://research-explorer.ista.ac.at/record/2851
DOI: 10.1088/1742-5468/2013/03/P03015

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.
LibreCat: https://research-explorer.ista.ac.at/record/2863
DOI: 10.1371/journal.pcbi.1002922

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.
LibreCat: https://research-explorer.ista.ac.at/record/2861
DOI: 10.1088/1751-8113/46/12/125101

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.
LibreCat: https://research-explorer.ista.ac.at/record/2913
DOI: 10.1103/PhysRevLett.110.058104

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.
LibreCat: https://research-explorer.ista.ac.at/record/3261
DOI: 10.1073/pnas.1315642110
PMID: 24089448

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.
LibreCat: https://research-explorer.ista.ac.at/record/499
DOI: 10.1126/science.1229858

K. Simmons et al., “Transformation of stimulus correlations by the retina,” PLoS Computational Biology, vol. 9, no. 12. Public Library of Science, 2013.
LibreCat: https://research-explorer.ista.ac.at/record/2277
DOI: 10.1371/journal.pcbi.1003344

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.
LibreCat: https://research-explorer.ista.ac.at/record/2914
DOI: 10.1103/PhysRevLett.110.018701
arXiv: 0806.2694

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.
LibreCat: https://research-explorer.ista.ac.at/record/3262
DOI: 10.1103/PhysRevE.85.041903

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.
LibreCat: https://research-explorer.ista.ac.at/record/3274
DOI: 10.1016/j.enganabound.2011.12.014

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.
LibreCat: https://research-explorer.ista.ac.at/record/3374
DOI: 10.1088/0953-8984/23/15/153102

G. Tkadik et al., “Natural images from the birthplace of the human eye,” PLoS One, vol. 6, no. 6. Public Library of Science, 2011.
LibreCat: https://research-explorer.ista.ac.at/record/3384
DOI: 10.1371/journal.pone.0020409