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