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. 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

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