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193 Publications

2016 | Published | Journal Article | IST-REx-ID: 1242 | OA
Sokolowski, T. R., Walczak, A., Bialek, W., & Tkačik, G. (2016). Extending the dynamic range of transcription factor action by translational regulation. Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.93.022404
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2016 | Research Data Reference | IST-REx-ID: 9870
Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Computation of positional information in an Ising model. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s002
[Published Version] View | Files available | DOI
 
2016 | Research Data Reference | IST-REx-ID: 9869
Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Error bound on an estimator of position. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s001
[Published Version] View | Files available | DOI
 
2016 | Research Data Reference | IST-REx-ID: 9871
Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Computation of positional information in a discrete morphogen field. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s003
[Published Version] View | Files available | DOI
 
2016 | Published | Journal Article | IST-REx-ID: 1394 | OA
De Martino, D., Capuani, F., & De Martino, A. (2016). Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. IOP Publishing. https://doi.org/10.1088/1478-3975/13/3/036005
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2016 | Published | Journal Article | IST-REx-ID: 1188 | OA
De Martino, D., & Masoero, D. (2016). Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth. Journal of Statistical Mechanics: Theory and Experiment. IOP Publishing. https://doi.org/10.1088/1742-5468/aa4e8f
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2016 | Published | Conference Paper | IST-REx-ID: 1105
Savin, Cristina, Estimating nonlinear neural response functions using GP priors and Kronecker methods. 29. 2016
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2016 | Published | Conference Paper | IST-REx-ID: 948
Monk, Travis, Neurons equipped with intrinsic plasticity learn stimulus intensity statistics. 29. 2016
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2016 | Published | Journal Article | IST-REx-ID: 1485 | OA
De Martino, Daniele, Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology 13 (1). 2016
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2016 | Published | Conference Paper | IST-REx-ID: 8094 | OA
Martius, Georg S, Self-organized control of an tendon driven arm by differential extrinsic plasticity. 15th International Conference on the Synthesis and Simulation of Living Systems 28. 2016
[Published Version] View | Files available | DOI
 
2016 | Published | Conference Paper | IST-REx-ID: 1320
Lang, M., & Sontag, E. (2016). Scale-invariant systems realize nonlinear differential operators (Vol. 2016–July). Presented at the ACC: American Control Conference, Boston, MA, USA: IEEE. https://doi.org/10.1109/ACC.2016.7526722
[Preprint] View | Files available | DOI
 
2016 | Published | Journal Article | IST-REx-ID: 1420 | OA
Bodova, K., Tkačik, G., & Barton, N. H. (2016). A general approximation for the dynamics of quantitative traits. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.115.184127
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2016 | Published | Journal Article | IST-REx-ID: 1358 | OA
Friedlander, T., Prizak, R., Guet, C. C., Barton, N. H., & Tkačik, G. (2016). Intrinsic limits to gene regulation by global crosstalk. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms12307
[Published Version] View | Files available | DOI
 
2016 | Published | Journal Article | IST-REx-ID: 1148
Schilling, C., Bogomolov, S., Henzinger, T. A., Podelski, A., & Ruess, J. (2016). Adaptive moment closure for parameter inference of biochemical reaction networks. Biosystems. Elsevier. https://doi.org/10.1016/j.biosystems.2016.07.005
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2016 | Published | Journal Article | IST-REx-ID: 1197 | OA
Prentice, J., Marre, O., Ioffe, M., Loback, A., Tkačik, G., & Berry, M. (2016). Error-robust modes of the retinal population code. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005148
[Published Version] View | Files available | DOI
 
2016 | Published | Journal Article | IST-REx-ID: 1248 | OA
Tkačik, G., & Bialek, W. (2016). Information processing in living systems. Annual Review of Condensed Matter Physics. Annual Reviews. https://doi.org/10.1146/annurev-conmatphys-031214-014803
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2016 | Published | Conference Paper | IST-REx-ID: 1082 | OA
Chalk, M. J., Marre, O., & Tkačik, G. (2016). Relevant sparse codes with variational information bottleneck (Vol. 29, pp. 1965–1973). Presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain: Neural Information Processing Systems Foundation.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2015 | Published | Journal Article | IST-REx-ID: 1861
Ruess, J., & Lygeros, J. (2015). Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks. ACM Transactions on Modeling and Computer Simulation. ACM. https://doi.org/10.1145/2688906
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2015 | Published | Journal Article | IST-REx-ID: 1885 | OA
Tkačik, G., Dubuis, J., Petkova, M., & Gregor, T. (2015). Positional information, positional error, and readout precision in morphogenesis: A mathematical framework. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.114.171850
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2015 | Published | Journal Article | IST-REx-ID: 1940 | OA
Sokolowski, T. R., & Tkačik, G. (2015). Optimizing information flow in small genetic networks. IV. Spatial coupling. Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.91.062710
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