De Martino, D., &; Masoero, D. (2016). Asymptotic analysis of noisy fitness maximization, applied to metabolism &;amp; growth. https://doi.org/10.1088/1742-5468/aa4e8f__Journal of Statistical Mechanics: Theory and Experiment. IOPscience.https://doi.org/10.1088/1742-5468/aa4e8f 

Hu, F., Rishishwar, L., Sivadas, A., Mitchell, G., King, J., Murphy, T.,https://doi.org/10.1128/JCM.01511-16__Wang, X. (2016). Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination. Journal of Clinical Microbiology. American Society for Microbiology.https://doi.org/10.1128/JCM.01511-16 

Martius, G. S., Hostettler, R., Knoll, A., &; Der, R. (2016). Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm (Vol. 2016–November). Presented at the IEEE RSJ International Conference on Intelligent Robots and Systems IROS , Daejeon, Korea: IEEE.https://doi.org/10.1109/IROS.2016.7759138 

Miki, G., Stoll, A., Bevirt, J., Grah, R., &; Moore, M. (2016). Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency (pp. 1–19). Presented at the AIAA: Aviation Technology, Integration, and Operations Conference, Washington, D.C., USA: AIAA.https://doi.org/10.2514/6.2016-3764 

Sokolowski, T. R., Walczak, A., Bialek, W., &; Tkadik, 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 

Recouvreux, P., Sokolowski, T. R., Grammoustianou, A., Tenwolde, P., &; Dogterom, M. (2016). Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells. PNAS. National Academy of Sciences.https://doi.org/10.1073/pnas.1419248113 

Tkadik, 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 

De Martino, D. (2016). The dual of the space of interactions in neural network models. International Journal of Modern Physics C. World Scientific Publishing.https://doi.org/10.1142/S0129183116500674 

Chalk, M. J., Gutkin, B., &; Denève, S. (2016). Neural oscillations as a signature of efficient coding in the presence of synaptic delays. ELife. eLife Sciences Publications.https://doi.org/10.7554/eLife.13824 

Stone, L., Baym, M., Lieberman, T., Chait, R. P., Clardy, J., &; Kishony, R. (2016). Compounds that select against the tetracycline-resistance efflux pump. Nature Chemical Biology. Nature Publishing Group.https://doi.org/10.1038/nchembio.2176 

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 

Chait, R. P., Palmer, A., Yelin, I., &; Kishony, R. (2016). Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments. Nature Communications. Nature Publishing Group.https://doi.org/10.1038/ncomms10333 

Baym, M., Lieberman, T., Kelsic, E., Chait, R. P., Gross, R., Yelin, I., &; Kishony, R. (2016). Spatiotemporal microbial evolution on antibiotic landscapes. Science. American Association for the Advancement of Science.https://doi.org/10.1126/science.aag0822 

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 Ltd.https://doi.org/10.1088/1478-3975/13/3/036005 

Bodova, K., Tkadik, 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 

De Martino, D. (2016). Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis. Physical Biology. IOP Publishing Ltd.https://doi.org/10.1088/1478-3975/13/1/016003 

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 

Martius, G. S., Hostettler, R., Knoll, A., &; Der, R. (2016). Self-organized control of an tendon driven arm by differential extrinsic plasticity. In Proceedings of the Artificial Life Conference 2016 (Vol. 28, pp. 142–143). Cancun, Mexico: MIT Press.https://doi.org/10.7551/978-0-262-33936-0-ch029 

Prentice, J., Marre, O., Ioffe, M., Loback, A., Tkadik, 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 

Monk, T., Savin, C., &; Lücke, J. (2016). Neurons equipped with intrinsic plasticity learn stimulus intensity statistics (Vol. 29, pp. 4285–4293). Presented at the NIPS: Neural Information Processing Systems, Barcelona, Spaine: Neural Information Processing Systems.