Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics
D. De Martino,  Physical Review E Statistical Nonlinear and Soft Matter Physics  95 (2017) 062419.

Quantifying the entropic cost of cellular growth control
D. De Martino, F. Capuani, A. De Martino,  Physical Review E Statistical Nonlinear and Soft Matter Physics  96 (2017).

Decoding of position in the developing neural tube from antiparallel morphogen gradients
M.P. Zagórski, Y. Tabata, N. Brandenberg, M. Lutolf, G. Tkadik, T. Bollenbach, J. Briscoe, A. Kicheva, Science 356 (2017) 1379–1383.

Phase transitions in integer linear problems
S. Colabrese, D. De Martino, L. Leuzzi, E. Marinari,  Journal of Statistical Mechanics: Theory and Experiment 2017 (2017).

Maximum entropy models as a tool for building precise neural controls
C. Savin, G. Tkadik, Current Opinion in Neurobiology 46 (2017) 120–126.

Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes
D. De Martino, Physical Review E 96 (2017).

Zeros of nonlinear systems with input invariances
M. Lang, E. Sontag, Automatica 81C (2017) 46–55.

Multi-electrode array recording from salamander retinal ganglion cells
O. Marre, G. Tkadik, D. Amodei, E. Schneidman, W. Bialek, M. Berry, (2017).

Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity
T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild, G. Tkadik, C.C. Guet, (2017).

Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity
T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild, G. Tkadik, C.C. Guet, Science 356 (2017) 311–315.

An effective feedback loop between cell-cell contact duration and morphogen signaling determines cell fate
V. Barone, M. Lang, G. Krens, S. Pradhan, S. Shamipour, K. Sako, M.K. Sikora, C.C. Guet, C.-P.J. Heisenberg, Developmental Cell 43 (2017) 198–211.

Relevant sparse codes with variational information bottleneck
M.J. Chalk, O. Marre, G. Tkadik, in:, Neural Information Processing Systems, 2016, pp. 1965–1973.

Estimating nonlinear neural response functions using GP priors and Kronecker methods
C. Savin, G. Tkadik, in:, Neural Information Processing Systems, 2016, pp. 3610–3618.

Modular parameter identification of biomolecular networks
M. Lang, J. Stelling, SIAM Journal on Scientific Computing 38 (2016) 8–08.

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.
G. Tkadik, Physics of Life Reviews 17 (2016) 166–167.

Asymptotic analysis of noisy fitness maximization, applied to metabolism &amp; growth
D. De Martino, D. Masoero,  Journal of Statistical Mechanics: Theory and Experiment 2016 (2016).

Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination
F. Hu, L. Rishishwar, A. Sivadas, G. Mitchell, J. King, T. Murphy, J. Gilsdorf, L. Mayer, X. Wang, Journal of Clinical Microbiology 54 (2016) 3010–3017.

Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm
G.S. Martius, R. Hostettler, A. Knoll, R. Der, in:, IEEE, 2016.

Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency
G. Miki, A. Stoll, J. Bevirt, R. Grah, M. Moore, in:, AIAA, 2016, pp. 1–19.

Extending the dynamic range of transcription factor action by translational regulation
T.R. Sokolowski, A. Walczak, W. Bialek, G. Tkadik, Physical Review E Statistical Nonlinear and Soft Matter Physics 93 (2016).