Adaptive moment closure for parameter inference of biochemical reaction networks
C. Schilling, S. Bogomolov, T.A. Henzinger, A. Podelski, J. Ruess, Biosystems 149 (2016) 15–25.

A study of rigorous ODE integrators for multi scale set oriented computations
T. Miyaji, P. Pilarczyk, M. Gameiro, H. Kokubu, K. Mischaikow, Applied Numerical Mathematics 107 (2016) 34–47.

A Radical Break Restraining Neutrophil Migration
J. Renkawitz, M.K. Sixt, Developmental Cell 38 (2016) 448–450.

A noncanonical auxin sensing mechanism is required for organ morphogenesis in arabidopsis
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A model of differential growth guided apical hook formation in plants
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A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients
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Facets of the r-stable (n, k)-hypersimplex
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Tracy-widom distribution for the largest eigenvalue of real sample covariance matrices with general population
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The Ly;1 luminosity function at z= 5.7–6.6 and the steep drop of the faint end: Implications for reionization
S. Santos, D. Sobral, J.J. Matthee, Monthly Notices of the Royal Astronomical Society 463 (2016) 1678–1691.

The Fundamental Plane of star formation in galaxies revealed by the EAGLE hydrodynamical simulations
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The most luminous H ;1 emitters at z c 0.8–2.23 from HiZELS: Evolution of AGN and star-forming galaxies
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The CALYMHA survey: Ly;1 escape fraction and its dependence on galaxy properties at z = 2.23
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Shedding light on the grey zone of speciation along a continuum of genomic divergence
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Hanani-Tutte for radial planarity II
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C-planarity of embedded cyclic c-graphs
R. Fulek, in:, Springer, 2016, pp. 94–106.

A symbolic SAT based algorithm for almost sure reachability with small strategies in pomdps
K. Chatterjee, M. Chmelik, J. Davies, in:, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, AAAI Press, 2016, pp. 3225–3232.

Beyond the hypercube evolutionary accessibility of fitness landscapes with realistic mutational networks
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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.

Nonequilibrium description of de novo biogenesis and transport through Golgi-like cisternae
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