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20062025
most citedOptimal Prediction by Cellular Signaling Networks

72 citations · 249 across the 12 of their papers we have counts for

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Showing q-bio.MNShow all

6 papers · 1 filter

q-bio.MN2017

eGFRD in all dimensions

Thomas R. Sokolowski, Joris Paijmans, Laurens Bossen +7

Biochemical reactions typically occur at low copy numbers, but at once in crowded and diverse environments. Space and stochasticity therefore play an essential role in biochemical…

q-bio.MN2015★ 72 cited

Optimal Prediction by Cellular Signaling Networks

Nils B. Becker, Andrew Mugler, Pieter Rein ten Wolde

Living cells can enhance their fitness by anticipating environmental change. We study how accurately linear signaling networks in cells can predict future signals. We find that max…

q-bio.MN2015★ 1 cited

Fundamental Limits to Cellular Sensing

Pieter Rein ten Wolde, Nils B. Becker, Thomas E. Ouldridge +1

In recent years experiments have demonstrated that living cells can measure low chemical concentrations with high precision, and much progress has been made in understanding what s…

q-bio.MN2013★ 6 cited

Prediction and Dissipation in Biochemical Sensing

Nils B. Becker, Andrew Mugler, Pieter Rein ten Wolde

Cells sense and predict their environment via energy-dissipating pathways. However, it is unclear whether dissipation helps or harms prediction. Here we study dissipation and predi…

q-bio.MN2012★ 12 cited

Rare switching events in non-stationary systems

Nils B. Becker, Pieter Rein ten Wolde

Physical systems with many degrees of freedom can often be understood in terms of transitions between a small number of metastable states. For time-homogeneous systems with short-t…

q-bio.MN2012★ 39 cited

Non-Stationary Forward Flux Sampling

Nils B. Becker, Rosalind J. Allen, Pieter Rein ten Wolde

We present a new method, Non-Stationary Forward Flux Sampling, that allows efficient simulation of rare events in both stationary and non-stationary stochastic systems. The method…