Encoding and Decoding Cellular Information through Signaling Dynamics

By Jeremy E. Purvis, Galit Lahav. Cell, 2013

784 citations recorded by the source corpus.

A growing number of studies are revealing that cells can send and receive information by controlling the temporal behavior (dynamics) of their signaling molecules. In this review, we discuss what is known about the dynamics of various signaling networks and their role in controlling cellular responses. We identify general principles that are emerging in the field, focusing specifically on how the identity and quantity of a stimulus is encoded in temporal patterns, how signaling dynamics influence cellular outcomes and how specific dynamical patterns are both shaped and interpreted by the structure of molecular networks. We conclude by discussing potential functional roles for transmitting cellular information through signaling dynamics and possible applications for the treatment of disease.

Subfields: Biophysics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0f003a7e3feae9962245a06c2b15308927d24700

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Citations in the corpus

Single-Cell and Single-Molecule Analysis of Gene Expression Regulation (2016, background): “In addition to concentration, TFs such as ERK, p53, or NF-κB can transfer information through changes in localization rather than global concentration (25, 36, 109, 118).”
Inferring Biological Networks by Sparse Identification of Nonlinear Dynamics (2016, background): “Understanding the network structure and the time-dependent dynamic behavior of the signaling molecules can potentially improve our ability to design such interventions [8], [9].”
Deep learning for cellular image analysis (2019, background): “Although object tracking can be challenging, successful solutions have made it useful in a variety of biological analyses, including quantification of signaling dynamics 109 , efforts to understand cell motility 110 , and attempts to unravel the laws of bacterial cell growth 111 .”