Prediction and validation of the distinct dynamics of transient and sustained ERK activation

By S. Sasagawa, Yu‐ichi Ozaki, Kazuhiro A. Fujita, Shinya Kuroda. Nature Cell Biology, 2005

475 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/fcdad5f1bff9567dba95a080790737079a3c8dd2

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A methodology for the structural and functional analysis of signaling and regulatory networks (2006, background): “Ordinary differential equations relying on kinetic descriptions of the underlying molecular interactions are arguably the most used approach for modeling signaling networks (e.g. [3-6]).”
Cell-signalling dynamics in time and space (2006, methodology): “Since the 1990s, modelling has emerged as a novel tool to handle the rapidly growing information on the molecular-parts list and the overwhelmingly complex interaction circuitry of signalling networks 29–41 .”
Encoding and Decoding Cellular Information through Signaling Dynamics (2013, unknown): “In addition, NGF, but not EGF, signaling continues after receptor internalization, which contributes to the sustained activation of ERK (Sasagawa et al., 2005).”
Input–output behavior of ErbB signaling pathways as revealed by a mass action model trained against dynamic data (2009, methodology): “…et al , 1999; Hatakeyama, 2003; Resat et al , 2003; Hendriks, 2005; Sasagawa et al , 2005; Birtwistle et al , 2007), ours is more extensive in including all four receptors and two ligand classes, although nonetheless retaining the rigor of a mass action formulation based on elementary reactions.”
Chapter 1. General introduction (2015, unknown): “…books Built by scientists, for scientists 12.2% 117,000 130M TOP 1%154 4,400 Chapter 1 General Introduction: Advances in Hepatic Surgery J.H.M.B. Stoot, R.J.S. Coelen, J.L.A. van Vugt and C.H.C. Dejong Additional information is available at the end of the chapter http://dx.doi.org/10.5772/54710”
Universally Sloppy Parameter Sensitivities in Systems Biology Models (2007, methodology): “, phosphorylation rates) [31, 32, 41], and adjust key parameters to qualitatively best fit the existing data [2, 37, 40].”
A Logical Model Provides Insights into T Cell Receptor Signaling (2007, background): “Dynamic models provide an optimal basis for a detailed study of cellular networks and have been applied successfully to cellular networks of moderate size [2–5].”