Literature DB >> 14708118

Dynamical and integrative cell signaling: challenges for the new biology.

Andre Levchenko1.   

Abstract

Years of careful experimental analysis have revealed that signaling molecules are organized into complex networks of biochemical reactions exquisitely regulated in time and space to provide a cell with high-fidelity information about an extremely noisy and volatile environment. A new view of signaling networks as systems consisting of multiple complex elements interacting in a multifarious fashion is emerging, a view that conflicts with the single-gene or protein-centric approach common in biological research. The postgenomic era has brought about a different, network-centric methodology of analysis, suddenly forcing researchers toward the opposite extreme of complexity, where the networks being explored are, to a certain extent, intractable and uninterpretable. Both the cartoons of simple pathways and the very large "hair-ball" diagrams of large intracellular networks are also representations of static worlds, superficially devoid of dynamics and chemistry. These representations are often viewed as being analogous to stably linked computer and neural networks rather than dynamically changing networks of chemical interactions, where the notions of concentration, compartmentalization, and diffusion may be the primary determinants of connectivity. Arguably, the systems biology approach, relying on computational modeling coupled with various experimental techniques and methodologies, will be an essential component of analysis of the behavior of signal transduction pathways. Combining the dynamical view of rapidly evolving responses and the structural view arising from high-throughput analyses of the interacting species will be the best approach toward efforts toward greater understanding of intracellular signaling processes. Copyright 2003 Wiley Periodicals, Inc.

Mesh:

Year:  2003        PMID: 14708118     DOI: 10.1002/bit.10854

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  12 in total

Review 1.  Toward predictive models of mammalian cells.

Authors:  Avi Ma'ayan; Robert D Blitzer; Ravi Iyengar
Journal:  Annu Rev Biophys Biomol Struct       Date:  2005

Review 2.  From components to regulatory motifs in signalling networks.

Authors:  Avi Ma'ayan; Ravi Iyengar
Journal:  Brief Funct Genomic Proteomic       Date:  2006-02-20

Review 3.  Transmembrane helix-helix interactions involved in ErbB receptor signaling.

Authors:  Florian Cymer; Dirk Schneider
Journal:  Cell Adh Migr       Date:  2010-04-13       Impact factor: 3.405

4.  Filamentation Regulatory Pathways Control Adhesion-Dependent Surface Responses in Yeast.

Authors:  Jacky Chow; Izzy Starr; Sheida Jamalzadeh; Omar Muniz; Anuj Kumar; Omer Gokcumen; Denise M Ferkey; Paul J Cullen
Journal:  Genetics       Date:  2019-05-03       Impact factor: 4.562

5.  Computational modeling with forward and reverse engineering links signaling network and genomic regulatory responses: NF-kappaB signaling-induced gene expression responses in inflammation.

Authors:  Shih Chi Peng; David Shan Hill Wong; Kai Che Tung; Yan Yu Chen; Chun Cheih Chao; Chien Hua Peng; Yung Jen Chuang; Chuan Yi Tang
Journal:  BMC Bioinformatics       Date:  2010-06-08       Impact factor: 3.169

Review 6.  Kinetic modeling of biological systems.

Authors:  Haluk Resat; Linda Petzold; Michel F Pettigrew
Journal:  Methods Mol Biol       Date:  2009

7.  Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates.

Authors:  André Fujita; Luciana Rodrigues Gomes; João Ricardo Sato; Rui Yamaguchi; Carlos Eduardo Thomaz; Mari Cleide Sogayar; Satoru Miyano
Journal:  BMC Syst Biol       Date:  2008-12-05

8.  Robust and sensitive control of a quorum-sensing circuit by two interlocked feedback loops.

Authors:  Joshua W Williams; Xiaohui Cui; Andre Levchenko; Ann M Stevens
Journal:  Mol Syst Biol       Date:  2008-12-16       Impact factor: 11.429

9.  SNAVI: Desktop application for analysis and visualization of large-scale signaling networks.

Authors:  Avi Ma'ayan; Sherry L Jenkins; Ryan L Webb; Seth I Berger; Sudarshan P Purushothaman; Noura S Abul-Husn; Jeremy M Posner; Tony Flores; Ravi Iyengar
Journal:  BMC Syst Biol       Date:  2009-01-20

10.  Assessing cumulative health risks from exposure to environmental mixtures - three fundamental questions.

Authors:  Ken Sexton; Dale Hattis
Journal:  Environ Health Perspect       Date:  2007-01-24       Impact factor: 9.031

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.