Literature DB >> 17249498

Network genomics.

T E Ideker1.   

Abstract

Network genomics is an emerging area of bioengineering which models the influence of genes (hence, genomics) in the context of a larger biomolecular system or network. A biomolecular network is a comprehensive collection of molecules and molecular interactions that regulate cellular function. Molecular interactions include physical binding events between proteins and proteins, proteins and DNA, or proteins and drugs, as well as genetic relationships dictating how genes combine to cause particular phenotypes. Thinking about biological systems as networks goes hand-in-hand with our ability to experimentally measure and define biomolecular interactions at large scale. Once we have catalogued all of the interactions present in a network, we may begin to ask questions such as: How many different molecules are bound by a typical protein? What is the topological structure of the network? How are signals transmitted through the network in response to internal and external events? Which parts of the network are evolutionarily conserved across species, and which parts differ? Perhaps most importantly, we can begin to use the interaction network as a storehouse of information from which to extract and construct computer-based models of cellular processes and disease.

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Year:  2007        PMID: 17249498     DOI: 10.1007/978-3-540-31339-7_5

Source DB:  PubMed          Journal:  Ernst Schering Res Found Workshop        ISSN: 0947-6075


  4 in total

1.  SOX2 and CHD7 cooperatively regulate human disease genes.

Authors:  Janusz Puc; Michael G Rosenfeld
Journal:  Nat Genet       Date:  2011-06       Impact factor: 38.330

2.  Editorial: Network-Oriented Approaches to Anticancer Drug Response.

Authors:  Paola Lecca; Juan Manuel Corchado; Daniela Besozzi
Journal:  Front Bioeng Biotechnol       Date:  2021-05-24

3.  Biomolecular self-defense and futility of high-specificity therapeutic targeting.

Authors:  Simon Rosenfeld
Journal:  Gene Regul Syst Bio       Date:  2011-11-21

4.  Markov clustering versus affinity propagation for the partitioning of protein interaction graphs.

Authors:  James Vlasblom; Shoshana J Wodak
Journal:  BMC Bioinformatics       Date:  2009-03-30       Impact factor: 3.169

  4 in total

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