Genotype to phenotype via network analysis.
A prime objective of genomic medicine is the identification of disease-causing mutations and the mechanisms by which such events result in disease. As most disease phenotypes arise not from single genes and proteins but from a complex network of molecular interactions, a priori knowledge about the molecular network serves as a framework for biological inference and data mining. Here we review recent developments at the interface of biological networks and mutation analysis. We examine how mutations may be treated as a perturbation of the molecular interaction network and what insights may be gained from taking this perspective. We review work that aims to transform static networks into rich context-dependent networks and recent attempts to integrate non-coding RNAs into such analysis. Finally, we conclude with an overview of the many challenges and opportunities that lie ahead.
Institute for Genomic Medicine and Department of Medicine, University of California, San Diego, 9500 Gillman Drive, La Jolla, CA 92093, United States.
Hannah
H
Carter
Matan
M
Hofree
Trey
T
Ideker
D053263:Gene Regulatory Networks; D056726:Genetic Association Studies / Q000379:methods*; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D009154:Mutation; D010641:Phenotype