Genotype to phenotype via network analysis

Hannah Carter, Matan Hofree, Trey Ideker*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

93 Scopus citations

Abstract

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.

Original languageAmerican English
Pages (from-to)611-621
Number of pages11
JournalCurrent Opinion in Genetics and Development
Volume23
Issue number6
DOIs
StatePublished - Dec 2013
Externally publishedYes

Bibliographical note

Funding Information:
This work was supported by NIH Grants P41 GM103504 , R01 GM070743 and P50 GM085764 .

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