Format

Send to

Choose Destination
Cell. 2011 Mar 18;144(6):864-73. doi: 10.1016/j.cell.2011.03.001.

Principles and strategies for developing network models in cancer.

Author information

1
Department of Biological Sciences, Columbia University, 1212 Amsterdam Avenue, New York, NY 10027, USA. dpeer@biology.columbia.edu

Abstract

The flood of genome-wide data generated by high-throughput technologies currently provides biologists with an unprecedented opportunity: to manipulate, query, and reconstruct functional molecular networks of cells. Here, we outline three underlying principles and six strategies to infer network models from genomic data. Then, using cancer as an example, we describe experimental and computational approaches to infer "differential" networks that can identify genes and processes driving disease phenotypes. In conclusion, we discuss how a network-level understanding of cancer can be used to predict drug response and guide therapeutics.

PMID:
21414479
PMCID:
PMC3082135
DOI:
10.1016/j.cell.2011.03.001
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center