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BMC Syst Biol. 2010 Jun 15;4:84. doi: 10.1186/1752-0509-4-84.

Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets.

Author information

1
Department of Biological Chemistry, University of California, Irvine, 92697-1700, USA.

Abstract

BACKGROUND:

RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis.

RESULTS:

In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes.

CONCLUSIONS:

We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches.

PMID:
20550706
PMCID:
PMC2904735
DOI:
10.1186/1752-0509-4-84
[Indexed for MEDLINE]
Free PMC Article
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