hARACNe: Improving the accuracy of regulatory model reverse engineering via higher-order data processing inequality tests

Sock Jang, Adam Margolin, Andrea Califano

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

A key goal of systems biology is to elucidate molecularmechanisms associated with physiologic and pathologic phenotypes based on the systematic and genome-wide understanding of cell context-specific molecular interaction models. To this end, reverse engineering approaches have been used to systematically dissect regulatory interactions in a specific tissue, based on the availability of large molecular profile datasets, thus improving our mechanistic understanding of complex diseases, such as cancer. In this paper, we introduce high-order Algorithm for the Reconstruction of Accurate Cellular Network (hARACNe), an extension of the ARACNe algorithm for the dissection of transcriptional regulatory networks. ARACNe uses the data processing inequality (DPI), from information theory, to detect and prune indirect interactions that are unlikely to be mediated by an actual physical interaction. Whereas ARACNe considers only first-order indirect interactions, i.e. those mediated by only one extra regulator, hARACNe considers a generalized form of indirect interactions via two, three or more other regulators. We show that use of higher-order DPI resulted in significantly improved performance, based on transcription factor (TF)-specific ChIP-chip data, as well as on gene expression profile following RNAi-mediated TF silencing.

Original languageEnglish (US)
JournalInterface Focus
Volume3
Issue number4
DOIs
StatePublished - Aug 6 2013
Externally publishedYes

Fingerprint

Reverse engineering
Transcription factors
Transcription Factors
Information Theory
Dissection
Molecular Models
Systems Biology
Molecular interactions
Gene Regulatory Networks
Information theory
RNA Interference
Transcriptome
Gene expression
Genes
Availability
Genome
Tissue
Phenotype
Neoplasms

Keywords

  • ARACNe
  • Higher-order data processing inequality
  • Information theory
  • Reverse engineering
  • Transcriptional regulatory network

ASJC Scopus subject areas

  • Biophysics
  • Biotechnology
  • Biochemistry
  • Bioengineering
  • Biomedical Engineering
  • Biomaterials

Cite this

hARACNe : Improving the accuracy of regulatory model reverse engineering via higher-order data processing inequality tests. / Jang, Sock; Margolin, Adam; Califano, Andrea.

In: Interface Focus, Vol. 3, No. 4, 06.08.2013.

Research output: Contribution to journalArticle

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