Multivariate dependence and genetic networks inference

Adam Margolin, K. Wang, A. Califano, I. Nemenman

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

A critical task in systems biology is the identification of genes that interact to control cellular processes by transcriptional activation of a set of target genes. Many methods have been developed that use statistical correlations in high-throughput data sets to infer such interactions. Howevercellular pathways are highly cooperativeoften requiring the joint effect of many molecules. Few methods have been proposed to explicitly identify such higher-order interactionspartially due to the fact that the notion of multivariate statistical dependence itself remains imprecisely defined. The authors define the concept of dependence among multiple variables using maximum entropy techniques and introduce computational tests for their identification. Synthetic network results reveal that this procedure uncovers dependencies even in undersampled regimeswhen the joint probability distribution cannot be reliably estimated. Analysis of microarray data from human B cells reveals that third-order statisticsbut not second-order onesuncover relationships between genes that interact in a pathway to cooperatively regulate a common set of targets.

Original languageEnglish (US)
Pages (from-to)428-440
Number of pages13
JournalIET Systems Biology
Volume4
Issue number6
DOIs
StatePublished - Nov 2010
Externally publishedYes

Fingerprint

Genetic Network
Genes
Gene
Pathway
Target
Systems Biology
B Cells
Entropy
Maximum Entropy
Microarray Analysis
Microarrays
Microarray Data
Joint Distribution
Probability distributions
Transcriptional Activation
High Throughput
Activation
B-Lymphocytes
Probability Distribution
Chemical activation

ASJC Scopus subject areas

  • Biotechnology
  • Cell Biology
  • Genetics
  • Molecular Biology
  • Modeling and Simulation

Cite this

Multivariate dependence and genetic networks inference. / Margolin, Adam; Wang, K.; Califano, A.; Nemenman, I.

In: IET Systems Biology, Vol. 4, No. 6, 11.2010, p. 428-440.

Research output: Contribution to journalArticle

Margolin, Adam ; Wang, K. ; Califano, A. ; Nemenman, I. / Multivariate dependence and genetic networks inference. In: IET Systems Biology. 2010 ; Vol. 4, No. 6. pp. 428-440.
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