Campus Units

Electrical and Computer Engineering, Genetics, Development and Cell Biology, Statistics

Document Type

Article

Publication Version

Published Version

Publication Date

1-1-2013

Journal or Book Title

Nucleic Acids Research

Volume

41

Issue

1

First Page

e24

DOI

10.1093/nar/gks904

Abstract

Reverse engineering the whole-genome networks of complex multicellular organisms continues to remain a challenge. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. To enable fast and accurate reconstruction of large networks, we developed Tool for Inferring Network of Genes (TINGe), a parallel mutual information (MI)-based program. The novel features of our approach include: (i) B-spline-based formulation for linear-time computation of MI, (ii) a novel algorithm for direct permutation testing and (iii) development of parallel algorithms to reduce run-time and facilitate construction of large networks. We assess the quality of our method by comparison with ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks) and GeneNet and demonstrate its unique capability by reverse engineering the whole-genome network of Arabidopsis thaliana from 3137 Affymetrix ATH1 GeneChips in just 9 min on a 1024-core cluster. We further report on the development of a new software Gene Network Analyzer (GeNA) for extracting context-specific subnetworks from a given set of seed genes. Using TINGe and GeNA, we performed analysis of 241 Arabidopsis AraCyc 8.0 pathways, and the results are made available through the web.

Comments

This article is published as Aluru, Maneesha, Jaroslaw Zola, Dan Nettleton, and Srinivas Aluru. "Reverse engineering and analysis of large genome-scale gene networks." Nucleic acids research 41, no. 1 (2012): e24. doi: 10.1093/nar/gks904.

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

Copyright Owner

The Authors

Language

en

File Format

application/pdf

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