Reverse Engineering Gene Networks Using Singular Value Decomposition and Robust Regression

We propose a scheme to reverse-engineer gene networks on a genome-wide scale using a relatively small amount of gene expression data from microarray experiments. Our method is based on the empirical observation that such networks are typically large and sparse. It uses singular value decomposition t...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 99; no. 9; pp. 6163 - 6168
Main Authors M. K. Stephen Yeung, Tegnér, Jesper, Collins, James J.
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 30.04.2002
National Acad Sciences
The National Academy of Sciences
Subjects
Algorithms
Architecture
Biological Sciences
Connectivity
Experimental data
Gene expression
Genes
Genetic engineering
Genomes
Genomics
Linear systems
Medicin och hälsovetenskap
Messenger RNA
Models, Genetic
Models, Statistical
Network topology
Oligonucleotide Array Sequence Analysis
Regression Analysis
Reproducibility of Results
Reverse engineering
Software
Statistics as Topic - methods
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Summary:We propose a scheme to reverse-engineer gene networks on a genome-wide scale using a relatively small amount of gene expression data from microarray experiments. Our method is based on the empirical observation that such networks are typically large and sparse. It uses singular value decomposition to construct a family of candidate solutions and then uses robust regression to identify the solution with the smallest number of connections as the most likely solution. Our algorithm has O(log N) sampling complexity and O(N4) computational complexity. We test and validate our approach in a series of in numero experiments on model gene networks.
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Present address: Stockholm Bioinformatic Center, SCFAB, S-10691 Stockholm, and Department of Numerical Analysis and Computer Science, Royal Institute of Technology, S-10044 Stockholm, Sweden.
Edited by Charles S. Peskin, New York University, Hartsdale, NY, and approved March 13, 2002
To whom reprint requests should be addressed at: Center for BioDynamics and Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215. E-mail: jcollins@bu.edu.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.092576199