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Reverse Engineering and Analysis of Genome-Wide Gene Regulatory Networks from Gene Expression Profiles Using High-Performance Computing
May-June 2012 (vol. 9 no. 3)
pp. 668-678
ASCII Text
x 
 
G. Oliva, Diego di Bernardo, G. D'Angelo, M. Santoro, V. Siciliano, F. Gregoretti, V. Belcastro, "Reverse Engineering and Analysis of Genome-Wide Gene Regulatory Networks from Gene Expression Profiles Using High-Performance Computing," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 3, pp. 668-678, May-June, 2012.
 
 
BibTex
x
 
@article{ 10.1109/TCBB.2011.60,
author = {G. Oliva and Diego di Bernardo and G. D'Angelo and M. Santoro and V. Siciliano and F. Gregoretti and V. Belcastro},
title = {Reverse Engineering and Analysis of Genome-Wide Gene Regulatory Networks from Gene Expression Profiles Using High-Performance Computing},
journal ={IEEE/ACM Transactions on Computational Biology and Bioinformatics},
volume = {9},
number = {3},
issn = {1545-5963},
year = {2012},
pages = {668-678},
doi = {http://doi.ieeecomputersociety.org/10.1109/TCBB.2011.60},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE/ACM Transactions on Computational Biology and Bioinformatics
TI - Reverse Engineering and Analysis of Genome-Wide Gene Regulatory Networks from Gene Expression Profiles Using High-Performance Computing
IS - 3
SN - 1545-5963
SP668
EP678
EPD - 668-678
A1 - G. Oliva,
A1 - Diego di Bernardo,
A1 - G. D'Angelo,
A1 - M. Santoro,
A1 - V. Siciliano,
A1 - F. Gregoretti,
A1 - V. Belcastro,
PY - 2012
KW - reverse engineering
KW - biology computing
KW - cellular biophysics
KW - genetics
KW - genomics
KW - liver
KW - molecular biophysics
KW - parallel algorithms
KW - proteins
KW - mitochondrial proteins
KW - genome-wide gene regulatory networks
KW - gene expression profiles
KW - high-performance computing
KW - mammalian cells
KW - parallel computing algorithm
KW - reverse-engineer genome-scale gene regulatory networks
KW - pairwise mutual information
KW - gene-pair
KW - Mus Musculus gene regulatory network
KW - liver
KW - public repository
KW - parallel hierarchical clustering algorithm
KW - network community
KW - biological functions
KW - Probes
KW - Gene expression
KW - Proteins
KW - Bioinformatics
KW - Mutual information
KW - Mice
KW - Joints
KW - parallel computing.
KW - Reverse engineering
KW - gene regulatory network
KW - clustering algorithm
VL - 9
JA - IEEE/ACM Transactions on Computational Biology and Bioinformatics
ER -
 
G. Oliva, Inst. of High Performance Comput. & Networking ICAR-CNR, Naples, Italy
Diego di Bernardo, Telethon Inst. of Genetics & Med. (TIGEM), Naples, Italy
G. D'Angelo, Telethon Inst. of Genetics & Med. (TIGEM), Naples, Italy
M. Santoro, Telethon Inst. of Genetics & Med. (TIGEM), Naples, Italy
V. Siciliano, Telethon Inst. of Genetics & Med. (TIGEM), Naples, Italy
F. Gregoretti, Inst. of High Performance Comput. & Networking ICAR-CNR, Naples, Italy
V. Belcastro, Telethon Inst. of Genetics & Med. (TIGEM), Naples, Italy
Regulation of gene expression is a carefully regulated phenomenon in the cell. "Reverse-engineering” algorithms try to reconstruct the regulatory interactions among genes from genome-scale measurements of gene expression profiles (microarrays). Mammalian cells express tens of thousands of genes; hence, hundreds of gene expression profiles are necessary in order to have acceptable statistical evidence of interactions between genes. As the number of profiles to be analyzed increases, so do computational costs and memory requirements. In this work, we designed and developed a parallel computing algorithm to reverse-engineer genome-scale gene regulatory networks from thousands of gene expression profiles. The algorithm is based on computing pairwise Mutual Information between each gene-pair. We successfully tested it to reverse engineer the Mus Musculus (mouse) gene regulatory network in liver from gene expression profiles collected from a public repository. A parallel hierarchical clustering algorithm was implemented to discover "communities” within the gene network. Network communities are enriched for genes involved in the same biological functions. The inferred network was used to identify two mitochondrial proteins.

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Index Terms:
reverse engineering,biology computing,cellular biophysics,genetics,genomics,liver,molecular biophysics,parallel algorithms,proteins,mitochondrial proteins,genome-wide gene regulatory networks,gene expression profiles,high-performance computing,mammalian cells,parallel computing algorithm,reverse-engineer genome-scale gene regulatory networks,pairwise mutual information,gene-pair,Mus Musculus gene regulatory network,liver,public repository,parallel hierarchical clustering algorithm,network community,biological functions,Probes,Gene expression,Proteins,Bioinformatics,Mutual information,Mice,Joints,parallel computing.,Reverse engineering,gene regulatory network,clustering algorithm
Citation:
G. Oliva, Diego di Bernardo, G. D'Angelo, M. Santoro, V. Siciliano, F. Gregoretti, V. Belcastro, "Reverse Engineering and Analysis of Genome-Wide Gene Regulatory Networks from Gene Expression Profiles Using High-Performance Computing," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 3, pp. 668-678, May-June 2012, doi:10.1109/TCBB.2011.60
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