TY - JOUR
T1 - Construction of gene networks with hybrid approach from expression profile and gene ontology
AU - Jing, Liping
AU - NG, Kwok Po
AU - Liu, Ying
N1 - Funding Information:
Manuscript received December 9, 2008; revised May 5, 2009. First published September 29, 2009; current version published January 15, 2010. This work was supported in part by the National Natural Science Foundation of China (90820013, 60875031, and 60905028), 973 project (2007CB311002), Program for New Century Excellent Talents in University (NCET-06-0078), Hong Kong Research Grants Council, and Hong Kong Baptist University Faculty Research Grants.
PY - 2010/1
Y1 - 2010/1
N2 - Gene regulatory networks have been long studied in model organisms as a means of identifying functional relationships among genes or their corresponding products. Despite many existing methods for genome-wide construction of such networks, solutions to the gene regulatory networks problem are however not trivial. Here, we present, a hybrid approach with gene expression profiles and gene ontology (HAEO). HAEO makes use of multimethods (overlapping clustering and reverse engineering methods) to effectively and efficiently construct gene regulatory networks from multisources (gene expression profiles and gene ontology). Application to yeast cell cycle dataset demonstrates HAEOs ability to construct validated gene regulatory networks, such as some potential gene regulatory pairs, which cannot be discovered by general inferring methods and identifying cycles (i.e., feedback loops) between genes. We also experimentally study the efficiency of building networks and show that the proposed method, HAEO is much faster than Bayesian networks method.
AB - Gene regulatory networks have been long studied in model organisms as a means of identifying functional relationships among genes or their corresponding products. Despite many existing methods for genome-wide construction of such networks, solutions to the gene regulatory networks problem are however not trivial. Here, we present, a hybrid approach with gene expression profiles and gene ontology (HAEO). HAEO makes use of multimethods (overlapping clustering and reverse engineering methods) to effectively and efficiently construct gene regulatory networks from multisources (gene expression profiles and gene ontology). Application to yeast cell cycle dataset demonstrates HAEOs ability to construct validated gene regulatory networks, such as some potential gene regulatory pairs, which cannot be discovered by general inferring methods and identifying cycles (i.e., feedback loops) between genes. We also experimentally study the efficiency of building networks and show that the proposed method, HAEO is much faster than Bayesian networks method.
KW - Bioinformatics
KW - Gene ontology (GO)
KW - Gene regulatory network
KW - Hybrid approach
KW - Overlapping clustering
UR - http://www.scopus.com/inward/record.url?scp=76849085464&partnerID=8YFLogxK
U2 - 10.1109/TITB.2009.2033056
DO - 10.1109/TITB.2009.2033056
M3 - Journal article
C2 - 19789116
AN - SCOPUS:76849085464
SN - 2168-2194
VL - 14
SP - 107
EP - 118
JO - IEEE Journal of Biomedical and Health Informatics
JF - IEEE Journal of Biomedical and Health Informatics
IS - 1
M1 - 5272346
ER -