TY - GEN
T1 - Dynamic identification and visualization of gene regulatory networks from time-series gene expression profiles
AU - Chen, Yu
AU - Han, Kyungsook
PY - 2009
Y1 - 2009
N2 - Recent improvements in high-throughput proteomics technology have produced a large amount of time-series gene expression data. The data provide a good resource to uncover causal gene-gene or gene-phenotype relationships and to characterize the dynamic properties of the underlying molecular networks for various biological processes. Several methods have been developed for identifying the molecular mechanisms of regulation of genes from the data, but many of the methods consider static gene expression profiles only. This paper presents a new method for identifying gene regulations from the time-series gene expression data and for visualizing the gene regulations as dynamic gene regulatory networks. The method has been implemented as a program called DRN Builder (Dynamic Regulatory Network Builder; http://wilab.inha.ac.kr/drnbuilder/ ) and successfully tested on actual gene expression profiles. DRN Builder will be useful for generating potential gene regulatory networks from a large amount of time-series gene expression data and for analyzing the identified networks.
AB - Recent improvements in high-throughput proteomics technology have produced a large amount of time-series gene expression data. The data provide a good resource to uncover causal gene-gene or gene-phenotype relationships and to characterize the dynamic properties of the underlying molecular networks for various biological processes. Several methods have been developed for identifying the molecular mechanisms of regulation of genes from the data, but many of the methods consider static gene expression profiles only. This paper presents a new method for identifying gene regulations from the time-series gene expression data and for visualizing the gene regulations as dynamic gene regulatory networks. The method has been implemented as a program called DRN Builder (Dynamic Regulatory Network Builder; http://wilab.inha.ac.kr/drnbuilder/ ) and successfully tested on actual gene expression profiles. DRN Builder will be useful for generating potential gene regulatory networks from a large amount of time-series gene expression data and for analyzing the identified networks.
UR - http://www.scopus.com/inward/record.url?scp=70350751283&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04070-2_8
DO - 10.1007/978-3-642-04070-2_8
M3 - Conference contribution
AN - SCOPUS:70350751283
SN - 3642040691
SN - 9783642040696
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 65
EP - 74
BT - Emerging Intelligent Computing Technology and Applications - 5th International Conference on Intelligent Computing, ICIC 2009, Proceedings
T2 - 5th International Conference on Intelligent Computing, ICIC 2009
Y2 - 16 September 2009 through 19 September 2009
ER -