TY - GEN
T1 - Utilizing cis-elements to refine gene regulatory networks
AU - Xiao, Yiou
AU - Mehrotra, Kishan
AU - Mohan, Chilukuri
AU - Raina, Ramesh
PY - 2013
Y1 - 2013
N2 - Gene regulatory networks (GRNs) describe epistatic relationship of genes and how the expression of some genes influence the expression of other genes. This information is critical for understanding molecular mechanisms regulating various biological processes and molecular basis of several diseases. Current research work mostly attempts to infer such regulatory relationships (and GRN architecture topology) from gene expression data. This paper improves on this methodology by utilizing additional information available that describes which cis-elements are present in which genes, and at what locations. Using the underlying principle that target genes of a transcription factor should share the same binding site in their promoter regions, we propose a scoring method that facilitates the refinement of a candidate GRN. Improvements are demonstrated with three data sets, on which GRNs are first obtained from existing dataset (AtRegNet) or using an existing approach (ARACNe), and then modified using cis-element information.
AB - Gene regulatory networks (GRNs) describe epistatic relationship of genes and how the expression of some genes influence the expression of other genes. This information is critical for understanding molecular mechanisms regulating various biological processes and molecular basis of several diseases. Current research work mostly attempts to infer such regulatory relationships (and GRN architecture topology) from gene expression data. This paper improves on this methodology by utilizing additional information available that describes which cis-elements are present in which genes, and at what locations. Using the underlying principle that target genes of a transcription factor should share the same binding site in their promoter regions, we propose a scoring method that facilitates the refinement of a candidate GRN. Improvements are demonstrated with three data sets, on which GRNs are first obtained from existing dataset (AtRegNet) or using an existing approach (ARACNe), and then modified using cis-element information.
KW - Cis-element
KW - Gene Regulatory Network
KW - Motif
KW - Transcription Factor
UR - http://www.scopus.com/inward/record.url?scp=84894595022&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84894595022&partnerID=8YFLogxK
U2 - 10.1109/BIBM.2013.6732737
DO - 10.1109/BIBM.2013.6732737
M3 - Conference contribution
AN - SCOPUS:84894595022
SN - 9781479913091
T3 - Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
SP - 65
EP - 71
BT - Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
T2 - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
Y2 - 18 December 2013 through 21 December 2013
ER -