TY - JOUR
T1 - Efficiently finding regulatory elements using correlation with gene expression
AU - Bannai, Hideo
AU - Inenaga, Shunsuke
AU - Shinohara, Ayumi
AU - Takeda, Masayuki
AU - Miyano, Satoru
N1 - Funding Information:
The authors would like to acknowledge the anonymous referees for their helpful comments. This research was supported in part by Grant-in-Aid for Encouragement of Young Scientists (B), and Grant-in-Aid for Scientific Research on Priority Areas (C) “Genome Biology” from the Ministry of Education, Culture, Sports, Science and Technology of Japan.
PY - 2004/6
Y1 - 2004/6
N2 - We present an efficient algorithm for detecting putative regulatory elements in the upstream DNA sequences of genes, using gene expression information obtained from microarray experiments. Based on a generalized suffix tree, our algorithm looks for motif patterns whose appearance in the upstream region is most correlated with the expression levels of the genes. We are able to find the optimal pattern, in time linear in the total length of the upstream sequences. We implement and apply our algorithm to publicly available microarray gene expression data, and show that our method is able to discover biologically significant motifs, including various motifs which have been reported previously using the same data set. We further discuss applications for which the efficiency of the method is essential, as well as possible extensions to our algorithm.
AB - We present an efficient algorithm for detecting putative regulatory elements in the upstream DNA sequences of genes, using gene expression information obtained from microarray experiments. Based on a generalized suffix tree, our algorithm looks for motif patterns whose appearance in the upstream region is most correlated with the expression levels of the genes. We are able to find the optimal pattern, in time linear in the total length of the upstream sequences. We implement and apply our algorithm to publicly available microarray gene expression data, and show that our method is able to discover biologically significant motifs, including various motifs which have been reported previously using the same data set. We further discuss applications for which the efficiency of the method is essential, as well as possible extensions to our algorithm.
UR - https://www.scopus.com/pages/publications/4043181443
UR - https://www.scopus.com/pages/publications/4043181443#tab=citedBy
U2 - 10.1142/S0219720004000612
DO - 10.1142/S0219720004000612
M3 - Article
C2 - 15297982
AN - SCOPUS:4043181443
SN - 0219-7200
VL - 2
SP - 273
EP - 288
JO - Journal of bioinformatics and computational biology
JF - Journal of bioinformatics and computational biology
IS - 2
ER -