Paper Info
Title
Combining Gene Expression And Interactions Data With Mirna Family Information For Identifying Mirna-Mrna Regulatory Modules
Abstract
It is well known that microRNAs (miRNAs) play pivotal roles in gene expression, transcriptional regulation and other important biological processes. An impressive body of literature indicates that miRNAs and mRNAs work cooperatively to form an important part of gene regulatory modules which are extensively involved in cancer. However, with the accumulation of available data, it is a great challenge to identify cancer-related miRNA regulatory modules and uncover their precise regulatory mechanism. This paper proposed a novel computational framework by combining gene expression and interaction data with miRNA family information to identify miRNA-mRNA regulatory modules (GIFMRM), which was evaluated on three heterogeneous datasets. Literature survey, biological significance and functional enrichment analysis were used to validate the obtained results. The analysis results show that the modules identified are highly correlated with the biological conditions in their respective datasets, and they enrich in GO biological processes and KEGG pathways.
Year
DOI
Venue
2017
10.1007/978-3-319-63312-1_28
INTELLIGENT COMPUTING THEORIES AND APPLICATION, ICIC 2017, PT II
Keywords
Field
DocType
miRNA-mRNA regulation modules, Gene expression, miRNA family
Transcriptional regulation,Gene,Computer science,microRNA,Gene expression,KEGG,Messenger RNA,Artificial intelligence,Computational biology,Bioinformatics,Machine learning
Conference
Volume
ISSN
Citations 
10362
0302-9743
0
PageRank 
References 
Authors
0.34
10
3
Name
Order
Citations
PageRank
Dan Luo143.17
Shulin Wang2277.13
Jianwen Fang314814.82