TY - GEN
T1 - Analysis microRNA-gene co-modules in glioblastoma multiforme based on integrative two types of genomic data
AU - Deng, Jin
AU - Kong, Wei
AU - Wang, Huimin
AU - Wang, Shuaiqun
AU - Mou, Xiaoyang
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/9/19
Y1 - 2018/9/19
N2 - Glioblastoma multiforme (GBM) is the most common primary central nervous system tumor. Although treatment continues to make progress in the past, the pathogenesis is still unknown to a large extent. MicroRNA (miRNA) is known to regulate cooperatively the expression of gene profiles in the post transcriptional stages and affect many crucial biological processes. The majority of the existing researches on GBM transcriptional regulation mechanism devoted to global analysis only on gene expression data, disregarding the complex coordination between miRNA and gene expression profiles. With the development of high throughput biotechnology and computational biology, it is possible to simulate and understand the regulatory role in cellular process by integrating gene expression profiles with miRNA data. In this article, we adopt the joint Non-negative Matrix Factorization Algorithm (JNMF) to integrate miRNA data and gene expression data to form co-modules. In addition, the characteristic co-modules and the number of miRNA related with GBM were identified by correlation analysis, thus constructing miRNA-gene regulation network to speculate the pathogenesis of GBM. The results demonstrated that the characteristic co-modules showed a significant biological correlation and potential association with GBM. Furthermore, GO biological processes and KEGG enrichment analysis further revealed the biological functions of miRNA targets gene in co-modules.
AB - Glioblastoma multiforme (GBM) is the most common primary central nervous system tumor. Although treatment continues to make progress in the past, the pathogenesis is still unknown to a large extent. MicroRNA (miRNA) is known to regulate cooperatively the expression of gene profiles in the post transcriptional stages and affect many crucial biological processes. The majority of the existing researches on GBM transcriptional regulation mechanism devoted to global analysis only on gene expression data, disregarding the complex coordination between miRNA and gene expression profiles. With the development of high throughput biotechnology and computational biology, it is possible to simulate and understand the regulatory role in cellular process by integrating gene expression profiles with miRNA data. In this article, we adopt the joint Non-negative Matrix Factorization Algorithm (JNMF) to integrate miRNA data and gene expression data to form co-modules. In addition, the characteristic co-modules and the number of miRNA related with GBM were identified by correlation analysis, thus constructing miRNA-gene regulation network to speculate the pathogenesis of GBM. The results demonstrated that the characteristic co-modules showed a significant biological correlation and potential association with GBM. Furthermore, GO biological processes and KEGG enrichment analysis further revealed the biological functions of miRNA targets gene in co-modules.
UR - http://www.scopus.com/inward/record.url?scp=85060042840&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060042840&partnerID=8YFLogxK
U2 - 10.1145/3278198.3278199
DO - 10.1145/3278198.3278199
M3 - Conference contribution
AN - SCOPUS:85060042840
T3 - ACM International Conference Proceeding Series
BT - 2018 2nd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2018
PB - Association for Computing Machinery
T2 - 2nd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2018
Y2 - 19 September 2018 through 21 September 2018
ER -