Analyzing the LncRNA, miRNA, and mRNA regulatory network in prostate cancer with bioinformatics software
Motivation: Information processing tools and bioinformatics software have significantly advanced researchers” ability to process and analyze biological data.Molecular data from human and model organism genomes, helps researchers identify topics for study, which in turn improves predictive accuracy, facilitates the identification of relevant genes, and simplifies the validation of laboratory data.The objective of this study was to explore the regulatory network constituted by long non-coding RNA (lncRNA), miRNA, and mRNA in prostate cancer.Results: Our study identified 57 differentially expressed miRNAs and 1252 differentially expressed mRNAs; of these, 691 were down-regulated genes primarily involved in focal adhesion, vascular smooth muscle contraction, calcium signaling pathway, and so on.The remaining 561 were up-regulated genes principally involved in systemic lupus erythematosus, progesterone-mediated oocyte maturation, oocyte meiosis, and so on.Through the integrated analysis of correlation and target gene prediction, our studies identified 1214 miRNA:mRNA pairs, including 52 miRNAs and 395 mRNAs, and screened out 455 lncRNA-miRNA pairs containing 52 miRNAs.Therefore, due to the interrelationship of lncRNAs and miRNAs with mRNAs, our study screened out 19,075 regulatory relations.
Yu-Guang Li Ze-Ping Han Mao-Xian Zhou Li Wang Yu Bing Lv Jia Bing Zhou Ming-Rong Cao Jin huahe
Department of Laboratory, Central Hospital of Panyu District, Guangzhou, Guangdong, 511400, China Department of General Surgery, First Affiliated Hospital, Jinan University, Guangzhou, Guangdong,510
国内会议
第九届粤桂琼检验医学学术会议暨海南省医学会检验医学专业委员会2015年学术年会
海南陵水
英文
41-48
2015-10-01（万方平台首次上网日期，不代表论文的发表时间）