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- Title
基于乒乓算法的复杂疾病标志物识别.
- Authors
吕鹏举; 沈继红; 郭爽; 蔡明霏; 陈宇格
- Abstract
Objective: Biomarkers are the biochemical indexes that indicate the changes or possible changes of systems, organs and tissues, which have very extensive clinical application. Based on the high-throughput data, it is very important to study the biomarkers of complex diseases using the computer aided method. In this study, we proposed a novel approach to identify biomarkers of complex diseases. Methods: The biomarkers of complex diseases were identified referring to 'omics' data through constructing the lnc RNA-mRNA interaction network based on Ping-Pong Algorithm. Then, a random walk algorithm was used to calculate the biomarkers of complex diseases and compare them with t-test results. Results: Using this method, lnc RNAs(CCAT1, MEG3, Snhg1, MALAT1, HOTAIR, UCA1,PVT1, CASC9, LOC100130476, TUG1, BC200, POU6 F2-AS2, TP73-AS1 and ZEB1-AS1)and mRNAs(SPARC, CMTM7, Sph K1,NANOG, LOXL2, HMGCS2, FZD7, PTOV1, CADM1, CTHRC1, MGMT and RECK)were identified as biomarkers of esophageal cancer, which were related to the occurrence and development of esophageal cancer. Compared with the other identification method(t-test),four new lnc RNAs(BC200, POU6 F2-AS2, TP73-AS1 and ZEB1-AS1) and three new mRNAs(CADM1, Sph K1 and RECK)were identified. Conclusions: This method was verified to be more effective to predict biomarkers related to the complex disease.
- Publication
Progress in Modern Biomedicine, 2018, Vol 18, Issue 9, p1780
- ISSN
1673-6273
- Publication type
Article
- DOI
10.13241/j.cnki.pmb.2018.09.039