دورية أكاديمية
أعرض في EDS

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

التفاصيل البيبلوغرافية
العنوان: Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.
المؤلفون: Sehgal V; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America., Seviour EG; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America., Moss TJ; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America., Mills GB; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America., Azencott R; Department of Mathematics, University of Houston, Houston, Texas, United States of America., Ram PT; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
المصدر: PloS one [PLoS One] 2015 Oct 27; Vol. 10 (10), pp. e0140072. Date of Electronic Publication: 2015 Oct 27 (Print Publication: 2015).
نوع المنشور: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
أسماء مطبوعة: Original Publication: San Francisco, CA : Public Library of Science
مواضيع طبية MeSH: Computational Biology*, Biomarkers, Tumor/*genetics , MicroRNAs/*genetics , Neoplasms/*genetics, Algorithms ; Biomarkers, Tumor/biosynthesis ; Gene Expression Regulation, Neoplastic ; Humans ; MicroRNAs/biosynthesis ; RNA, Messenger/biosynthesis
مستخلص: MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.
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معلومات مُعتمدة: T15 LM007093 United States LM NLM NIH HHS; U54 CA112970 United States CA NCI NIH HHS; U54-CA112970 United States CA NCI NIH HHS; T15LM007093 United States LM NLM NIH HHS
المشرفين على المادة: 0 (Biomarkers, Tumor)
0 (MicroRNAs)
0 (RNA, Messenger)
تواريخ الأحداث: Date Created: 20151028 Date Completed: 20160608 Latest Revision: 20201215
رمز التحديث: 20240628
مُعرف محوري في PubMed: PMC4623517
DOI: 10.1371/journal.pone.0140072
PMID: 26505200
قاعدة البيانات: MEDLINE
الوصف
تدمد:1932-6203
DOI:10.1371/journal.pone.0140072