An approach to forecast human cancer by profiling microRNA expressions from NGS data

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• 作者：A. Salim ; R. Amjesh ; S. S. Vinod Chandra
• 关键词：MicroRNA ; Expression profiling ; Sequence mapping ; SVM classifiers
• 刊名：BMC Cancer
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：17
• 期：1
• 全文大小：1000KB
• 刊物主题：Cancer Research; Oncology; Surgical Oncology; Health Promotion and Disease Prevention; Biomedicine, general; Medicine/Public Health, general;
• 出版者：BioMed Central
• ISSN：1471-2407
• 卷排序：17

文摘

BackgroundmicroRNAs are single-stranded non-coding RNA sequences of 18 - 24 nucleotides in length. They play an important role in post-transcriptional regulation of gene expression. Evidences of microRNA acting as promoter/suppressor of several diseases including cancer are being unveiled. Recent studies have shown that microRNAs are differentially expressed in disease states when compared with that of normal states. Profiling of microRNA is a good measure to estimate the differences in expression levels, which can be further utilized to understand the progression of any associated disease.