Automatically clustering large-scale miRNA sequences: methods and experiments

BMC Genomics

Research

Jihong Guan¹  Jiandong Ding²  Linxia Wan²  Ting Jin²  Shuigeng Zhou³ 

[1] Department of Computer Science and Technology, Tongji Uinversity, 201804, Shanghai, China;School of Computer Science, Fudan University, 200433, Shanghai, China;School of Computer Science, Fudan University, 200433, Shanghai, China;Shanghai Key Lab of Intelligent Information Processing, Fudan University, 200433, Shanghai, China;

关键词: Feature Selection;    miRNA Family;    Mature miRNAs;    Cluster Number;    Latent Semantic Analysis;   

DOI  :  10.1186/1471-2164-13-S8-S15

来源: Springer

【 摘 要 】

BackgroundSince the initial annotation of microRNAs (miRNAs) in 2001, many studies have sought to identify additional miRNAs experimentally or computationally in various species. MiRNAs act with the Argonaut family of proteins to regulate target messenger RNAs (mRNAs) post-transcriptionally. Currently, researches mainly focus on single miRNA function study. Considering that members in the same miRNA family might participate in the same pathway or regulate the same target(s) and thus share similar biological functions, people can explore useful knowledge from high quality miRNA family architecture.ResultsIn this article, we developed an unsupervised clustering-based method miRCluster to automatically group miRNAs. In order to evaluate this method, several data sets were constructed from the online database miRBase. Results showed that miRCluster can efficiently arrange miRNAs (e.g identify 354 families in miRBase16 with an accuracy of 92.08%, and can recognize 9 of all 10 newly-added families in miRBase 17). By far, ~30% mature miRNAs registered in miRBase are unclassified. With miRCluster, over 85% unclassified miRNAs can be assigned to certain families, while ~44% of these miRNAs distributed in ~300novel families.ConclusionsIn short, miRCluster is an automatic and efficient miRNA family identification method, which does not require any prior knowledge. It can be helpful in real use, especially when exploring functions of novel miRNAs. All relevant materials could be freely accessed online (http://admis.fudan.edu.cn/projects/miRCluster).

【 授权许可】

Unknown   
© Wan et al.; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.