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MicroRNA prediction with a novel ranking algorithm based on random walks

By Yunpen Xu, Xuefeng Zhou and Weixiong Zhang

Abstract

MicroRNA (miRNAs) play essential roles in post-transcriptional gene regulation in animals and plants. Several existing computational approaches have been developed to complement experimental methods in discovery of miRNAs that express restrictively in specific environmental conditions or cell types. These computational methods require a sufficient number of characterized miRNAs as training samples, and rely on genome annotation to reduce the number of predicted putative miRNAs. However, most sequenced genomes have not been well annotated and many of them have a very few experimentally characterized miRNAs. As a result, the existing methods are not effective or even feasible for identifying miRNAs in these genomes

Topics: Ismb 2008 Conference Proceedings 19–23 July 2008, Toronto
Publisher: Oxford University Press
OAI identifier: oai:pubmedcentral.nih.gov:2718653
Provided by: PubMed Central

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