TAILIEUCHUNG - Báo cáo khoa học: "Prediction of viral microRNA precursors based on human microRNA precursor sequence and structural features"

Prediction of viral microRNA precursors based on human microRNA precursor sequence and structural features | Virology Journal BioMed Central Short report Prediction of viral microRNA precursors based on human microRNA precursor sequence and structural features Shiva Kumar Faraz A Ansari and Vinod Scaria Open Access Address GN Ramachandran Knowledge Center for Genome Informatics Institute of Genomics and Integrative Biology CSIR Mall Road Delhi 110 007 India Email Shiva Kumar - Faraz A Ansari - faraz@ Vinod Scaria - vinods@ Corresponding author Published 20 August 2009 Received 29 October 2008 Accepted 20 August 2009 Virology Journal 2009 6 129 doi 1743-422X-6-129 This article is available from http content 6 1 129 2009 Kumar et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract MicroRNAs small 22 nucleotide long non-coding endogenous RNAs have recently attracted immense attention as critical regulators of gene expression in multi-cellular eukaryotes especially in humans. Recent studies have proved that viruses also express microRNAs which are thought to contribute to the intricate mechanisms of host-pathogen interactions. Computational predictions have greatly accelerated the discovery of microRNAs. However most of these widely used tools are dependent on structural features and sequence conservation which limits their use in discovering novel virus expressed microRNAs and non-conserved eukaryotic microRNAs. In this work an efficient prediction method is developed based on the hypothesis that sequence and structure features which discriminate between host microRNA precursor hairpins and pseudo microRNAs are shared by viral microRNA as they depend on host machinery for the processing of microRNA precursors. The proposed method has been found to be more

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