Authors: Wei Chen Hao Lin Pengmian Feng Jinpeng Wang
Publish Date: 2014/09/11
Volume: 6, Issue: 3, Pages: 241-249
Abstract
Alternative splicing is a tissue and developmental stage specific process and greatly increases the biodiversity of proteins Besides the trans and cisfactors on the genome level the process of RNA splicing is also regulated by epigenetic factors In the present work we proposed a new method to predict exon skipping events by using the histone methylation and acetylation information The maximum relevance minimum redundancy method followed by incremental feature selection was performed to select the optimal feature set Based on the optimized features our method obtained an overall accuracy of 685 in a 10fold cross validation test for exon skipping event prediction It is anticipated that our method may become a useful tool for alternative splicing events prediction and the selected optimal features will provide insights into the regulatory mechanisms of epigenetic factors in alternative splicing
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