Identifying CpG Islands in Genome Using Conditional Random Fields

摘要

This paper presents a novel method for CpG islands location identification based on conditional random fields (CRF) model. The method transforms CpG islands location identification into the problem of sequential data labeling. Based on the nature of CpG islands location, we design the methods of model constructing, training and decoding in CRF accordingly. Experimental results on benchmark data sets show that our algorithm is more practicable and efficient than the traditional methods.