Syntenic global alignment and its application to the gene prediction problem

Given the increasing number of available genomic sequences, one now faces the task of identifying their protein coding regions. The gene prediction problem can be addressed in several ways, and one of the most promising methods makes use of information derived from the comparison of homologous sequences. In this work, we develop a new comparative-based gene prediction program, called Exon_Finder2. This tool is based on a new type of alignment we propose, called syntenic global alignment, that can deal satisfactorily with sequences that share regions with different rates of conservation. In addition to this new type of alignment itself, we also describe a dynamic programming algorithm that computes a best syntenic global alignment of two sequences, as well as its related score. The applicability of our approach was validated by the promising initial results achieved by Exon_Finder2. On a benchmark including 120 pairs of human and mouse genomic sequences, most of their encoded genes were successfully identified by our program.

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