Comparative sequence analysis to identify functional elements for functional genomics

Comparative sequence analysis is a powerful approach to identify functional elements for functional genomics. For gene prediction, this would mean whether given genomic sequences exhibit significant similarity to some arbitrary region in the genome sequence of an evolutionary related organism or not. Three gene prediction methods were examined to see how they perform on randomly chosen sequences. The focus was on examining the methods rather than data analysis. Thus, the dataset was selected in a flexible manner and may be biased. Our analysis of methods indicated that there are not many differences between recent version of GENEMARK.HMM and GENSCAN in terms of the algorithm used. Both programs use duration HMM and can predict genes and exons on both DNA strands simultaneously. MZEF, on the other hand, uses completely different approach. It employs quadratic discriminant function to distinguish between coding and noncoding regions. The analysis showed that the new generation of programs has substantially better results than the programs analyzed in previous studies. Specifically, GENEMARK.HMM and GENSCAN performed relatively better than MZEF.