Bioinformatics Approaches for Gene Finding

Gene finding as process of identification of genomic DNA regions encoding proteins , is one of the important scientific research programs and has vast application in structural genomics ,functional genomics ,metabolomics, transcriptomics, proteomics, genome studies and other genetic related studies including genetics disorders detection, treatment and prevention .It is prominent that for study of all above mentioned research programs , identification of fundamental and essential elements of genome such as functional genes, intron, exon, splicing sites, regulatory sites, gene encoding known proteins, motifs, EST, ACR, etc are formed principle basis of the studies and these functions are employed by gene prediction or finding process. So gene finding process plays significant role in the study of genome related programs. Several methods are available for gene finding such as laboratory -based approaches, feature- based approaches homology based approaches, statistical and HMM –based approaches. In this paper, we aim to discuss Insilco approaches for gene prediction in order to make scientist familiar with available bioinformatics tools for gene finding to take benefit from their advantages including low in cost, rapid in time, high in accuracy and large in scale.