Candidate Gene Predictions: Bioinformatics Significance in Linkage Analysis

2015 International Journal of Science and Research (IJSR)  
The rationale behind this review article is based on the identification of candidate genes in linkage analysis by using insilico strategies. In recent development, it is noted that computational approaches are widely used to find out disease-causing genes. This is achieved by applying various greedy algorithms, which are constructed either on mathematical modeling, or computational search and alignment methods, or both. The advantage of computer-assisted techniques is that, it reduces the
more » ... domain of diseasecausing genes which may comprise of 100 to 1000's candidate genes mapped on a single locus. In this context, the common criterion for in-silico candidate-gene identification relies on gene ontology, protein-protein interaction, sequence based features, functional annotation, data mining, and microarray-expression data. In addition to improve the disease-causing genes identification, development of disease-predicting software by incorporating existing data (wet-lab) will be a straightforward and effective step.
doi:10.21275/v4i11.sub15940 fatcat:bafcil632vhgvg75rftlvijqhi