Bioinformatics techniques for comparative genomic analysis

Comparative genomic analysis is hindered by the ability to identify conserved regions, variations in evolution, and functional differences in the genome in large and heterogeneous sequence datasets.In this work, an integrated bioinformatics solution for the systematic genome comparison using BLAST sequence alignment, Multiple Sequence Alignment (MSA) detection of SNPs, phylogenetic analysis and gene annotation is proposed.Pre-processing, alignment, annotation and evaluation of genomic sequences were performed by applying sequence identity, alignment coverage, variant detection rate, computational time and classification accuracy as criteria for analysis.The proposed approach yielded a sequence-matching accuracy of 96.4%, alignment coverage of 94.8% and variant-detection accuracy of 93.7% with overall analytical accuracy of about 5.6% higher than conventional alignment-based analysis.Comparative evaluation showed better results in terms of sensitivity, specificity, computational efficiency and evolutionary relationship identification.It's novel because it's a single analytical pipeline that combines complementary genomic approaches.This approach provides a scalable, accurate method to identify genomic similarities and differences and evolutionary relationships, aiding in the accurate comparative genomics and biological interpretation.