Eliminating Target Anopheles Proteins to Non-Target Organisms based on Posterior Probability Algorithm

Adebiyi, Marion and Olugbara, Oludayo (2021) Eliminating Target Anopheles Proteins to Non-Target Organisms based on Posterior Probability Algorithm. Advances in Science, Technology and Engineering Systems Journal, 6 (1). pp. 710-718. ISSN 24156698

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Abstract

Capturing similarity in gene sequences of a target organism to detect significant regions of comparison will most likely occur because genes share a related descendant. Local sequence alignment for the targeted organisms can help preserve associations among sequences of related organisms. Such homologous genes possess identical sequences with common ancestral genes. The genes may be similar to common traits, and varying purposes, but they descend from a common ancestor. Basic local alignment search tool (BLAST) from the National Center for Biotechnology Information. (NCBI) has been used by different researchers to resolve the various forms of alignment problems. However, much literature to bare the efficacy of standard protein- protein BLAST (BLASTp) on the MATLAB platform has not been seen. In this study, a position- specific iteration BLASTp of 20 anopheles insecticide target protein sequence was performed on NCBI Ensembl against genomes of Anopheles (target organism), then against humans, fruit-fly, zebrafish, and chicken genomes (non-target organisms) to eliminate the targets with homology to non-target organisms. Furthermore, the same iteration was repeated for the genomes of Anopheles and non-target organisms using a posterior probability algorithm built into MATLAB as a tool for protein to protein search BLAST. Outputs from NCBI and MATLAB were put forward to determine the optimality of an optimized search algorithm on MATLAB. The MATLAB-Blastp method based on the application of posterior probability has helped to avoid errors occurring in the early stages of alignment. Moreover, the same results were obtained for the sought features on NCBI Blastp with a refined understanding of how feature values are generated from MATLAB posterior probability built-in algorithm for position-specific BLAST.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Depositing User:	Mr Uchechukwu F. Ekpendu
Date Deposited:	08 Jul 2021 15:29
Last Modified:	08 Jul 2021 15:29
URI:	https://eprints.lmu.edu.ng/id/eprint/3236

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