A Scalable Algorithm for Interpreting DNA Sequence and Predicting the Response of Killer T-Cells in Systemic Lupus Erythematosus Patients

  • Nwoye O Ephraim Professor, Department of Biomedical Engineering, University of Lagos, Lagos, Nigeria
  • Fidelis P Obinna Lecturer,Department of Biomedical Technology, Federal University of Technology, Akure, Nigeria
  • Nwosu O I Department of Biomedical Engineering, University of Lagos, Lagos, Nigeria
  • Balogun O Jessy Department of Biomedical Engineering, University of Lagos, Lagos, Nigeria
  • Raid Rafi Al-Nima Assistant Professor, Technical Engineering College, Northern Technical University, Iraq
  • Wai Lok Woo Department of Computer and Information Sciences, Northumbria University, UK
DOI: https://doi.org/10.61797/ijbic.v1i1.141
Keywords: Systemic Lupus Erythematosus, Boyer Moore, Approximate matching, SNP, Killer T-cells

Abstract

The incidence and prevalence of SLE in North America are 23.2 and 241 per 100,000 people per year respectively while the incidence in Africa is 0.3 per 100,000 people per year. The study aims to predict the autoimmune response of killer T-cells in a patient suffering from Systemic Lupus Erythematosus by searching for variations in genes regulating the activities of Killer T cells. An approximate matching algorithm applying the Boyer-Moore Algorithm for the matching algorithm. Nucleotide sequences of each of the genes liked to Killer T-cells in reference human genome to DNA sequences of SLE patients. The threshold on all single nucleotide polymorphisms (SNPs) is set to 10% of the nucleotide sequence length of the gene. For 50% of susceptibility genes with no match the patient is susceptible. Sixteen (16) patients show that they are all guaranteed to manifest autoimmune Killer T-cells. The algorithm can predict the response of killer T-cells and improve the early detection and treatment of SLE patients. A similar approach can be used for genetically linked diseases like cancer. 

Published
2022-02-28
Issue
Vol 1 No 1 (2022): Int J Bioinfor Intell Comput
Section
Articles

Copyright (c) 2022 Wai Lok Woo, Nwoye O Ephraim, Fidelis P Obinna, Nwosu O I, Balogun O Jessy, Raid Rafi Al-Nima

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Copyright © by the authors; licensee Research Lake International Inc., Canada. This open-access article is distributed under the terms of the Creative Commons Attribution Non-Commercial License (CC BY-NC) (http://creative-commons.org/licenses/by-nc/4.0/).