Support Vector Machine Implementation in the Analysis of HIV Species Based on Amino Acid and Dipeptide Sequences

Dr. Kailash Chandra Nayak. and Dr. Bhabani Sankar Ratha
Additional contact information
Dr. Kailash Chandra Nayak.: Associate Professor, USBM, Bhubaneswar
Dr. Bhabani Sankar Ratha: Associate Professor, NIIS Institute of Business Administration, Bhubaneswar

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 3, 201-205

Abstract: Infections are little irresistible specialists that can reproduce inside the cells in living life form. Human Immunodeficiency (HIV) is an infection that attacks human cells, debilitates the insusceptible framework and making individuals more vulnerable to disease. The favourable environment created by such virus allows grow of its content and rapidly increases within the hosts. HIV is a progressive sickness that causes a wide range of medical problems as a result of a widening array of bodily deficiencies and also considered as a lentivirus responsible for AIDS. The progressive breakdown of safe structures and the increase of dangerous breakthrough contamination characterise such human situation. In the study we used support vector machine (SVM) with Uniprot / Swiss-prot database to know the discrimination in HIV species based on Amino Acid and Dipeptide sequences to know the proportion and suggest the doctors to inject favourable protein to overcome the contamination. This also encourages the pharmaceutical industries to produce low cost medicines to cure of such diseases and also allow the patients to recover from diseases in low cost.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.ijltemas.in/DigitalLibrary/Vol.14Issue3/201-205.pdf (application/pdf)
https://www.ijltemas.in/papers/volume-14-issue-3/201-205.html (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjb:journl:v:14:y:2025:i:3:p:201-205

Access Statistics for this article

International Journal of Latest Technology in Engineering, Management & Applied Science is currently edited by Dr. Pawan Verma

More articles in International Journal of Latest Technology in Engineering, Management & Applied Science from International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Bibliographic data for series maintained by Dr. Pawan Verma ().