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Collaborative Mining of Whole Genome Sequences for Intelligent HIV-1 Sub-Strain(s) Discovery.

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Bibliographic Details
Title:	Collaborative Mining of Whole Genome Sequences for Intelligent HIV-1 Sub-Strain(s) Discovery.
Authors:	Ekpenyong ME; Department of Computer Science, Faculty of Science, University of Uyo, Uyo, Nigeria.; Centre for Research and Development, University of Uyo, Uyo, Nigeria., Adegoke AA; Department of Microbiology, Faculty of Science, University of Uyo, Uyo, Nigeria., Edoho ME; Department of Computer Science, Faculty of Science, University of Uyo, Uyo, Nigeria., Inyang UG; Department of Computer Science, Faculty of Science, University of Uyo, Uyo, Nigeria., Udo IJ; Department of Computer Science, Faculty of Science, University of Uyo, Uyo, Nigeria., Ekaidem IS; Department of Chemical Pathology, College of Health Sciences, University of Uyo, Uyo, Nigeria., Osang F; Department of Computer Science, Faculty of Science, National Open University, Abuja, Nigeria., Uto NP; School of Mathematics and Statistics, University of St Andrews, Scotland, United Kingdom., Geoffery JI; Department of Computer Science, Faculty of Science, University of Uyo, Uyo, Nigeria.
Source:	Current HIV research [Curr HIV Res] 2022 Aug 12; Vol. 20 (2), pp. 163-183.
Publication Type:	Journal Article; Research Support, Non-U.S. Gov't
Journal Info:	Publisher: Bentham Science Publishers Country of Publication: Netherlands NLM ID: 101156990 Publication Model: Print Cited Medium: Internet ISSN: 1873-4251 (Electronic) Linking ISSN: 1570162X NLM ISO Abbreviation: Curr HIV Res Subsets: MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	1873-4251
DOI:	10.2174/1570162X20666220210142209