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