Insilico Functional Analysis of Genome-Wide Dataset From 17,000 Individuals Identifies Candidate Malaria Resistance Genes Enriched in Malaria Pathogenic Pathways.

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Title: Insilico Functional Analysis of Genome-Wide Dataset From 17,000 Individuals Identifies Candidate Malaria Resistance Genes Enriched in Malaria Pathogenic Pathways.
Authors: Damena D; Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa., Agamah FE; Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa., Kimathi PO; Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa., Kabongo NE; Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa., Girma H; Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa., Choga WT; Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa., Golassa L; Aklilu Lema Institute of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia., Chimusa ER; Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa.; Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
Source: Frontiers in genetics [Front Genet] 2021 Nov 18; Vol. 12, pp. 676960. Date of Electronic Publication: 2021 Nov 18 (Print Publication: 2021).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101560621 Publication Model: eCollection Cited Medium: Print ISSN: 1664-8021 (Print) Linking ISSN: 16648021 NLM ISO Abbreviation: Front Genet Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1664-8021
DOI:10.3389/fgene.2021.676960