{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Gerns Storey HL"],"funding":["NICHD NIH HHS","NCRR NIH HHS","NIAID NIH HHS"],"pagination":["37-44"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC3931433"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["30(1)"],"pubmed_abstract":["The role of HIV-1-specific antibody responses in HIV disease progression is complex and would benefit from analysis techniques that examine clusterings of responses. Protein microarray platforms facilitate the simultaneous evaluation of numerous protein-specific antibody responses, though excessive data are cumbersome in analyses. Principal components analysis (PCA) reduces data dimensionality by generating fewer composite variables that maximally account for variance in a dataset. To identify clusters of antibody responses involved in disease control, we investigated the association of HIV-1-specific antibody responses by protein microarray, and assessed their association with disease progression using PCA in a nested cohort design. Associations observed among collections of antibody resp"],"journal":["AIDS research and human retroviruses"],"pubmed_title":["Use of principal components analysis and protein microarray to explore the association of HIV-1-specific IgG responses with disease progression."],"pmcid":["PMC3931433"],"funding_grant_id":["K24 HD054314","5U01AI078213-05","TL1 RR025016"],"pubmed_authors":["Walson JL","Camerini D","Singa B","Naulikha J","Felgner PL","Horton H","Diaz-Ochoa VE","John-Stewart G","Gerns Storey HL","Prindle VC","Richardson BA"],"additional_accession":[]},"is_claimable":false,"name":"Use of principal components analysis and protein microarray to explore the association of HIV-1-specific IgG responses with disease progression.","description":"The role of HIV-1-specific antibody responses in HIV disease progression is complex and would benefit from analysis techniques that examine clusterings of responses. Protein microarray platforms facilitate the simultaneous evaluation of numerous protein-specific antibody responses, though excessive data are cumbersome in analyses. Principal components analysis (PCA) reduces data dimensionality by generating fewer composite variables that maximally account for variance in a dataset. To identify clusters of antibody responses involved in disease control, we investigated the association of HIV-1-specific antibody responses by protein microarray, and assessed their association with disease progression using PCA in a nested cohort design. Associations observed among collections of antibody resp","dates":{"release":"2014-01-01T00:00:00Z","publication":"2014 Jan","modification":"2026-04-07T14:00:19.327Z","creation":"2019-03-27T01:22:13Z"},"accession":"S-EPMC3931433","cross_references":{"pubmed":["24134221"],"doi":["10.1089/AID.2013.0088","10.1089/aid.2013.0088"]}}