http://rdf.disgenet.org/resource/nanopub/NP1057852.RAvdGgchJPr30gPZQPPzCztCmB9urAc6XbiQsm2oQ7lmQ
type: Nanopublication
created: 2016-05-13T12:49:46+02:00
rights: http://opendatacommons.org/licenses/odbl/1.0/
rights holder: IBIGroup
subject: SIO_000983
used data: disgenetv3.0rdf
authored by: http://orcid.org/0000-0001-5999-6269
authored by: http://orcid.org/0000-0002-7534-7661
authored by: 0000-0002-9383-528X
authored by: http://orcid.org/0000-0003-0169-8159
authored by: http://orcid.org/0000-0003-1244-7654
created by: http://orcid.org/0000-0003-0169-8159
version: v4.0.0.0

http://rdf.disgenet.org/resource/nanopub/NP1057852.RAvdGgchJPr30gPZQPPzCztCmB9urAc6XbiQsm2oQ7lmQ130_assertion
type: Assertion
description: [A multi-assay algorithm (MAA) that includes the BED capture immunoassay, an avidity assay, CD4 cell count, and viral load was used to identify women who were vs. were not recently infected at the time of enrollment (MAA recent, N = 73; MAA non-recent, N = 2,488); a subset of the women in the MAA non-recent group known to have been HIV infected for at least 2 years before enrollment (known non-recent, N = 54).]. Sentence from MEDLINE/PubMed, a database of the U.S. National Library of Medicine.
evidence: DisGeNET evidence - LITERATURE
SIO_000772: http://identifiers.org/pubmed/23460842
was generated by: ECO_0000203

befree-2016
imported on: 2016-02-19

DisGeNET evidence - LITERATURE
type: ECO_0000212
comment: Gene-disease associations inferred from text-mining the literature.

disgenetv3.0rdf
version: v4.0.0