http://rdf.disgenet.org/resource/nanopub/NP1278616.RAtU5hfFPsyGDO3TR5-h1NGyhsOvMvHz1zts74Dye92X8
type: Nanopublication
created: 2016-05-13T12:51:25+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/NP1278616.RAtU5hfFPsyGDO3TR5-h1NGyhsOvMvHz1zts74Dye92X8130_assertion
type: Assertion
description: [High-throughput technologies allow deepening into the molecular architecture of breast cancer, integrating different levels of information, which is important if it helps in making clinical decisions. microRNA (miRNA) and protein expression profiles were obtained from 71 estrogen receptor-positive (ER(+)) and 25 triple-negative breast cancer (TNBC) samples.]. Sentence from MEDLINE/PubMed, a database of the U.S. National Library of Medicine.
evidence: DisGeNET evidence - LITERATURE
SIO_000772: http://identifiers.org/pubmed/25883093
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