http://rdf.disgenet.org/resource/nanopub/NP264592.RADGZbfnppA1bzkiz_qBtB7PE2AsGL4cON22agnHhQhNo
type: Nanopublication
created: 2016-05-13T12:43:46+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/NP264592.RADGZbfnppA1bzkiz_qBtB7PE2AsGL4cON22agnHhQhNo130_assertion
type: Assertion
description: [The results of our study demonstrate that the assessment of combined PSA and p53 expression status by ELISAs, easily applicable to breast tumour extracts prepared for steroid hormone receptor analyses, may stratify breast cancer patients into groups differing by relapse and death risks of greater magnitude than offered by the assessment of either p53 or PSA alone.]. Sentence from MEDLINE/PubMed, a database of the U.S. National Library of Medicine.
evidence: DisGeNET evidence - LITERATURE
SIO_000772: http://identifiers.org/pubmed/10507775
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