http://rdf.disgenet.org/resource/nanopub/NP542658.RAJ2Dz4GhEifQVJmDLP4Vc_AblwuDVxirWJLkWTK3DqRI
type: Nanopublication
created: 2016-05-13T12:45:50+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/NP542658.RAJ2Dz4GhEifQVJmDLP4Vc_AblwuDVxirWJLkWTK3DqRI130_assertion
type: Assertion
description: [The combination of LCM, MDA and gaCGH is ideally suited for the identification of CNAs from small cell clusters and may assist in the discovery of potential genomic markers for early diagnosis, or identify the location of tumour suppressor genes (TSG) or oncogenes previously unreported in HPIN and CaP.]. Sentence from MEDLINE/PubMed, a database of the U.S. National Library of Medicine.
evidence: DisGeNET evidence - LITERATURE
SIO_000772: http://identifiers.org/pubmed/16573809
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