http://rdf.disgenet.org/resource/nanopub/NP1140847.RAmf_GxlNGdmpiKmdLU9atNB_Milppy4gsA4XZj4jl58A
type: Nanopublication
created: 2016-05-13T12:50:23+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/NP1140847.RAmf_GxlNGdmpiKmdLU9atNB_Milppy4gsA4XZj4jl58A130_assertion
type: Assertion
description: [Moreover, integration of CNAs with other high-throughput genomic data, such as aberrantly coding transcriptomes and non-coding gene expression in human HCC tissues and rodent HCC models, provides lines of evidence that can be used to facilitate the identification of novel HCC target genes with the potential of improving the survival of HCC patients.]. Sentence from MEDLINE/PubMed, a database of the U.S. National Library of Medicine.
evidence: DisGeNET evidence - LITERATURE
SIO_000772: http://identifiers.org/pubmed/24379610
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