From big data to diagnosis and prognosis: gene expression signatures in liver hepatocellular carcinoma.

ABSTRACT:

Background

Liver hepatocellular carcinoma accounts for the overwhelming majority of primary liver cancers and its belated diagnosis and poor prognosis call for novel biomarkers to be discovered, which, in the era of big data, innovative bioinformatics and computational techniques can prove to be highly helpful in.

Methods

Big data aggregated from The Cancer Genome Atlas and Natural Language Processing were integrated to generate differentially expressed genes. Relevant signaling pathways of differentially expressed genes went through Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes and Panther pathway enrichment analysis and protein-protein interaction network. The pathway ranked high in the enrichment analysis was further investigated, and selected

SUBMITTER: Yang H 

PROVIDER: S-EPMC5354077 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature