Comput Methods Programs Biomed - TMT-HCC: a tool for text mining the biomedical literature for hepatocellular carcinoma (HCC) biomarkers identification.

Tópicos

{ gene(2352) biolog(1181) express(1162) }
{ cancer(2502) breast(956) screen(824) }
{ extract(1171) text(1153) clinic(932) }
{ research(1085) discuss(1038) issu(1018) }
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Resumo

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide. New insights into the pathogenesis of this lethal disease are urgently needed. Chromosomal copy number alterations (CNAs) can lead to activation of oncogenes and inactivation of tumor suppressors in human cancers. Thus, identification of cancer-specific CNAs will not only provide new insight into understanding the molecular basis of tumor genesis but also facilitate the identification of HCC biomarkers using CNA. This paper presents the TMT-HCC system; it is a tool for text mining the biomedical literature for hepatocellular carcinoma (HCC) biomarkers identification. TMT-HCC provides researchers with a powerful way to identify and discern molecular biomarkers of HCC to inform diagnosis, prognosis, and treatment driver genes with causal roles in carcinogenesis is to detect genomic regions that under frequent alterations in cancers (CNAs). TMT-HCC also extracts protein-protein interactions from the full text of the scientific papers. The results provided that the integration of genomic and transcriptional data offers powerful potential for identifying novel cancer genes in HCC pathogenesis.

Resumo Limpo

hepatocellular carcinoma hcc third lead caus cancerrel mortal worldwid new insight pathogenesi lethal diseas urgent need chromosom copi number alter cnas can lead activ oncogen inactiv tumor suppressor human cancer thus identif cancerspecif cnas will provid new insight understand molecular basi tumor genesi also facilit identif hcc biomark use cna paper present tmthcc system tool text mine biomed literatur hepatocellular carcinoma hcc biomark identif tmthcc provid research power way identifi discern molecular biomark hcc inform diagnosi prognosi treatment driver gene causal role carcinogenesi detect genom region frequent alter cancer cnas tmthcc also extract proteinprotein interact full text scientif paper result provid integr genom transcript data offer power potenti identifi novel cancer gene hcc pathogenesi

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