Work

Harnessing big ‘omics’ data and AI for drug discovery in hepatocellular carcinoma

Year: 2020

Type: review

Source: Nature Reviews Gastroenterology & Hepatology

DOI: 10.1038/s41575-019-0240-9

Authors: Bin Chen, Lana Garmire, Diego F. Calvisi, Mei-Sze Chua, Robin K. Kelley, Xin Chen

Institutions: Michigan State University, University of Michigan, University of Sassari, University of Regensburg, Stanford Medicine, Stanford University, University of California, San Francisco

Language: English

Topic: Hepatocellular Carcinoma Treatment and Prognosis

Subfield: Hepatology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Institute of General Medical Sciences, National Institute of Environmental Health Sciences, U.S. National Library of Medicine, National Center for Advancing Translational Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development

Awards: Targeting glucose metabolism for the treatment of Hepatocellular Carcinoma, DR. EPS: Drug Repurposing for Extended Patient Survival, An Integrative Omics Approach to Identify Biomarkers Related to Preeclampsia and Breast Cancer Risks, Institute for Biogenesis Research: COBRE, An Integrative Bioinformatics Approach to Study Single Cancer Cell Heterogeneity, Integrating transcriptomic, proteomic and pharmacogenomic data to inform individualized therapy in cancers, Cancer precision medicine through spatially informative single cell image and transcriptomics data analysis

OpenAlex ID: W2997782431

FWCI: 3.531

Cites: 133

Cited by: 154

Related to: 10