Next-Generation Analytics for Omics Data

Jun Li; Hu Chen; Yumeng Wang; Mei-Ju May Chen; Han Liang

doi:10.1016/j.ccell.2020.09.002

Next-Generation Analytics for Omics Data

Cancer Cell. 2021 Jan 11;39(1):3-6. doi: 10.1016/j.ccell.2020.09.002. Epub 2020 Sep 24.

Authors

Jun Li¹, Hu Chen², Yumeng Wang², Mei-Ju May Chen¹, Han Liang³

Affiliations

¹ Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
² Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Graduate Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX 77030, USA.
³ Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Graduate Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX 77030, USA; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. Electronic address: hliang1@mdanderson.org.

Abstract

The increasing omics data present a daunting informatics challenge. DrBioRight, a natural language-oriented and artificial intelligence-driven analytics platform, enables the broad research community to perform analysis in an intuitive, efficient, transparent, and collaborative way. The emerging next-generation analytics will maximize the utility of omics data and lead to a new paradigm for biomedical research.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Animals
Big Data
Computational Biology / methods*
Humans
Natural Language Processing

Abstract

Publication types

MeSH terms

Grants and funding