TY - JOUR
T1 - Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform
AU - Blatti, Charles
AU - Emad, Amin
AU - Berry, Matthew J.
AU - Gatzke, Lisa
AU - Epstein, Milt
AU - Lanier, Daniel
AU - Rizal, Pramod
AU - Ge, Jing
AU - Liao, Xiaoxia
AU - Sobh, Omar
AU - Lambert, Mike
AU - Post, Corey S.
AU - Xiao, Jinfeng
AU - Groves, Peter
AU - Epstein, Aidan T.
AU - Chen, Xi
AU - Srinivasan, Subhashini
AU - Lehnert, Erik
AU - Kalari, Krishna R.
AU - Wang, Liewei
AU - Weinshilboum, Richard M.
AU - Song, Jun S.
AU - Jongeneel, C. Victor
AU - Han, Jiawei
AU - Ravaioli, Umberto
AU - Sobh, Nahil
AU - Bushell, Colleen B.
AU - Sinha, Saurabh
N1 - Publisher Copyright:
© 2020 Blatti et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2020
Y1 - 2020
N2 - We present Knowledge Engine for Genomics (KnowEnG), a free-to-use computational system for analysis of genomics data sets, designed to accelerate biomedical discovery. It includes tools for popular bioinformatics tasks such as gene prioritization, sample clustering, gene set analysis, and expression signature analysis. The system specializes in “knowledge-guided” data mining and machine learning algorithms, in which user-provided data are analyzed in light of prior information about genes, aggregated from numerous knowledge bases and encoded in a massive “Knowledge Network.” KnowEnG adheres to “FAIR” principles (findable, accessible, interoperable, and reuseable): its tools are easily portable to diverse computing environments, run on the cloud for scalable and cost-effective execution, and are interoperable with other computing platforms. The analysis tools are made available through multiple access modes, including a web portal with specialized visualization modules. We demonstrate the KnowEnG system’s potential value in democratization of advanced tools for the modern genomics era through several case studies that use its tools to recreate and expand upon the published analysis of cancer data sets.
AB - We present Knowledge Engine for Genomics (KnowEnG), a free-to-use computational system for analysis of genomics data sets, designed to accelerate biomedical discovery. It includes tools for popular bioinformatics tasks such as gene prioritization, sample clustering, gene set analysis, and expression signature analysis. The system specializes in “knowledge-guided” data mining and machine learning algorithms, in which user-provided data are analyzed in light of prior information about genes, aggregated from numerous knowledge bases and encoded in a massive “Knowledge Network.” KnowEnG adheres to “FAIR” principles (findable, accessible, interoperable, and reuseable): its tools are easily portable to diverse computing environments, run on the cloud for scalable and cost-effective execution, and are interoperable with other computing platforms. The analysis tools are made available through multiple access modes, including a web portal with specialized visualization modules. We demonstrate the KnowEnG system’s potential value in democratization of advanced tools for the modern genomics era through several case studies that use its tools to recreate and expand upon the published analysis of cancer data sets.
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U2 - 10.1371/journal.pbio.3000583
DO - 10.1371/journal.pbio.3000583
M3 - Article
C2 - 31971940
AN - SCOPUS:85078303291
SN - 1544-9173
VL - 18
JO - PLoS biology
JF - PLoS biology
IS - 1
M1 - e3000583
ER -