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Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform.
PLoS Biol 2020; 18(1):e3000583PB

Abstract

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.

Authors+Show Affiliations

Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America. Department of Electrical and Computer Engineering, McGill University, Montreal, Canada.National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Seven Bridges Genomics, Charlestown, Massachusetts, United States of America.Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America.Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota, United States of America.Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America. Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America. Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America. Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America. Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31971940

Citation

Blatti, Charles, et al. "Knowledge-guided Analysis of "omics" Data Using the KnowEnG Cloud Platform." PLoS Biology, vol. 18, no. 1, 2020, pp. e3000583.
Blatti C, Emad A, Berry MJ, et al. Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform. PLoS Biol. 2020;18(1):e3000583.
Blatti, C., Emad, A., Berry, M. J., Gatzke, L., Epstein, M., Lanier, D., ... Sinha, S. (2020). Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform. PLoS Biology, 18(1), pp. e3000583. doi:10.1371/journal.pbio.3000583.
Blatti C, et al. Knowledge-guided Analysis of "omics" Data Using the KnowEnG Cloud Platform. PLoS Biol. 2020;18(1):e3000583. PubMed PMID: 31971940.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform. AU - Blatti,Charles,3rd 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, Y1 - 2020/01/23/ PY - 2019/05/29/received PY - 2019/12/19/accepted PY - 2020/1/24/entrez PY - 2020/1/24/pubmed PY - 2020/1/24/medline SP - e3000583 EP - e3000583 JF - PLoS biology JO - PLoS Biol. VL - 18 IS - 1 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. SN - 1545-7885 UR - https://www.unboundmedicine.com/medline/citation/31971940/Knowledge-guided_analysis_of_"omics"_data_using_the_KnowEnG_cloud_platform L2 - http://dx.plos.org/10.1371/journal.pbio.3000583 DB - PRIME DP - Unbound Medicine ER -