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Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform.

Authors :
Blatti C 3rd
Emad A
Berry MJ
Gatzke L
Epstein M
Lanier D
Rizal P
Ge J
Liao X
Sobh O
Lambert M
Post CS
Xiao J
Groves P
Epstein AT
Chen X
Srinivasan S
Lehnert E
Kalari KR
Wang L
Weinshilboum RM
Song JS
Jongeneel CV
Han J
Ravaioli U
Sobh N
Bushell CB
Sinha S
Source :
PLoS biology [PLoS Biol] 2020 Jan 23; Vol. 18 (1), pp. e3000583. Date of Electronic Publication: 2020 Jan 23 (Print Publication: 2020).
Publication Year :
2020

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.<br />Competing Interests: The authors have declared that no competing interests exist.

Details

Language :
English
ISSN :
1545-7885
Volume :
18
Issue :
1
Database :
MEDLINE
Journal :
PLoS biology
Publication Type :
Academic Journal
Accession number :
31971940
Full Text :
https://doi.org/10.1371/journal.pbio.3000583