Author:
Blatti Charles,Emad Amin,Berry Matthew J.,Gatzke Lisa,Epstein Milt,Lanier Daniel,Rizal Pramod,Ge Jing,Liao Xiaoxia,Sobh Omar,Lambert Mike,Post Corey S.,Xiao Jinfeng,Groves Peter,Epstein Aidan T.,Chen Xi,Srinivasan Subhashini,Lehnert Erik,Kalari Krishna R.,Wang Liewei,Weinshilboum Richard M.,Song Jun S.,Jongeneel C. Victor,Han Jiawei,Ravaioli Umberto,Sobh Nahil,Bushell Colleen B.,Sinha Saurabh
Abstract
AbstractWe present 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 offers ‘knowledge-guided’ data-mining and machine learning algorithms, where 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: its tools are easily portable to diverse computing environments, run on the cloud for scalable and cost-effective execution of compute-intensive and data-intensive algorithms, and are interoperable with other computing platforms. They are made available through multiple access modes including a web-portal, and include specialized visualization modules. We present use cases and re-analysis of published cancer data sets using KnowEnG tools and demonstrate its potential value in democratization of advanced tools for the modern genomics era.
Publisher
Cold Spring Harbor Laboratory
Cited by
3 articles.
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