RT Journal Article
SR Electronic
T1 Knowledge-guided analysis of ‘omics’ data using the KnowEnG cloud platform
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 642124
DO 10.1101/642124
A1 Charles Blatti III
A1 Amin Emad
A1 Matthew J. Berry
A1 Lisa Gatzke
A1 Milt Epstein
A1 Daniel Lanier
A1 Pramod Rizal
A1 Jing Ge
A1 Xiaoxia Liao
A1 Omar Sobh
A1 Mike Lambert
A1 Corey S. Post
A1 Jinfeng Xiao
A1 Peter Groves
A1 Aidan T. Epstein
A1 Xi Chen
A1 Subhashini Srinivasan
A1 Erik Lehnert
A1 Krishna R. Kalari
A1 Liewei Wang
A1 Richard M. Weinshilboum
A1 Jun S. Song
A1 C. Victor Jongeneel
A1 Jiawei Han
A1 Umberto Ravaioli
A1 Nahil Sobh
A1 Colleen B. Bushell
A1 Saurabh Sinha
YR 2019
UL http://biorxiv.org/content/early/2019/05/19/642124.abstract
AB We 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.