| Literature DB >> 29506198 |
Diem-Trang Tran1,2, Tian Zhang2, Ryan Stutsman2, Matthew Might3, Umesh R Desai4, Balagurunathan Kuberan1,5.
Abstract
Summary: Although RNA expression data are accumulating at a remarkable speed, gaining insights from them still requires laborious analyses, which hinder many biological and biomedical researchers. This report introduces a visual analytics framework that applies several well-known visualization techniques to leverage understanding of an RNA expression dataset. Our analyses on glycosaminoglycan-related genes have demonstrated the broad application of this tool, anexVis (analysis of RNA expression), to advance the understanding of tissue-specific glycosaminoglycan regulation and functions, and potentially other biological pathways. Availability and implementation: The application is accessible at https://anexvis.chpc.utah.edu/, source codes deposited on GitHub. Supplementary information: Supplementary data are available at Bioinformatics online.Entities:
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Year: 2018 PMID: 29506198 PMCID: PMC6041878 DOI: 10.1093/bioinformatics/bty122
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937