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anexVis: visual analytics framework for analysis of RNA expression.
Tran, Diem-Trang; Zhang, Tian; Stutsman, Ryan; Might, Matthew; Desai, Umesh R; Kuberan, Balagurunathan.
Afiliación
  • Tran DT; Department of Medicinal Chemistry.
  • Zhang T; School of Computing, University of Utah, Salt Lake City, UT, USA.
  • Stutsman R; School of Computing, University of Utah, Salt Lake City, UT, USA.
  • Might M; School of Computing, University of Utah, Salt Lake City, UT, USA.
  • Desai UR; Hugh Kaul Personalized Medicine Institute, University of Alabama at Birmingham, Birmingham, AL, USA.
  • Kuberan B; Department of Medicinal Chemistry, Virginia Commonwealth University, Richmond, VA, USA.
Bioinformatics ; 34(14): 2510-2512, 2018 07 15.
Article en En | MEDLINE | ID: mdl-29506198
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.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Análisis de Secuencia de ARN / Perfilación de la Expresión Génica / Visualización de Datos Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2018 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Análisis de Secuencia de ARN / Perfilación de la Expresión Génica / Visualización de Datos Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2018 Tipo del documento: Article