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SimplevisGrid: grid services for visualization of diverse biomedical knowledge and molecular systems data.
Stokes, Todd H; Wang, May D.
Afiliação
  • Stokes TH; Electrical and Computer Engineering Department, Georgia Institute of Technology, Atlanta, GA 30332, USA. todd.stokes@bme.gatech.edu
Article em En | MEDLINE | ID: mdl-19964624
Biomedical data visualization is a great challenge due to the scale, complexity, and diversity of systems, system component interactions and experimental data. Standards for interoperable data are a good start to addressing these problems, but standardization of visualization technologies is an emerging topic. SimpleVisGrid builds on Cancer Biomedical Informatics Grid (caBIG) common infrastructure for cancer research, and clearly specifies and extends three standard data formats for inputs and outputs to grid services: comma-separated values (CSV), Portable Network Graphics (PNG), and Scalable Vector Graphics (SVG). Four prototype visualizations are available: 2D array data quality visualization, correlation heatmaps between high-dimensional data and associated meta-data, feature landscapes, and biochemical or semantic network graphs. The services and data model are prepared for submission for caBIG Silver-level compatibility review and for integration into automated research workflows. Making these tools available to caBIG developers and ultimately to biomedical researchers can (1) help with biomedical communication, discovery, and decision-making, (2) encourage more research on standardization of visualization formats, and (3) improve the efficiency of large data transfers across the grid.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Gráficos por Computador / Software / Biologia Computacional Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2009 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Gráficos por Computador / Software / Biologia Computacional Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2009 Tipo de documento: Article