Literature DB >> 11102659

Interactive visualization and exploration of relationships between biological objects.

D R Gilbert1, M Schroeder, J van Helden.   

Abstract

Genome sequencing and microarray technology produce ever-increasing amounts of complex data that need analysis. Visualization is an effective analytical technique that exploits the ability of the human brain to process large amounts of data. Here, we review traditional visualization methods based on clustering and tree representation, and also describe an alternative approach that involves projecting objects onto a Euclidean space in a way that reflects their structural or functional distances. Data are visualized without preclustering and can be dynamically explored by the user using 'virtual-reality'. We illustrate this approach with two case studies from protein topology and gene expression.

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Year:  2000        PMID: 11102659     DOI: 10.1016/s0167-7799(00)01510-9

Source DB:  PubMed          Journal:  Trends Biotechnol        ISSN: 0167-7799            Impact factor:   19.536


  4 in total

1.  d-matrix - database exploration, visualization and analysis.

Authors:  Dominik Seelow; Raffaello Galli; Siegrun Mebus; Hans-Peter Sperling; Hans Lehrach; Silke Sperling
Journal:  BMC Bioinformatics       Date:  2004-10-28       Impact factor: 3.169

2.  Providing visualisation support for the analysis of anatomy ontology data.

Authors:  Aba-Sah Dadzie; Albert Burger
Journal:  BMC Bioinformatics       Date:  2005-03-24       Impact factor: 3.169

3.  Integrative analysis of longitudinal metabolomics data from a personal multi-omics profile.

Authors:  Larissa Stanberry; George I Mias; Winston Haynes; Roger Higdon; Michael Snyder; Eugene Kolker
Journal:  Metabolites       Date:  2013-09-03

4.  Computational gene expression profiling under salt stress reveals patterns of co-expression.

Authors:  Ashok Sharma
Journal:  Genom Data       Date:  2016-01-15
  4 in total

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