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ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology.

Authors
  • Waese, Jamie1
  • Fan, Jim2
  • Pasha, Asher1
  • Yu, Hans1
  • Fucile, Geoffrey3
  • Shi, Ruian1
  • Cumming, Matthew1
  • Kelley, Lawrence A4
  • Sternberg, Michael J4
  • Krishnakumar, Vivek5
  • Ferlanti, Erik5
  • Miller, Jason5
  • Town, Chris5
  • Stuerzlinger, Wolfgang6
  • Provart, Nicholas J7
  • 1 Department of Cell and Systems Biology/Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, Ontario M5S 3B2, Canada. , (Canada)
  • 2 Department of Computer Science, University of Waterloo, Ontario N2L 3G1, Canada. , (Canada)
  • 3 SIB Swiss Institute of Bioinformatics, sciCORE Computing Center, University of Basel, CH-4056 Basel, Switzerland. , (Switzerland)
  • 4 Imperial College London, London SW7 2AZ, United Kingdom. , (United Kingdom)
  • 5 Araport.org/J. Craig Venter Institute, Rockville, Maryland 20850.
  • 6 School of Interactive Arts and Technology, Simon Fraser University, British Columbia V3T 0A3, Canada. , (Canada)
  • 7 Department of Cell and Systems Biology/Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, Ontario M5S 3B2, Canada [email protected] , (Canada)
Type
Published Article
Journal
The Plant Cell
Publisher
American Society of Plant Biologists
Publication Date
Aug 01, 2017
Volume
29
Issue
8
Pages
1806–1821
Identifiers
DOI: 10.1105/tpc.17.00073
PMID: 28808136
Source
Medline
Language
English
License
Unknown

Abstract

A big challenge in current systems biology research arises when different types of data must be accessed from separate sources and visualized using separate tools. The high cognitive load required to navigate such a workflow is detrimental to hypothesis generation. Accordingly, there is a need for a robust research platform that incorporates all data and provides integrated search, analysis, and visualization features through a single portal. Here, we present ePlant (http://bar.utoronto.ca/eplant), a visual analytic tool for exploring multiple levels of Arabidopsis thaliana data through a zoomable user interface. ePlant connects to several publicly available web services to download genome, proteome, interactome, transcriptome, and 3D molecular structure data for one or more genes or gene products of interest. Data are displayed with a set of visualization tools that are presented using a conceptual hierarchy from big to small, and many of the tools combine information from more than one data type. We describe the development of ePlant in this article and present several examples illustrating its integrative features for hypothesis generation. We also describe the process of deploying ePlant as an "app" on Araport. Building on readily available web services, the code for ePlant is freely available for any other biological species research. © 2017 American Society of Plant Biologists. All rights reserved.

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