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Bioinformatics. 2017 Oct 1;33(19):3134-3136. doi: 10.1093/bioinformatics/btx382.

GraphSpace: stimulating interdisciplinary collaborations in network biology.

Author information

1
Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, USA.
2
Biology Department, Reed College, Portland, OR 97202, USA.
3
Department of Statistics, Virginia Tech, Blacksburg, VA 24061, USA.
4
RedOwl Analytics, Baltimore, MD 21230, USA.
5
Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061, USA.
6
Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO 80523, USA.
7
Center for Human-Computer Interaction, Virginia Tech, Blacksburg, VA 24061, USA.
8
Biocomplexity Institute.
9
ICTAS Centre for Systems Biology of Engineered Tissues, Virginia Tech, Blacksburg, VA 24061, USA.

Abstract

Summary:

Networks have become ubiquitous in systems biology. Visualization is a crucial component in their analysis. However, collaborations within research teams in network biology are hampered by software systems that are either specific to a computational algorithm, create visualizations that are not biologically meaningful, or have limited features for sharing networks and visualizations. We present GraphSpace, a web-based platform that fosters team science by allowing collaborating research groups to easily store, interact with, layout and share networks.

Availability and implementation:

Anyone can upload and share networks at http://graphspace.org. In addition, the GraphSpace code is available at http://github.com/Murali-group/graphspace if a user wants to run his or her own server.

Contact:

murali@cs.vt.edu.

Supplementary information:

Supplementary data are available at Bioinformatics online.

PMID:
28957495
PMCID:
PMC5860550
DOI:
10.1093/bioinformatics/btx382
[Indexed for MEDLINE]
Free PMC Article

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