GRAPHSPACE: Stimulating interdisciplinary collaborations in network biology
Creators: name: Bharadwaj, Aditya
name: Divit P. Singh, Anna Ritz
name: T. M. Murali
Publisher: name: F1000Research
Year: 2017

description: Project Website: http://www.graphspace.org<br>Source Code: https://github.com/Murali-group/GraphSpace<br>License: GNU General Public License v3<br><br>Computational analysis of molecular interaction networks has become pervasive in systems biology. Despite the existence of several software systems and interfaces to analyze and view networks, interdisciplinary research teams in network biology face several challenges in sharing, exploring, and interpreting computed networks in their collaborations. GRAPHSPACE is a web-based system that provides a rich set of user-friendly features designed to stimulate and enhance network-based collaboration:


	Users can upload richly-annotated networks, irrespective of the algorithms or software used to generate them. GRAPHSPACE networks follow the JSON format supported by Cytoscape.js [1]. Users of Cytoscape [3] can export their networks and upload them directly into GRAPHSPACE.
	Users can create private groups, invite other users to join groups, and share networks with groups.
	A user may search for networks with a specific property or that contain a specific node or collection of nodes.
	A powerful layout editor allows users to efficiently modify node positions, edit node and edge styles, save new layouts, and share them with other users.
	Researchers may make networks public and provide a persistent URL in a publication, enabling other researchers to explore these networks.
	A comprehensive RESTFul API streamlines programmatic access to GRAPHSPACE features.
	A Python module called graphspace-python allows a user to rapidly construct a graph, set visual styles of nodes and edges, and then upload the graph, all within tens of lines of code. It is very easy to integrate this script into a user’s software pipeline. Currently, GraphSpace supports more than 300 users who have stored more than 21,000 graphs (most of them private) containing a total of over 1.4 million nodes and 3.8 million edges. Conceptually, GRAPHSPACE serves as a bridge between visualization and analysis of individual networks supported by systems such as Cytoscape [3] and the network indexing capabilities of NDex [2]. We anticipate that GRAPHSPACE will find wide use in network biology projects and will assist in accelerating all aspects of collaborations among computational biologists and experimentalists, including preliminary investigations, manuscript development, and dissemination of research.

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