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A Web Tool for Generating High Quality Machine-readable Biological Pathways
Published on: February 8, 2017
SEND: a suite of tools for the easy sharing of linked biological data
Rodolfo S Allendes Osorio1,2, Yi-An Chen2, Kenji Mizuguchi2,3
1Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), The University of Osaka, 2-2 Yamadaoka, Suita-shi, Osaka 565-0871, Japan.
Abstract:
Here, we introduce SEND (Share Easily bioiNformatics Data), a suite of tools that allow users to share heterogeneous and linked biological data, in an easy and highly customizable way. The code for SEND is freely available on GitHub (https://github.com/targetmine). Also, docker images of all different components of the system are directly available for download from DockerHub (https://hub.docker.com/search?q=rallendes; contact: Rodolfo S. Allendes Osorio, rodolfo.allendes.prime@osaka-u.ac.jp; Kenji Mizuguchi, kenji@protein.osaka-u.ac.jp). Links to additional figures/data available on a web site, or references to online-only supplementary data available at the journal's web site.
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