Richard R Adams1. 1. SynthSys Edinburgh, University of Edinburgh, Edinburgh, UK. richard.adams@ed.ac.uk
Abstract
UNLABELLED: The simulation experiment description markup language (SED-ML) is a new community data standard to encode computational biology experiments in a computer-readable XML format. Its widespread adoption will require the development of software support to work with SED-ML files. Here, we describe a software tool, SED-ED, to view, edit, validate and annotate SED-ML documents while shielding end-users from the underlying XML representation. SED-ED supports modellers who wish to create, understand and further develop a simulation description provided in SED-ML format. AVAILABILITY AND IMPLEMENTATION: SED-ED is available as a standalone Java application, as an Eclipse plug-in and as an SBSI (www.sbsi.ed.ac.uk) plug-in, all under an MIT open-source license. Source code is at https://sed-ed-sedmleditor.googlecode.com/svn. The application itself is available from https://sourceforge.net/projects/jlibsedml/files/SED-ED/.
UNLABELLED: The simulation experiment description markup language (SED-ML) is a new community data standard to encode computational biology experiments in a computer-readable XML format. Its widespread adoption will require the development of software support to work with SED-ML files. Here, we describe a software tool, SED-ED, to view, edit, validate and annotate SED-ML documents while shielding end-users from the underlying XML representation. SED-ED supports modellers who wish to create, understand and further develop a simulation description provided in SED-ML format. AVAILABILITY AND IMPLEMENTATION: SED-ED is available as a standalone Java application, as an Eclipse plug-in and as an SBSI (www.sbsi.ed.ac.uk) plug-in, all under an MIT open-source license. Source code is at https://sed-ed-sedmleditor.googlecode.com/svn. The application itself is available from https://sourceforge.net/projects/jlibsedml/files/SED-ED/.
Authors: Pei-Chi Yang; Shweta Purawat; Pek U Ieong; Mao-Tsuen Jeng; Kevin R DeMarco; Igor Vorobyov; Andrew D McCulloch; Ilkay Altintas; Rommie E Amaro; Colleen E Clancy Journal: PLoS Comput Biol Date: 2019-03-08 Impact factor: 4.475
Authors: Richard Adams; Allan Clark; Azusa Yamaguchi; Neil Hanlon; Nikos Tsorman; Shakir Ali; Galina Lebedeva; Alexey Goltsov; Anatoly Sorokin; Ozgur E Akman; Carl Troein; Andrew J Millar; Igor Goryanin; Stephen Gilmore Journal: Bioinformatics Date: 2013-01-17 Impact factor: 6.937