Reproducible computational biology experiments with SED-ML - The Simulation Experiment Description Markup Language

BMC Systems Biology Reproducible computational biology experiments with SED-ML - The Simulation Experiment Description Markup Language Dagmar Waltemath 4 Richard Adams 2 Frank T Bergmann 1 Michael Hucka 1 Fedor Kolpakov 8 Andrew K Miller 7 Ion I Moraru 6 David Nickerson 7 Sven Sahle 5 Jacky L Snoep 3 9 10 Nicolas Le Novre 0 0 EBI, Wellcome Trust Genome Campus , Hinxton, Cambridgeshire CB10 1SD , UK 1 California Institute of Technology , 1200 East California Blvd., Pasadena, CA 91125 , USA 2 Centre for Systems Biology Edinburgh, CHWaddington Building, University of Edinburgh , Edinburgh EH9 3JD , UK 3 Molecular Cell Physiology, VU University , Amsterdam , The Netherlands 4 Department of Systems Biology & Bioinformatics, Institute of Computer Science, University of Rostock , D-18051 Rostock , Germany 5 BIOQUANT, University of Heidelberg , Im Neuenheimer Feld 267, Heidelberg , Germany 6 Center for Cell Analysis and Modeling, University of Connecticut Health Center , Farmington, CT 06030 , USA 7 Auckland Bioengineering Institute, The University of Auckland , Auckland , New Zealand 8 Institute of Systems Biology Ltd. , Detskiy proezd 15, Novosibirsk, 630090 , Russia 9 Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, the University of Manchester , 131 Princess Street Manchester, M1 7DN , UK 10 Department of Biochemistry, Stellenbosch University , Privatebag X1, Matieland 7602 , South Africa Background: The increasing use of computational simulation experiments to inform modern biological research creates new challenges to annotate, archive, share and reproduce such experiments. The recently published Minimum Information About a Simulation Experiment (MIASE) proposes a minimal set of information that should be provided to allow the reproduction of simulation experiments among users and software tools. Results: In this article, we present the Simulation Experiment Description Markup Language (SED-ML). SED-ML encodes in a computer-readable exchange format the information required by MIASE to enable reproduction of simulation experiments. It has been developed as a community project and it is defined in a detailed technical specification and additionally provides an XML schema. The version of SED-ML described in this publication is Level 1 Version 1. It covers the description of the most frequent type of simulation experiments in the area, namely time course simulations. SED-ML documents specify which models to use in an experiment, modifications to apply on the models before using them, which simulation procedures to run on each model, what analysis results to output, and how the results should be presented. These descriptions are independent of the underlying model implementation. SED-ML is a software-independent format for encoding the description of simulation experiments; it is not specific to particular simulation tools. Here, we demonstrate that with the growing software support for SED-ML we can effectively exchange executable simulation descriptions. Conclusions: With SED-ML, software can exchange simulation experiment descriptions, enabling the validation and reuse of simulation experiments in different tools. Authors of papers reporting simulation experiments can make their simulation protocols available for other scientists to reproduce the results. Because SED-ML is agnostic about exact modeling language(s) used, experiments covering models from different fields of research can be accurately described and combined. - Background Reproducibility of results is a basic requirement for all scientific endeavors. This is not only true for experiments in the wet lab, but also for simulations of computational biology models [1]. Reproducibility of simulations (i. e., the closeness between the results of independent simulations performed with the same methods on identical models but with a different experimental setup [1]) saves time in modeling and simulation projects. The Minimum Information About a Simulation Experiment (MIASE, [1]) is a reporting guideline describing the minimal set of information that must be provided to make the description of a simulation experiment available to others. It includes the list of models to use and their modifications, all the simulation procedures to apply and in which order, the processing of the raw numerical results, and the description of the final output. MIASE is part of MIBBI [2], a project aiming at federating Minimum Information guidelines (MIs) in the life sciences. MIs are standards that specify which information should be provided as a minimum to ensure that published results of a given type can be understood, ww.biomedcentral.com/1752-0509/5/198 r e p r o d u c e d . s t a n d a r d s E n d - u s e r s d o w n l o a d i n f o r m a t i o n a p p l i c a b l e s i m u l a t i o n r e p r e s e n t a t i o n e x p e r i m e n t d e s c r i p t i o n s s t r u c t u r e , ht tp://sed-ml.o rg/) , c o m p u t a t i o n a l post-processing e x p e r im e n t ; i n t e r p r e t i n g X M L , e x c h a n g e a b l e , d e s c r i p t i o ns d e s c r i p t i o n s , r e c o m m e n d p e r s i s t e n t , Article No . jtbi.19 9.0924, available online at ht p:/ www.idealibrary.com on Chaos and Birhythmicity in a Model for Circadian Oscil ations of the Unite de Chronobiologie Theorique, Faculte des Sciences, Universite Libre de Bruxel es , Campus Plaine, C .P . 231, B -1050 Brus els, Belgium (Received on 13 July 19 8, Ac epted in revised form on12 February 19 9) 1. Introduction oc ur in nearly al living organisms, and are Hal & Rosbash, 1987; Baylies et al., 19 3; Hal , 19 6; Crosthwaite et al., 19 7). In Drosophila, among the most conspicuous biological rhythms. 19 6). The per and tim genes have recently be n have be n gained from the study of organisms including man. This sug ests that the circadian expres ion of the per and tim genes which code for the two proteins (Hunter-Ensor et al., 19 6; clock mechanism might be conserved at least *Author to whom cor espondence should be ad res ed. 19 6). The extended model ac ounts for a E-mail: agoldbet ulb.ac.be number of experimental observations such as the Model database Simulaon Tool SED-ML with Oscillation and Chaos Task Data Generators Figure 2 Main SED-ML elements. High level overview of the relations between the five major elements of a SED-ML document. Pairs of model and simulation elements are used in tasks. The dataGenerators allow to define the post-processing of simulation data to define the desired output (plots or reports). consistent and accessible model resources. Persistent model resources include, for instance, repositories or databases having a MIRIAM URI [6]. We have restricted SED-ML to model encodings in XML-based languages (such as SBML, CellML, or NeuroML). In order to improve interoperability, the particular language a model is encoded in should be specified using one of the predefined SED-ML language Unif (...truncated)