Improving reproducibility and reuse of modelling results in the life sciences

Research results are complex and include a variety of heterogeneous data. This entails major computational challenges to (i) to manage simulation studies, (ii) to ensure model exchangeability, stability and validity, and (iii) to foster communication between partners. I describe techniques to improve the reproducibility and reuse of modelling results. First, I introduce a method to characterise differences in computational models. Second, I present approaches to obtain shareable and reproducible research results. Altogether, my methods and tools foster exchange and reuse of modelling results.Die verteilte Entwicklung von komplexen Simulationsstudien birgt eine große Zahl an informationstechnischen Herausforderungen: (i) Modelle müssen verwaltet werden; (ii) Reproduzierbarkeit, Stabilität und Gültigkeit von Ergebnissen muss sichergestellt werden; und (iii) die Kommunikation zwischen Partnern muss verbessert werden. Ich stelle Techniken vor, um die Reproduzierbarkeit und Wiederverwendbarkeit von Modellierungsergebnissen zu verbessern. Meine Implementierungen wurden erfolgreich in internationalen Anwendungen integriert und fördern das Teilen von wissenschaftlichen Ergebnissen

The CombineArchiveWeb application -A web based tool to handle files associated with modelling results

Abstract. Sharing in silico experiments is essential for the advance of research in computational biology. Consequently, the COMBINE archive was designed as a digital container format. It eases the management of files related to a modelling result, fosters collaboration, and ultimately enables the exchange of reproducible simulation studies. However, manual handling of COMBINE archives is tedious and error prone. We therefore developed the CombineArchiveWeb application to support scientists in promoting and publishing their research by means of creating, exploring, modifying, and sharing archives. All files are equipped with meta data and can be distributed over the Web through shareable workspaces

SED-ML Web Tools: Generate, modify and export standard-compliant simulation studies

ABSTRACT The Simulation Experiment Description Markup Language (SED-ML) is a standardized format for exchanging simulation studies independently of software tools. We present the SED-ML Web Tools, a software that supports SED-ML Level 1 Version 2, including complex modifications and co-simulation of SBML and CellML models. This online application allows for creating, editing, simulating and validating SED-ML documents. It lowers the bar on working with SED-ML documents and helps users create valid simulation descriptions for models in CellML and SBML formats. Availability and Implementation: sysbioapps.dyndns.org/SED-ML Web Tools. Further information: sysbioapps.dyndns.org/SED-ML Web Tools/Services/SedMLService.asmx

Toward community standards and software for whole-cell modeling

Whole-cell (WC) modeling is a promising tool for biological research, bioengineering, and medicine. However, substantial work remains to create accurate, comprehensive models of complex cells. Methods: We organized the 2015 Whole-Cell Modeling Summer School to teach WC modeling and evaluate the need for new WC modeling standards and software by recoding a recently published WC model in SBML. Results: Our analysis revealed several challenges to representing WC models using the current standards. Conclusion: We, therefore, propose several new WC modeling standards, software, and databases. Significance:We anticipate that these new standards and software will enable more comprehensive models

SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution

binfalse.de

My blog at http://binfalse.d

A fully featured COMBINE archive of a simulation study on syncytial mitotic cycles in Drosophila embryos [version 1; referees: 1 approved, 2 approved with reservations]

COMBINE archives are standardised containers for data files related to a simulation study in computational biology. This manuscript describes a fully featured archive of a previously published simulation study, including (i) the original publication, (ii) the model, (iii) the analyses, and (iv) metadata describing the files and their origin. With the archived data at hand, it is possible to reproduce the results of the original work. The archive can be used for both, educational and research purposes. Anyone may reuse, extend and update the archive to make it a valuable resource for the scientific community

Docker for CS @ Rostock

This is about the Docker software and whether it makes sense to use and support it at the institute of computer science in Rostock, Germany. Shown commands and there outputs are as executed on a CentOS Linux release 7.2.1511 (Core). This paper neither recommends anything nor does it show best practices. Its goal is to launch and facilitate a competent discussion.<br><br

COMODI : an ontology to characterise differences in versions of computational models in biology

CITATION: Scharm, M., Waltemath, D., Mendes, P. & Wolkenhauer, O. 2016. COMODI : an ontology to characterise differences in versions of computational models in biology. Journal of Biomedical Semantics, 7:46, doi:10.1186/s13326-016-0080-2.The original publication is available at https://jbiomedsem.biomedcentral.comBackground: Open model repositories provide ready-to-reuse computational models of biological systems. Models within those repositories evolve over time, leading to different model versions. Taken together, the underlying changes reflect a model’s provenance and thus can give valuable insights into the studied biology. Currently, however, changes cannot be semantically interpreted. To improve this situation, we developed an ontology of terms describing changes in models. The ontology can be used by scientists and within software to characterise model updates at the level of single changes. When studying or reusing a model, these annotations help with determining the relevance of a change in a given context. Methods: We manually studied changes in selected models from BioModels and the Physiome Model Repository. Using the BiVeS tool for difference detection, we then performed an automatic analysis of changes in all models published in these repositories. The resulting set of concepts led us to define candidate terms for the ontology. In a final step, we aggregated and classified these terms and built the first version of the ontology. Results: We present COMODI, an ontology needed because COmputational MOdels DIffer. It empowers users and software to describe changes in a model on the semantic level. COMODI also enables software to implement user-specific filter options for the display of model changes. Finally, COMODI is a step towards predicting how a change in a model influences the simulation results. Conclusion: COMODI, coupled with our algorithm for difference detection, ensures the transparency of a model’s evolution, and it enhances the traceability of updates and error corrections. COMODI is encoded in OWL. It is openly available at http://comodi.sems.uni-rostock.de/.https://jbiomedsem.biomedcentral.com/articles/10.1186/s13326-016-0080-2Publisher's versio