SEMS Project

Project duration: March 2012 – February 2017

Research goal

In order to compare scientific results in the life sciences but also to integrate the outcomes from partners in large-scale research collaborations, standardization is necessary. The standardization and exchange of protocols by which data are generated are already widely promoted. However, for the same reasons that apply to wet-lab data generation, results from projects that involve mathematical modelling and computer simulations must be documented to improve exchange, reuse and reproducibility. For example, in order to reproduce a simulation plot in a publication it is often not sufficient to know the equations of the model. The choice of numerical algorithms and their internal settings can influence the simulation results. In parameter estimation the results are often driven by random number generation, requiring statistical information on the outcomes of parameter value optimization. Metainformationon simulation experiments improves the re-use of simulations, supports the development of new models from existing ones and helps reducing errors, thereby improving the reproducibility of scientific results in the field of systems biology.

In this project Dr. Dagmar Waltemath and her team investigate techniques for the encoding of simulation experiments. The project covers the standardized encoding of experiments in an XML format, supporting a range of types of simulation experiments, and including the versioning of both, simulation experiment descriptions and associated models. The exchange of simulation experiment descriptions, together with existing models, will help reduce the development time of models in systems biology, will help the reproducibility of publications and support training in systems biology.

Specific objectives

  • the further development of a standard for the description of simulation experiments (SED-ML). This will improve the reproducibility of model-derived results in publications.
  • a study of model histories, tracing the development of a selection of models, describing the changes that have occurred. The analysis will help deriving criteria for the evolution of models, to enable reference to a particular model instance from a simulation description.
  • a study of simulation experiment histories, tracing the development, describing and classifying the changes that have occurred. This will help to describe differences in simulation experiments.
  • the provision of a simulation experiment management system for maintenance, public availability, retrieval, exchange, and versioning of simulation experiment descriptions in a standard format.

Our most favorite publications…

  1. Dagmar Waltemath, Jonathan R. Karr, Frank T. Bergmann, Vijayalakshmi Chelliah, Michael Hucka, Marcus Krantz, Wolfram Liebermeister, Pedro Mendes, Chris J. Myers, Fellow, IEEE, Pinar Pir, Begum Alaybeyoglu, Naveen K Aranganathan, Kambiz Baghalian et al.Toward community standards and software for whole-cell modeling. IEEE Transactions on Biomedical Engineering (2016). doi: 10.1109/TBME.2016.2560762 (open access)
  2. Dagmar Waltemath and Olaf Wolkenhauer. How modeling standards, software, and initiatives support reproducibility in systems biology and systems medicine. IEEE Transactions on Biomedical Engineering (2016). doi:10.1109/TBME.2016.2555481 (open access)
  3. Martin Scharm, Olaf Wolkenhauer and Dagmar Waltemath. An algorithm to detect and communicate the differences in computational models describing biological systems. Oxford Journals BIOINFORMATICS. doi: 10.1093/bioinformatics/btv484
  4. Martin Scharm and Dagmar Waltemath (2015). Extracting reproducible simulation studies from model repositories using the CombineArchive Toolkit. Workshop on Data management in Life Sciences, BTW 2015, Hamburg, March 2015.
  5. Jonathan Cooper, Jon Olav Vik, Dagmar Waltemath (2014). A call for virtual experiments: Accelerating the scientific process. Progress in Biophysics and Molecular Biology.  access via ScienceDirect (or contact us for further details)
  6. Martin Scharm, Florian Wendland, Martin Peters, Markus Wolfien, Tom Theile, Dagmar Waltemath (2014) The CombineArchiveWeb Application – A Web-based Tool to Handle Files Associated with Modelling Results. Proceedings of the 2014 Workshop on Semantic Web Applications and Tools for life sciences. Demo paper. open access (PDF)

Tools

  1. BiVeS — difference detection in XML-encoded models (SBML, CellML)
  2. WebCAT — Generating, exploring, sharing COMBINE Archives on the Web
  3. CARO — Converting COMBINE Archives into Research Objects and vice versa
  4. M2CAT — Searching for virtual experiments across different model repositories and retrieving COMBINE Archives