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![Generate an Experiment
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Calzone et al. (2007): Dynamical modeling of syncytial mitotic
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July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 5](https://image.slidesharecdn.com/fairdom-webinar-model-management-scharm-160726132711/75/Model-Management-in-Systems-Biology-Challenges-Approaches-Solutions-6-2048.jpg)
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Model Management in Systems Biology: Challenges – Approaches – Solutions
The document discusses the challenges and approaches in model management within systems biology and bioinformatics, emphasizing the increasing complexity and number of models. It outlines workflows for modeling, sharing research, and the importance of standards for collaboration, while also highlighting ongoing challenges such as version control and data provenance. The authors, Martin Scharm and Dagmar Waltemath, aim to improve accessibility and reproducibility of simulation studies in the field.
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Model Management in Systems Biology: Challenges – Approaches – Solutions
- 1. SYSTEMS BIOLOGY BIOINFORMATICS ROSTOCK S ESsimulation experiment management system Model Management in Systems Biology Challenges – Approaches – Solutions MARTIN SCHARM, DAGMAR WALTEMATH Department of Systems Biology & Bioinformatics, University of Rostock http://sems.uni-rostock.de FAIRDOM Webinar 2016 July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 1
- 2. Background • Number ofmodels is steadily increasing • Models tend to get more complex • Continuous development produces multiple versions July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 2
- 3. Modelling A typical workflow Search and Retrieve Compare Evaluate andSelect Run private public Create Model Encode in Standard Formats Submit and Share Define Analyses and Experiments Model Creator Curator Model User July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 3
- 4. Modelling A typical workflow COPASI JWS CellDesigner Tellurium Search and Retrieve Compare Create Model Evaluate andSelect Run private public Run Create Model Encode in Standard Formats Submit and Share Define Analyses and Experiments Model Creator Curator Model User Run July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 3
- 5. Standards Make life easier Drägerand Palsson: Improving collaboration by standardization efforts in systems biology. Front. Bioeng. Biotechnol. 2014; 2:61. 10.3389/fbioe.2014.00061 July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 4
- 6. Generate an Experiment Encodingthe simulation study Calzone et al. (2007): Dynamical modeling of syncytial mitotic cycles in Drosophila embryos. Mol Syst Biol. 3: 131 TM Wee1n_1 MPFn_1 StgPn_1 mol/l 0 0.2 0.4 0.6 0.8 1 1.2 1.4 s 0 50 100 150 200 250 MPFn_1 StgPn_1 Wee1n_1 mol/l 0 0.2 0.4 0.6 0.8 1 1.2 s 0 50 100 150 200 250 [MPFc]|Time [MPFn]|Time [Stgc]|Time [Stgn]|Time [Wee1n]|Time [preMPFc]|Time [preMPFn]|Time mol/l 0 0.5 1 1.5 2 s 0 50 100 150 200 250 MLSED as published MLSED modified initial environment MLSED selected different species adapted from Waltemath: Reproducible virtual experiments with SED-ML. Harmony 2016, Auckland, NZ July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 5
- 7. Generate an Experiment Encodingthe simulation study Open Challenges • click-able simulation studies • hybrid diagrams in SBGN • zooming for SBGN diagrams • better links from SBML models to genomics data • established standards perform already quite good for most cases, but don’t allow for encoding of every feature and very big studies Waltemath et al.: Toward community standards and software for whole-cell modeling. IEEE Transactions on Biomedical Engineering. vol.PP, no.99, pp.1-1. 10.1109/TBME.2016.2560762 July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 6
- 8. Share your ResearchResults Making research useful for the community What belongs to a reproducible simulation study in systems biology? • models encoding the biology TM • semantic annotations describing the model and its entities • simulation descriptions defining environments and simulation setups MLSED • experimental data feeding the model • documentation on the model and its usage • resulting data ⇒ plenty of heterogeneous data! Problem: How to ship the data while preserving the links? July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 7
- 9. Share your ResearchResults Making research useful for the community Research Object • different flavours, useful for any kind of research data • excellent support for linked data and provenance Combine Archive • entailed for standards in systems biology • good tool support in sysbio software July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 8
- 10. Share your ResearchResults Making research useful for the community TM July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 9
- 11. Share your ResearchResults Making research useful for the community A Modeler’s Tale: the story about a researcher who wants to share his findings. Wolfien, Bagnacani, Gebhardt, Scharm: A Modeler’s Tale. figshare (2016) 10.6084/m9.figshare.3423371.v1 July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 10
- 12. Share your ResearchResults Making research useful for the community A fully featured COMBINE archive Scharm, Touré: COMBINE Archive Show Case. figshare (2016). 10.6084/m9.figshare.3427271.v1 see also github.com/SemsProject/CombineArchiveShowCase July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 11
- 13. Share your ResearchResults Making research useful for the community Open Challenges • lack of tool support • limited support for storing the provenance • limited support for linking files • lack of suitable guidelines for encoding of meta data July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 12
- 14. Public Repositories Biomodels Biomodels Database:575 curated SBML models in 4880 version July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 13
- 15. Public Repositories PMR2 The PhysiomeModel Repository: 5588 CellML models in 672 public repositories July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 14
- 16. Public Repositories FAIRDOMHub The FAIRDOMHubis based on SEEK and manages data for whole consortia ConsortiaConsortia Grp 3 Grp 3 Grp 1 Grp 1 Grp 2 Grp 2 Natalie Stanford SEEKing our way to better presentation of data and models from scientific investigations. ICSB/NormSys workshop Melbourne 2014 Wolstencroft et al.: SEEK: a systems biology data and model management platform. BMC Systems Biology (2015), Issue 9:33, pages 33. 10.1186/s12918-015-0174-y July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 15
- 17. Public Repositories FAIRDOMHub SEEK usesan ISA structure to organise data. Investigation Study Assay July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 15
- 18. Public Repositories Open Challenges •proper version control and access to specific versions • track and extract of provenance information • links between repositories • support for quality checks • one-click simulations • export of COMBINE archives and Research Objects July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 16
- 19. Searching and RetrievingStudies How to get the data? internet internet SEARCHubiquitin internet RESULTS EXPORT EXPORT EXPORT EXPORT Query database for annotations, persons, simulation descriptions Retrieve information about models, simulations, figures, documentation Export simulation study as COMBINE archive Download archive and open the study with your favourite simulation tool Open archive in CAT to modify its contents and to share it with others internet API Commincations enrich your studies with simulation results Simulate a Study with just a single click adapted from Scharm and Waltemath: Extracting reproducible simulation studies from model repositories using the CombineArchive Toolkit. Workshop on Data management in Life Sciences, DMforLS 2015 @ BTW 2015, Hamburg, Germany. btw-2015.de/?dms July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 17
- 20. Searching and RetrievingStudies How to get the data? Open Challenges • ranking on different indices • connection to existing repositories • support for versions July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 18
- 21. Compare Understanding the differences DearCollaborator, please find attached a fixed version of your model! Best regards, Researcher (GMT+7) What happened to my model? July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 19
- 22. Compare Understanding the differences TheBiVeS tool identifies and communicates the differences Scharm, Wolkenhauer and Waltemath: An algorithm to detect and communicate the differences in computational models describing biological systems. Bioinformatics (2016) 32 (4): 563-570. 10.1093/bioinformatics/btv484 July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 20
- 23. Compare Understanding the differences OpenChallenges • differences not really machine “understandable”, yet – see COMODI • just available for versions of models • how to compare different models? • how to compare (versions of) simulation descriptions? • how to compare (versions of) whole studies? Scharm, Waltemathet, Mendes, Wolkenhauer: COMODI: an ontology to characterise differences in versions of computational models in biology. Journal of Biomedical Semantics (2016) 7:46 10.1186/s13326-016-0080-2 July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 21
- 24. Evaluate and select Functionalcuration using a WebLab A call for virtual experiments: Accelerating the scientific process. Cooper et al., Progress in biophysics and molecular biology (2014). The Cardiac Electrophysiology Web Lab. Cooper et al., Biophysical Journal, Volume 110, Issue 2, 292 - 300 July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 22
- 25. Evaluate and select Functionalcuration using a WebLab Open Challenges • exclusively available for cardiac models encoded in CellML • lack of standard for protocols • no method available to evaluate all models in a search result set • lack of interoperability with other tools July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 23
- 26. Summary And acknowledgements Search and Retrieve Compare Create Model Evaluate and Select Run private public Run Create Model Encodein Standard Formats Submit and Share Define Analyses and Experiments Run Pedro Mendes Jacky Snoep Claudine Chaouiya Frank Bergmann David Nickerson Vasundra Touré Brett Olivier Stian Soiland-Reyes Martin Peters Natalie Stanford Stuart Owen Viji Chelliah Tommy Yu Mariam Nassar Jonathan Cooper Gary Mirams Tom Gebhardt Carole GobleDagmar Waltemath July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 24
- 27. SYSTEMS BIOLOGY BIOINFORMATICS ROSTOCK S ESsimulation experiment management system That’s it! SEMS task Force SBI Team Tom Gebhardt Fabienne Lambusch Mariam Nassar Martin Peters Vasundra Toure Dagmar Waltemath Olaf Wolkenhauer July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 25
- 28. SYSTEMS BIOLOGY BIOINFORMATICS ROSTOCK S ESsimulation experiment management system References • Dräger et al.: Improving collaboration by standardization efforts in systems biology. Front. Bioeng. Biotechnol. 2014; 2:61. • Wolfien et al.: A Modeler’s Tale. figshare (2016) 10.6084/m9.figshare.3423371.v1 • Wolstencroft et al.: SEEK: a systems biology data and model management platform. BMC Systems Biology (2015), Issue 9:33, pages 33. • Scharm et al: Extracting reproducible simulation studies from model repositories using the CombineArchive Toolkit. Workshop on Datamanagement in Life Sciences, DMforLS 2015 @ BTW 2015, Hamburg, Germany. • Scharm et al.: An algorithm to detect and communicate the differences in computational models describing biological systems. Bioinformatics (2016) 32 (4): 563-570. • Scharm et al.: COMODI: an ontology to characterise differences in versions of computational models in biology. Journal of Biomedical Semantics (2016) 7:46 • Cooper et al.: A call for virtual experiments: Accelerating the scientific process. Progress in biophysics and molecular biology (2014). • Cooper et al.: The Cardiac Electrophysiology Web Lab. Biophysical Journal, Volume 110, Issue 2, 292 - 300 July, 2016 Model Management in Systems Biology | Martin Scharm, Dagmar Waltemath 26