Quantitative analysis and simulation of cellular processes is becoming a useful and in an increasing number of cases, an indispensible tool for predictive biomedical research. In this proposal we aim to continue our work on biomedical computational standards together with further improvements to our simulation software infrastructure. Our work involves close collaboration with numerous colleagues in the United States and Europe particularly in relation to standards development. Over the last few years we have been heavily involved in efforts aimed at developing standards such as SBML (Model definition), SBGN (Graphical network representation) and MIASE/SED-ML (Simulation description). In addition we have provided software comparison tools to enable other developers to gauge their efforts against others and in the process helped improve software provision in the community. In this new proposal we highlight three areas of effort: 1) Continue to improve our infrastructure, particularly tutorials and documentation;2) To propose and develop a simulation description standard;2) Develop a bifurcation analysis suite. One of the most frustrating aspects of computational models is the difficulty in replicating simulations published by other researchers. We currently have the systems biology markup language (SBML) as the de facto standard model description format but we do not have any standard means to describe how a simulation should actually be carried out. There are tentative efforts to begin such a process and we propose to explore and develop such as standard in consultation with the community. Related to this we also intend to develop the necessary infrastructure and toolkits to enable authors and journal publishers to directly embed complete model descriptions of disease and biomedical processes in electronic published work, for example e-books and electronic journal articles. In practice we envisage a researcher viewing the document in a standard viewer and requesting all information required to model and replicate a particular graph by simply selecting the graph with the mouse. This would allow a researcher to reproduce a simulation with minimal effort. As a test of this effort we will develop a suite of bifurcation tools which we feel will be the most demanding test for a simulation description standard.

Public Health Relevance

The ability of scientists to replicate biomedical simulation experiments that have been published by their colleagues is a critical aspect of the scientific method. We propose to devise a common computer format that the community can use to represent the instructions needed to recreate any data or graph that is published in a scientific paper.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM081070-06
Application #
8534160
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Lyster, Peter
Project Start
2007-08-02
Project End
2015-08-31
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
6
Fiscal Year
2013
Total Cost
$281,230
Indirect Cost
$84,220
Name
University of Washington
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
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Bartley, Bryan A; Kim, Kyung; Medley, J Kyle et al. (2017) Synthetic Biology: Engineering Living Systems from Biophysical Principles. Biophys J 112:1050-1058
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Choi, Kiri; Smith, Lucian P; Medley, J Kyle et al. (2016) phraSED-ML: A paraphrased, human-readable adaptation of SED-ML. J Bioinform Comput Biol 14:1650035
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Neal, Maxwell L; Cooling, Michael T; Smith, Lucian P et al. (2014) A reappraisal of how to build modular, reusable models of biological systems. PLoS Comput Biol 10:e1003849
Bergmann, Frank T; Adams, Richard; Moodie, Stuart et al. (2014) COMBINE archive and OMEX format: one file to share all information to reproduce a modeling project. BMC Bioinformatics 15:369
Neal, M L; Galdzicki, M; Gallimore, J T et al. (2014) A C library for retrieving specific reactions from the BioModels database. Bioinformatics 30:129-30

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