The long-term goal of the Center for Reproducible Biomedical Modeling is to achieve comprehensive predictive models of biological systems, such as whole-cell models, that can guide precision medicine and synthetic biology. One promising way to build comprehensive models is to combine models of individual biological processes. This requires understandable, reproducible, reusable, and composable models of individual biological processes. Unfortunately, few existing models are reproducible, reusable, or composable. For example, many reported models are not published, many reported simulation results are not reproducible, and few models are annotated. Recently, researchers have developed several standard representations such as SBML and SED-ML to make models reusable and make simulation results reproducible. However, it is still difficult to understand, reproduce, and combine models because we lack tools for recording the data sources and assumptions used to build models, we lack tools for annotating the meanings of variables and equations, and we lack a universal simulator. Toward our long-term goal of achieving comprehensive models, we will make models understandable, reproducible, reusable, and composable by (1) developing these missing model building, annotation, and simulation tools and (2) combining these and other existing tools into a user-friendly reproducible modeling workflow. Ultimately, we believe this workflow will help modelers create comprehensive models that can guide medicine and bioengineering. We will strive to build broadly-applicable domain-independent tools. However, to help us to test our tools, we will initially focus on tools for systems biology models of cells. To ensure the center's tools advance modeling, the tools will be developed in conjunction with several motivating collaborative and service projects that span a wide range of modeling methods and biological and application domains. To further advance the understandability, reproducibility, and reusability of biomedical modeling, we will (1) promote the importance of reproducible modeling by organizing meetings and publishing perspectives; (2) train researchers to conduct modeling reproducibly by organizing workshops and publishing tutorials; and (3) help researchers and journals build, annotate, simulate, analyze, and verify models. The center would be one of the first large-scale efforts to make biomedical modeling reproducible, and the center would be timely given the increasing concern about the irreproducibility of biomedical research. We anticipate that this unique center will accelerate the development of comprehensive predictive models by enhancing the understandability, reusability, and reproducibility of biomedical modeling.

Public Health Relevance

Our long-term goal is to achieve comprehensive predictive models that can guide precision medicine and syn- thetic biology. Toward this goal, we will make models understandable, reproducible, and reusable by (1) devel- oping tool for reproducibly building, simulating, and analyzing models; (2) assembling these tools into a user- friendly workflow; (3) providing the community services for annotating, simulating, and validating models; (4) promoting the importance of reproducibility; and (5) training researchers to conduct modeling reproducibility. These efforts will enhance the reproducibility of modeling and, in turn, enable comprehensive models.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Biotechnology Resource Grants (P41)
Project #
1P41EB023912-01A1
Application #
9460251
Study Section
Special Emphasis Panel (ZEB1)
Program Officer
Peng, Grace
Project Start
2018-06-13
Project End
2023-02-28
Budget Start
2018-06-13
Budget End
2019-02-28
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Washington
Department
Engineering (All Types)
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195