Overview

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 comprehensive models, the center is making 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 are striving to build broadly-applicable domain-independent tools. To ensure the center’s tools advance modeling, we will begin by testing on tools on systems biology modeling in conjunction with several motivating projects that span a wide range of modeling methods and applications.

To further advance the understandability, reproducibility, and reusability of biomedical modeling, the center is also (1) promoting the importance of reproducible modeling by organizing meetings and publishing perspectives; (2) training researchers to conduct modeling reproducibly by organizing workshops and publishing tutorials; and (3) helping researchers and journals build, annotate, simulate, analyze, and verify models.

We anticipate that this unique center will accelerate the development of comprehensive predictive models by enhancing the understandability, reusability, and reproducibility of biomedical modeling.

Team

Model building

Arthur Goldberg
Arthur GoldbergCo-Investigator
Associate Professor, Icahn School of Medicine at Mount Sinai
Jonathan Karr
Jonathan KarrProject Director
Fellow, Icahn School of Medicine at Mount Sinai
Yosef Roth
Yosef Roth
Research Assistant, Icahn School of Medicine at Mount Sinai
Herbert Sauro
Herbert SauroDirector
Associate Professor, University of Washington
Balazs Szigeti
Balazs Szigeti
Postdoctoral Scholar, Icahn School of Medicine at Mount Sinai

Model and simulation annotation

Dan Cook
Dan CookCo-Investigator
Research Professor, University of Washington
John Gennari
John GennariProject Director
Associate Professor, University of Washington
Graham Kim
Graham Kim
Graduate Student, University of Washington
David Nickerson
David NickersonCo-Investigator
Senior Research Fellow, University of Auckland

Online simulation and visualization

Michael Blinov
Michael BlinovCo-Investigator
Assistant Professor, University of Connecticut School of Medicine
Ion Moraru
Ion MoraruProject Director
Professor, University of Connecticut School of Medicine
Dan Vasilescu
Dan Vasilescu
Software Developer, UConn Health

Technology integration, education & outreach

John Gennari
John GennariProject Director
Associate Professor, University of Washington
Jonathan Karr
Jonathan KarrProject Director
Fellow, Icahn School of Medicine at Mount Sinai
Ion Moraru
Ion MoraruProject Director
Professor, University of Connecticut School of Medicine
Herbert Sauro
Herbert SauroDirector
Associate Professor, University of Washington