# Ontologies and software tools for describing reproducible biomodels and biosimulations

> **NIH NIH P41** · UNIVERSITY OF WASHINGTON · 2020 · $265,866

## Abstract

TECHNOLOGY RESEARCH & DEVELOPMENT 2: PROJECT SUMMARY
TR&D 2 aims to accelerate biomodeling through enhanced annotation of models, simulation experiments, and
simulation results. As models accumulate in public repositories, there is an opportunity to reuse models for
new studies and to combine models into comprehensive meta-models of entire biological systems. However, it
is currently challenging to reuse and combine models because few models are reproducible or understandable.
Consequently, modelers currently waste huge amounts of time trying to understand, reproduce, and combine
models published by other modelers, including other modelers in the same research group.
To make it easier to understand, reproduce, and combine models, we must make the assumptions, meanings,
and limitations of models explicit. To achieve this, we will develop schemas, ontologies, and software tools for
clearly describing (a) the data and assumptions used to build models, (b) the meaning of each variable and
equation in a model, (c) the meaning of each simulation prediction, and (d) the experimental validations that
give confidence in model predictions and which model predictions should be trusted.
We will also develop several software tools that use annotations to visualize, decompose, merge, and convert
models among Antimony, BioNetGen, BISEN, CellML, MATLAB, MML, Python, SBML, and SimBiology. We
will make it easy for modelers to use these tools by integrating them into our SemGen annotation software tool.
To ensure these tools accelerate biomodeling, this TR&D will be driven by four Collaborative Projects which
need enhanced annotation schemas and tools to understand, reproduce, reuse, and merge their models. The
Collaborative Projects will push us to develop user-friendly graphical interfaces to our tools, and we will pull the
Collaborative Projects to use our new annotations to annotate their models more deeply.
To further help researchers annotate their models, via several Service Projects, we will also provide several
journals, model repositories, and labs annotation services where modelers can submit models for validation
and annotation by an expert curator.
The methods, tools, and services provided by this TR&D will help modelers discover models for new studies,
better understand published models, and augment and merge models to test new hypotheses about
physiology and pathophysiology.
This TR&D builds on our extensive experience in (a) developing schemas for describing models including the
SemSim schema for describing physics-based models, (b) developing ontologies for describing biomedical
knowledge including the Ontology of Physics for Biology, and (c) developing software tools for annotating,
visualizing, and merging models including the SemGem software program and the PhysioMap visualization.

## Key facts

- **NIH application ID:** 9970229
- **Project number:** 5P41EB023912-03
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** JOHN H. GENNARI
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $265,866
- **Award type:** 5
- **Project period:** — → 2024-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9970229

## Citation

> US National Institutes of Health, RePORTER application 9970229, Ontologies and software tools for describing reproducible biomodels and biosimulations (5P41EB023912-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9970229. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*