# StochSS: A Next-Generation Toolkit for Simulation-Driven Biological Discovery

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA SANTA BARBARA · 2022 · $537,223

## Abstract

Project Summary
 The development of a mathematical model is critical to the understanding of complex biological processes because it codifies current understanding so that it can be tested against existing data. A good model
with sufficient detail can be used to identify potential points of intervention (for example, drug targets) at
which an undesired outcome (for example, effects of disease) of the process might be altered. Model development proceeds through a cycle of model building, simulation of the model under numerous conditions, and
comparison to experimental data. The cycle is repeated and often augmented by new experiments to capture
additional data, until the resulting model can plausibly explain the data. Tremendous amounts of time and
effort must be devoted to finding and/or developing tools to analyze the model and compare it to the data,
 fit the parameters and assess the effects of typically large amounts of uncertainty in both the data and the
parameters, simulate the model and analyze the simulation data, refine the model to better capture our
increased understanding at each stage of the process, decide which additional experiments would add most
to our understanding, etc. Our objective in the proposed work is to facilitate and accelerate the modeling
process by providing state of the art, well-integrated tools to report complete and informative results at each
stage, enabling the modeler and the experimentalist to focus on what they do best: scientific discovery.
 This is a renewal proposal that builds on the capabilities and infrastructure developed in the current
project. In that work we developed StochSS, a novel Software-as-a-Service offering for quantitative modeling
of biochemical networks capable of seamless deployment in public cloud environments. StochSS does an
excellent job of supporting two of the major steps of the modeling process: Model Building - taking your
model description and putting it into a form that the StochSS simulation engines can work with, and
Simulation -  performing the simulations to produce the results.
 The proposed project has three complementary Aims. The first is to further develop StochSS's core
capabilities and to take the steps that will ensure its long-term sustainability; the second is to develop a
Model Development Toolkit, and the third is to develop a Model Exploration Toolkit. Both of these toolkits
will be integrated into our existing StochSS Model Building and Simulation environment and will leverage
our existing software infrastructure for cloud computing.
Aim 1. Core Capabilities and Long-Term Sustainability This aim has three sub-aims: (1) instituting
practices that will help ensure community involvement and better long-term sustainability of StochSS beyond
NIH funding, (2) extending core StochSS functional capabilities, and (3) improving compatibility with other
software via support for standard data formats.
Aim 2. Model Development Toolkit Develop and integrate tools to faci...

## Key facts

- **NIH application ID:** 10244992
- **Project number:** 5R01EB014877-07
- **Recipient organization:** UNIVERSITY OF CALIFORNIA SANTA BARBARA
- **Principal Investigator:** Linda R. Petzold
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $537,223
- **Award type:** 5
- **Project period:** 2012-05-15 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10244992

## Citation

> US National Institutes of Health, RePORTER application 10244992, StochSS: A Next-Generation Toolkit for Simulation-Driven Biological Discovery (5R01EB014877-07). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10244992. Licensed CC0.

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