# Cell Modeling

> **NIH NIH P41** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $413,471

## Abstract

IV. TR&D2 - Abstract
The overall goal of this project is to develop the next generation computer simulation platform for spatially
realistic simulation and analysis of cellular and subcellular biochemistry. Cellular systems, especially in
neurons, are profoundly difficult to understand because of the interplay between spatial, biochemical and
molecular complexity that occurs on multiple levels of organization, from macromolecular assemblies to
synapse architecture to neural circuits. Biological complexity is daunting and scientific investigators must
persevere to finds ways to overcome it. This is important because Scientific Discovery is driven by testable
hypotheses which derive from our intuition and questions surrounding our current understanding of reality. But
when daunting complexity confounds our intuition we struggle to conceive new hypotheses and the cycle of
discovery grinds to a halt. Computational models allow investigators to probe the complex relationships
between biological components, obtain new insights and intuition -- the genesis of new hypotheses. The
MCell/CellBlender platform for cell modeling we are developing is expressly designed to fulfill this need,
providing insight and understanding of complex cellular systems. The cell modeling tools we develop here are
designed to mesh with the molecular, network, and image-derived modeling tools of TR&Ds 1, 3 and 4. The
tools will be used by our Driving Biomedical Project research partners to study neuronal and synaptic structure
and function and the intricate biochemical pathways involved in learning and memory in the brain. The detailed
level of understanding of these systems afforded by computational modeling of these systems will provide new
insights that may be applicable to many types of cell signaling pathways, and in particular should help to
elucidate how dysfunctions in cell signaling may contribute to neurological and psychiatric pathology.

## Key facts

- **NIH application ID:** 9990798
- **Project number:** 5P41GM103712-09
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** TERRENCE J SEJNOWSKI
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $413,471
- **Award type:** 5
- **Project period:** 2012-09-24 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9990798

## Citation

> US National Institutes of Health, RePORTER application 9990798, Cell Modeling (5P41GM103712-09). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9990798. Licensed CC0.

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