# From intra to intercellular regulatory networks that define cell type identity

> **NIH NIH R35** · JOHNS HOPKINS UNIVERSITY · 2024 · $138,225

## Abstract

Project Abstract
Cell fate engineering, for example the directed differentiation of pluripotent stem cells, holds great promise for
disease modeling, drug screening, and regenerative medicine. However, our ability to engineering cell fate with
fidelity has been impeded by an incomplete understanding of inter- and intracellular networks that govern
differentiation, and by the lack of adequate computational tools to distill testable hypothesis from the mountains
of data coming from single cell omics technologies. In the parent award of this grant, we are addressing the
following unanswered questions and unmet challenges that emerged from our prior work. First, we are
extending our computational methods that assess the outcomes of cell fate engineering to more data types,
thus increasing the comprehensiveness of their results. Second, we are substantially improving and extending
our regulatory network tools so that they are statistically calibrated and so that they can ingest chromatin
accessibility and expression data simultaneously to discover binding site motifs of orphan transcription factors.
Third, we are devising computational methods to generate reliable cell fate engineering recipes that account
for not only transcriptional networks but also how signaling pathways inform them, and that account for
temporal dynamics. The Imaging system that we are requesting in this supplement grant is crucial for us to
experimentally assess the predictions that emerge from our computational algorithms to improve the directed
differentiation of pluripotent stem cells to, first, mesoderm sub-types, and second, to articular chondrocytes.
Meeting these goals will shed light on how signaling pathways and intracellular regulatory networks interact
during differentiation, and it will help to make cell fate engineering more reliable and controllable.

## Key facts

- **NIH application ID:** 11037217
- **Project number:** 3R35GM124725-08S1
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Patrick Cahan
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $138,225
- **Award type:** 3
- **Project period:** 2017-08-01 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11037217

## Citation

> US National Institutes of Health, RePORTER application 11037217, From intra to intercellular regulatory networks that define cell type identity (3R35GM124725-08S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/11037217. Licensed CC0.

---

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