# Core C- Molecular Regulation of Stem Cell Aging, Bioinformatics Core

> **NIH NIH P01** · STANFORD UNIVERSITY · 2020 · $127,585

## Abstract

SUMMARY
There is a shared need for genomic and other high dimensional data analysis among project
investigators. The Bioinformatics Core will establish a centralized, intelligent and robust
computational platform for high dimensional data analysis powered by a well-developed open
source software code base that will integrate novel techniques to more quantitatively map
chromatin and epigenetic changes during aging. To accelerate the computational aims of this
Program Project, the Core will lead a collaborative endeavor 1) to improve data accessibility and
security by implementing a NIH and GEO compliant database solution, 2) to promote
bioinformatics collaboration and reproducibility by implementing an application programming
interface (API) that interconnects analysis software and establishes a shared and well
documented development and analysis language, and 3) to enable facile data exploration and
interpretation by creating web based portals for project specific data analysis and visualization.
Through these Aims, this central resource for the Molecular Regulation of Stem Cell Aging
Program Project will promote intra-lab interactions and coordinate high dimensional data
analysis to help meet the broader goals of better understanding the epigenetic regulation of
aging in stem cells.

## Key facts

- **NIH application ID:** 9934977
- **Project number:** 5P01AG036695-09
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Charles Yang Lin
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $127,585
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9934977

## Citation

> US National Institutes of Health, RePORTER application 9934977, Core C- Molecular Regulation of Stem Cell Aging, Bioinformatics Core (5P01AG036695-09). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9934977. Licensed CC0.

---

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