# Thinking outside the cell: Leveraging HuBMAP data to build the human ECM atlas

> **NIH NIH U01** · UNIVERSITY OF ILLINOIS AT CHICAGO · 2023 · $150,000

## Abstract

Abstract:
NIH's Human BioMolecular Atlas Program (HuBMAP) is an ambitious endeavor striving to create
a comprehensive, high-resolution atlas of the human body. It relies on collaborations among
multiple research groups and the integration of diverse, complex datasets. Adhering to FAIR
principles (Findability, Accessibility, Interoperability, and Reusability) is essential for enabling
seamless sharing and reuse of valuable data among researchers and clinicians. This becomes
increasingly important as the HuBMAP program expands, and more collaborations emerge from
the project. In this proposal, we aim to enhance the data interoperability and reusability of existing
mass spectrometry-based data within HuBMAP. Our proposed efforts serve as a natural extension
of our current work in the parent U01 demo project (Thinking outside the cell: Leveraging HuBMAP
data to build the human ECM atlas), which focuses on constructing the first extracellular matrix
atlas for HuBMAP. The first aim plans to develop quality control tools and a unified proteomics
data processing pipeline to examine the current landscape of HuBMAP data and facilitate
comparisons across various experiments and tissue types. This effort will help us to better
evaluate the data quality and identify key aspects for improvement. Our second aim concentrates
on the cross-validation of diverse protein quantitation technologies currently utilized in HuBMAP.
The extensive scope and depth of current HuBMAP datasets uniquely position us to compare
various protein quantitation methods employed by different tissue mapping centers. This effort
will help us to better understand the robustness, interchangeability, and suitability of these
techniques. Collectively, our proposed research will significantly improve data interoperability and
reusability within the HuBMAP project and provide guidelines for best practices in future data
acquisition.

## Key facts

- **NIH application ID:** 10816692
- **Project number:** 3U01HG012680-02S1
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT CHICAGO
- **Principal Investigator:** Yu Gao
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $150,000
- **Award type:** 3
- **Project period:** 2022-07-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10816692

## Citation

> US National Institutes of Health, RePORTER application 10816692, Thinking outside the cell: Leveraging HuBMAP data to build the human ECM atlas (3U01HG012680-02S1). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10816692. Licensed CC0.

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