# A Spatially Resolved Molecular Atlas of Human Endothelium

> **NIH NIH U54** · CALIFORNIA INSTITUTE OF TECHNOLOGY · 2021 · $99,999

## Abstract

Project Abstract
Recent advances in imaging and genomics are revolutionizing our understanding of human tissues. As these
two technologies become more intertwined and high-throughput, there is an increasing need for scalable
methods to interpret these data with single-cell resolution. In this Supplement, we seek to build on ongoing
work to develop scalable and accurate algorithms for single-cell analysis of spatial genomics data. We propose
to develop annotation software for annotating individual cells, their cell types, and functional tissue units in
multiplexed imaging data. This software will be essential to produce training data to power the next generation
of deep learning models for analyzing multiplexed imaging data.

## Key facts

- **NIH application ID:** 10411809
- **Project number:** 3U54HL145611-04S1
- **Recipient organization:** CALIFORNIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Long Cai
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $99,999
- **Award type:** 3
- **Project period:** 2018-09-20 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10411809

## Citation

> US National Institutes of Health, RePORTER application 10411809, A Spatially Resolved Molecular Atlas of Human Endothelium (3U54HL145611-04S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10411809. Licensed CC0.

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