# Developing novel algorithms for spatial molecular profiling technologies

> **NIH NIH R01** · UT SOUTHWESTERN MEDICAL CENTER · 2021 · $370,939

## Abstract

Project Summary
The location, timing and abundance of mRNA and proteins within a tissue underlie the basic molecular
mechanisms of cell functions and physiological and pathological developments. For example, the study of
expression of thousands of genes simultaneously at different locations could reveal great insights into embryo
development, the cooperation of molecular and cellular processes for high-order mental functions, and the
molecular basis and clinical impact of intra-tumor heterogeneity. Recent technology breakthroughs in spatial
molecular profiling (SMP), including both imaging-based technologies and sequencing-based technologies, have
enabled the comprehensive molecular characterization of single cells while preserving their spatial and
morphological contexts. Due to the huge potential to deepen our understanding of the molecular mechanisms of
cellular and physiological phenotypes, SMP technologies are rapidly gaining attention and a large amount of
such data will be generated. However, there are only few computational methods developed to analyze such
rich but complex data, and the limitations of computational methods lead to such valuable data being largely
under-used. The overarching goal of this study is to develop computational methods to analyze SMP data to
characterize detailed molecular spatial distributions and associate such information with cellular phenotypes and
physiological phenotypes. The specific aims are as follows: 1. develop novel spatio-statistical methods to
characterize spatial distributions of gene expression; 2. develop computational methods to characterize cellular
spatial organizations and investigate their relationship with molecular spatial distributions and disease status; 3.
develop user-friendly software to facilitate researchers in SMP data analysis and visualization. In order to achieve
this goal, we have assembled a strong team with complementary expertise in single-cell genomics, tissue image
analysis, spatial modelling, machine learning and software development. If implemented successfully, this
platform will greatly facilitate users in understanding molecular and cellular spatial organization in biological
tissues and provide comprehensive insights into the underlying biological processes.

## Key facts

- **NIH application ID:** 10197672
- **Project number:** 1R01GM141519-01
- **Recipient organization:** UT SOUTHWESTERN MEDICAL CENTER
- **Principal Investigator:** Guanghua Xiao
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $370,939
- **Award type:** 1
- **Project period:** 2021-08-01 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10197672

## Citation

> US National Institutes of Health, RePORTER application 10197672, Developing novel algorithms for spatial molecular profiling technologies (1R01GM141519-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10197672. Licensed CC0.

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