National Human Genome Research Institute 5R01HG012875-04

Machine learning methods for interpreting spatial multi-omics data

Development of innovative computational tools using machine learning to analyze and integrate spatial multi-omics data, enabling insights into cell types, spatial organization, and gene regulation in various biological systems.

Description

This project aims to develop computational tools for spatial multi-omics data analysis, with applications in developmental biology and disease research. The project will be open-source and collaborative. It seeks to develop interpretable and rigorous machine learning models to characterize diverse cell types, their spatial organization and interactions, and their underlying gene circuitry from combining transcriptomic, proteomic, epigenomic and imaging datasets.

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