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Updated: Sep 6, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
Emerging artificial intelligence applications in Spatial Transcriptomics analysis
Yijun Li1, Stefan Stanojevic2, Lana X Garmire1,2
1Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Abstract:
Spatial transcriptomics (ST) has advanced significantly in the last few years. Such advancement comes with the urgent need for novel computational methods to handle the unique challenges of ST data analysis. Many artificial intelligence (AI) methods have been developed to utilize various machine learning and deep learning techniques for computational ST analysis. This review provides a comprehensive and up-to-date survey of current AI methods for ST analysis.
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