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Explore cutting-edge models and methods for spatial transcriptomics in this comprehensive lecture by Ben Raphael at the Computational Genomics Summer Institute (CGSI) 2023. Delve into advanced techniques for analyzing spatially resolved transcriptomics data, including discrete and continuous spatial variation in gene expression. Learn about the Belayer model, which addresses the challenges of modeling spatial gene expression patterns. Discover methods for alignment and integration of spatial transcriptomics data across multiple tissue sections. Gain insights into the latest developments in partial alignment techniques for multi-slice spatially resolved transcriptomics data, such as the PASTE2 algorithm. This 41-minute talk provides a deep dive into the forefront of spatial transcriptomics research, offering valuable knowledge for computational biologists, genomics researchers, and bioinformaticians working with spatially resolved gene expression data.
