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Alignment, Integration, and Modeling of Spatial Transcriptomics Data

Offered By: Computational Genomics Summer Institute CGSI via YouTube

Tags

Computational Biology Courses Bioinformatics Courses Genomics Courses Statistical Modeling Courses Gene Expression Courses Data Integration Courses Single-Cell Analysis Courses Spatial Transcriptomics Courses

Course Description

Overview

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Explore cutting-edge research in spatial transcriptomics data analysis through this comprehensive conference talk by Ben Raphael, Professor of Computer Science at Princeton University. Delve into advanced techniques for alignment, integration, and modeling of spatial transcriptomics data, drawing insights from three related research papers. Learn about innovative approaches such as the Belayer method for modeling discrete and continuous spatial variation in gene expression, and the STARCH algorithm for copy number and clone inference from spatial transcriptomics data. Gain valuable knowledge on the latest advancements in computational genomics and their applications in understanding complex biological systems.

Syllabus

Ben Raphael | Alignment, Integration, and Modeling of Spatial Transcriptomics Data | CGSI 2022


Taught by

Computational Genomics Summer Institute CGSI

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