AI and Machine Learning in Single Cell Genomics - Day 2

AI and Machine Learning in Single Cell Genomics - Day 2

Georgia Tech Research via YouTube Direct link

Spatial Morphoproteomic Features Predict Uniqueness of Immune Microarchitectures and Responses in Lymphoid Follicles, Thomas Hu, Georgia Tech

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4 of 10

Spatial Morphoproteomic Features Predict Uniqueness of Immune Microarchitectures and Responses in Lymphoid Follicles, Thomas Hu, Georgia Tech

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AI and Machine Learning in Single Cell Genomics - Day 2

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  1. 1 Spatial Tissue Profiling: from a Novelty to a Discovery Powerhouse, Ioannis Vlachos, Harvard Medical School
  2. 2 Studying Single Cells Through Multi-Omics and Spatiotemporal Context, Xiuwei Zhang, Georgia Tech
  3. 3 BREAK
  4. 4 Spatial Morphoproteomic Features Predict Uniqueness of Immune Microarchitectures and Responses in Lymphoid Follicles, Thomas Hu, Georgia Tech
  5. 5 Spatial Location Encoded in Gene Expression: A New Analytical Approach to Spatial Transcriptomics, Yeojin Kim, Georgia Tech
  6. 6 parDoub: Parallelized Doublet Detection for scRNA-seq, Kiersten Campbell, Emory
  7. 7 Discovering Cell Types and States from Reference with Heterogeneous Single-Cell ATAC-Seq Features, Yuqi Cheng, Georgia Tech
  8. 8 LUNCH BREAK/POSTER SESSION OFFLINE
  9. 9 Awards Session
  10. 10 Closing Remarks, Manoj Bhasin & Saurabh Sinha

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