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UID:20250511T230931EDT-4864zGDNxd@132.216.98.100
DTSTAMP:20250512T030931Z
DESCRIPTION:Souvik Seal\, PhD\n\nAssistant Professor of Biostatistics and B
 ioinformatics\n	Dept of Public Health Sciences\n	and Hollings Cancer Center 
 | MUSC\n\nWHEN: Wednesday\, November 13\, 2024\, from 3:30 to 4:30 p.m.\n	W
 HERE: Hybrid | 2001 ɬÀï·¬ College Avenue\, Room 1201\; Zoom\n	NOTE: Souvik
  Seal will be presenting from South Carolina\n\nAbstract\n\nAdvancements i
 n spatial omics technologies have facilitated the measurement of expressio
 n profiles of thousands of molecules\, including genes (spatial transcript
 omics)\, glycans (imaging mass spectrometry)\, and immune proteins (multip
 lex immunofluorescence)\, across spatial locations (spots\, cells\, or pix
 els) within tissues. However\, there remains a significant lack of statist
 ical methods for detecting spatial variations in the coordinated expressio
 n of molecule pairs. In the first part of this talk\, I will present a poi
 nt process-based framework for summarizing and testing differential spatia
 l co-expression in spatial proteomics datasets. In the latter part\, I wil
 l introduce a Bayesian shrinkage-based approach for identifying spatial co
 -expression in spatial transcriptomics and imaging mass spectrometry datas
 ets.\n\nSpeaker Bio\n\nSouvik Seal is an Assistant Professor of Biostatist
 ics and Bioinformatics at the Department of Public Health Sciences and Hol
 lings Cancer Center\, Medical University of South Carolina (MUSC)\, since 
 2023. Previously\, he was a post-doctoral fellow under Prof. Debashis Ghos
 h at the University of Colorado\, focusing on statistical methods for Sing
 le-cell Imaging and Multi-omics network analysis. He earned his Ph.D. in B
 iostatistics from the University of Minnesota in 2020\, where his thesis c
 entered on Genome-wide Association Analysis in large-scale biobank studies
 . His research interests lie in Spatial Statistics for Multi-omics and Sta
 tistical Genetics. For more information\, please visit: https://sealx017.g
 ithub.io/.\n
DTSTART:20241113T203000Z
DTEND:20241113T213000Z
SUMMARY:Studying molecular spatial co-expression in Spatial Omics datasets
URL:/epi-biostat-occh/channels/event/studying-molecula
 r-spatial-co-expression-spatial-omics-datasets-360431
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