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MSc Thesis Proposal Announcement of Sheena Hora: "Prediction of cell-cell Interactions in scRNA-seq data using Graph Convolutional Networks "

Friday, December 3, 2021 - 13:00 to 14:30

SCHOOL OF COMPUTER SCIENCE 

The School of Computer Science is pleased to present… 

MSc Thesis Proposal by: Sheena Hora 

Date: Friday December 3,2021    
Time:  1:00pm – 2:30pm 
Passcode: If interested in attending this event, contact the Graduate Secretary at csgradinfo@uwindsor.ca with sufficient notice before the event to obtain the passcode

Abstract:   

Rapid advances in single-cell technologies have given complex biological systems a new perspective. Researchers can identify potential information such as gene regulatory links, differential expressions, and developmental trajectories of different cell lineages using single-cell studies at the cellular and gene levels. Identification of cell-cell interactions is one of the significant areas of research. Cell-cell interactions regulate organismal development, homeostasis, and single-cell functions. The disease occurs when cells do not interact properly or decode molecular messages improperly. Thus, identifying and quantifying intercellular signaling pathways has become a common analysis carried out across a variety of fields. The recent advances in RNA sequencing technologies, have enabled routine analyses of intercellular signaling from bulk and single-cell data sets. For multicellular organisms, cell-to-cell communication is critical. We introduce a novel pipeline to identify cell-cell interactions in single cell RNA-seq data using graph convolutional networks. Pipeline steps include pre-processing of the data, followed by cell graph construction, and then identifying cell-cell interactions using graph convolutional networks. 
 
Keywords: single cell RNA-seq, Graph Convolutional Networks, cell-cell interactions 
 

MSc Thesis Committee:  

Internal Reader: Dr. Jianguo Lu         
External Reader: Dr. Ning Zhang        
Advisor: Dr. Luis Rueda 

 MSc Thesis Proposal Announcement   Vector Institute in Artificial Intelligence approved artificial intelligence topic logo

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