Improving MatchMaker - A Deep Learning Based Drug Synergy Predictor

2020-2021 Fall
Faculty Department of Project Supervisor: 
Faculty of Arts & Social Sciences
Number of Students: 

Drug combination therapies provides increased efficacy and are widely used for cancer therapies. However, experimentally searching combinations for synergistic interaction. We proposed a deep learning based model, MatchMaker that predicts drug synergy scores using drug chemical structure information and gene expression profiles of cell lines. The project will work on improving this model in various aspects.


The applicants should have experience using Deep Learning models.

Please contact for details with your CV and transcript.

Related Areas of Project: 
Computer Science and Engineering
Electronics Engineering
Industrial Engineering

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