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Disease-Gene Associations
Neural Inductive Matrix Factorization for Predicting Disease-Gene Associations
Siqing Hou, M.S., Computer Science
Apr 18, 10:00
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11:30
B3 R5208
bioinformatics
machine learning
Disease-Gene Associations
In silico prioritization of undiscovered associations can help find causal genes of newly discovered diseases. Some existing methods are based on known associations and side information of diseases and genes. We exploit the possibility of using a neural network model, Neural Inductive Matrix Completion (NIMC) in disease-gene prediction.
