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A Comparative Analysis of Gene Expression Profiling by Statistical and Machine Learning Approaches
A collection of machine learning models including logistic regression, multilayer perceptron, and graph neural network are trained to classify samples according to their cancer type.
Studying Limits of Explainability by Integrated Gradients for Gene Expression Models
The scientific questions are formulated as classical learning problems on tabular data or on graphs, e. g. phenotype prediction from gene expression data.
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