Prediction of drug targets for specific diseases leveraging gene perturbation data: A machine learning approach

Abstract excerpt

Identification of the correct targets is a key element for successful drug development. However, there are limited approaches for predicting drug targets for specific diseases using omics data, and few have leveraged expression profiles from gene perturbations. We present a novel computational target discovery approach based on machine learning(ML) models. ML models are first trained on drug-induced expression pro...

Topics

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• Algorithms
• Area Under Curve
• Computer Simulation
• Data Mining
• Drug Discovery
• Molecular Targeted Therapy
• Neural Networks, Computer
• Reproducibility of Results

Identifiers and source

Literature Corpus work

e7acd4cd-59c8-5934-b0b7-dc9d93099d2b

DOI

10.1101/2021.12.01.470692