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Found 2 papers, 1 papers with code
Machine learning-assisted search for novel coagulants: when machine learning can be efficient even if data availability is low
Design of new drugs is a challenging process: a candidate molecule should satisfy multiple conditions to act properly and make the least side-effect -- perfect candidates selectively attach to and influence only targets, leaving off-targets intact.
High throughput screening with machine learning
This study assesses the efficiency of several popular machine learning approaches in the prediction of molecular binding affinity: CatBoost, Graph Attention Neural Network, and Bidirectional Encoder Representations from Transformers.
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