Toward Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-Based Convolutional Encoders

0301 basic medicine FOS: Computer and information sciences Computer Science - Machine Learning Computer Science - Artificial Intelligence drug sensitivity prediction; computational systems biology; machine learning; drug discovery; multiscale; multimodal; attention; CNN; RNN; explainability; interpretability; molecular networks; molecular fingerprints; GDSC; SMILES; gene expression; drug sensitivity; anticancer compounds; IC50; EC50; lead discovery; personalized medicine; precision medicine GDSC precision medicine anticancer compounds, Antineoplastic Agents Machine Learning (stat.ML) IC50 Quantitative Biology - Quantitative Methods RNN Machine Learning (cs.LG) drug discovery 03 medical and health sciences Deep Learning Statistics - Machine Learning explainability computational systems biology Humans molecular networks drug sensitivity lead discovery Quantitative Methods (q-bio.QM) drug sensitivity prediction molecular fingerprints 0303 health sciences multimodal deep learning personalized medicine SMILES anticancer compounds attention EC50 Artificial Intelligence (cs.AI) machine learning multiscale Drug Design FOS: Biological sciences gene expression Neural Networks, Computer interpretability Algorithms CNN
DOI: 10.1021/acs.molpharmaceut.9b00520 Publication Date: 2019-10-16T21:54:10Z
ABSTRACT
ISSN:1543-8384<br/>ISSN:1543-8392<br/>Molecular Pharmaceutics, 16 (12)<br/>
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