DeepDTA: deep drug-target binding affinity prediction

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DeepDTA: deep drug-target binding affinity prediction

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im September 2018 veröffentlichter wissenschaftlicher Artikel

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wetenschappelijk artikel

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наукова стаття, опублікована у вересні 2018

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DeepDTA: deep drug-target binding affinity prediction

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DeepDTA: deep drug-target binding affinity prediction

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DeepDTA: deep drug-target binding affinity prediction

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DeepDTA: deep drug-target binding affinity prediction

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DeepDTA: deep drug-target binding affinity prediction

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DeepDTA: deep drug-target binding affinity prediction

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P1476

DeepDTA: deep drug-target binding affinity prediction

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Arzucan Özgür

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Elif Ozkirimli

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Hakime Öztürk

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P2860

UniProt: the Universal Protein knowledgebase

Identification of common molecular subsequences

Deep learning

A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking

Fast model-based protein homology detection without alignment

Too many roads not taken

Comprehensive analysis of kinase inhibitor selectivity

Computational Prediction of DrugTarget Interactions Using Chemical, Biological, and Network Features.

Some case studies on application of "r(m)2" metrics for judging quality of quantitative structure-activity relationship predictions: emphasis on scaling of response data.

Low-Quality Structural and Interaction Data Improves Binding Affinity Prediction via Random Forest.

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i821-i829

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scholarly article

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10.1093/BIOINFORMATICS/BTY593

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English

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2018-09-01T00:00:00Z

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30423097

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1801.10193

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computational mathematics

molecular biology

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6129291

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