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Leash Bio - Predict New Medicines with BELKA
Leash Bio - 利用BELKA预测新型药物
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创建时间：
2024-04-16
相关数据集
Extreme Gradient Boosting as a Method for Quantitative Structure–Activity Relationships
In the pharmaceutical industry it is common to generate many QSAR models from training sets containing a large number of molecules and a large number of descriptors. The best QSAR methods are those th
NIAID Data Ecosystem50
Results from OR'ing or AND'ing the predictions of Template CoMFA with Tanimoto NN predictions.
Results from OR'ing or AND'ing the predictions of Template CoMFA with Tanimoto NN predictions.
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The index of ideality of correlation: QSAR studies of hepatitis C virus NS3/4A protease inhibitors using SMILES descriptors
Robust and reliable QSAR models were developed to predict half-maximal inhibitory concentration (IC 50 ) values of hepatitis C virus NS3/4A protease inhibitors from the Monte Carlo technique.
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Knowledge-Based Artificial Intelligence System for Drug Prioritization
In silico drug prioritization may be a promising and time-saving strategy to identify potential drugs, standing as a faster and more cost-effective approach than de novo approaches. In recent years, a
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Performance of AI tools across pharmacological domain.
Performance of AI tools across pharmacological domain.
Figshare2025-12-16 更新20
