Selected article for: "partition coefficient and separated task"
Author: Kaifu Gao; Duc Duy Nguyen; Rui Wang; Guo-Wei Wei
Title: Machine intelligence design of 2019-nCoV drugs
  • Document date: 2020_2_4
    • ID: 1qniriu0_26
    Snippet: Binding free energies are computed with four methods, namely, the latent space binding predictor (LS-BP), the 2D fingerprint predictor (2DFP), a 3D deep learning model trained with the mixture all datasets, including the dataset for coronaviral protease (denoted as "3DALL"), and finally, a 3D deep learning multitask model trained with the dataset for coronaviral protease as a separated task (denoted as 3DMT). Table 2 as references. Table 2 lists .....
    Document: Binding free energies are computed with four methods, namely, the latent space binding predictor (LS-BP), the 2D fingerprint predictor (2DFP), a 3D deep learning model trained with the mixture all datasets, including the dataset for coronaviral protease (denoted as "3DALL"), and finally, a 3D deep learning multitask model trained with the dataset for coronaviral protease as a separated task (denoted as 3DMT). Table 2 as references. Table 2 lists a few other druggable properties, including partition coefficient (logP), solubility (logS), and synthesizability.

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