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Refinado por: Nome da Publicação: Journal Of Chemical Information And Modeling remover
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Deep Learning in Chemistry
Deep Learning in Chemistry
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Deep Learning in Chemistry

Mater, Adam C ; Coote, Michelle L

Journal of chemical information and modeling, 2019-06, Vol.59 (6), p.2545-2559 [Periódico revisado por pares]

United States: American Chemical Society

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2
Protein–Ligand Scoring with Convolutional Neural Networks
Protein–Ligand Scoring with Convolutional Neural Networks
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Protein–Ligand Scoring with Convolutional Neural Networks

Ragoza, Matthew ; Hochuli, Joshua ; Idrobo, Elisa ; Sunseri, Jocelyn ; Koes, David Ryan

Journal of chemical information and modeling, 2017-04, Vol.57 (4), p.942-957 [Periódico revisado por pares]

United States: American Chemical Society

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3
Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition
Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition
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Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition

Jaeger, Sabrina ; Fulle, Simone ; Turk, Samo

Journal of chemical information and modeling, 2018-01, Vol.58 (1), p.27-35 [Periódico revisado por pares]

United States: American Chemical Society

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4
Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery
Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery
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Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery

Preuer, Kristina ; Renz, Philipp ; Unterthiner, Thomas ; Hochreiter, Sepp ; Klambauer, G Uuml Nter

Journal of chemical information and modeling, 2018-09, Vol.58 (9), p.1736-1741 [Periódico revisado por pares]

United States: American Chemical Society

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5
AGL-Score: Algebraic Graph Learning Score for Protein–Ligand Binding Scoring, Ranking, Docking, and Screening
AGL-Score: Algebraic Graph Learning Score for Protein–Ligand Binding Scoring, Ranking, Docking, and Screening
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AGL-Score: Algebraic Graph Learning Score for Protein–Ligand Binding Scoring, Ranking, Docking, and Screening

Nguyen, Duc Duy ; Wei, Guo-Wei

Journal of chemical information and modeling, 2019-07, Vol.59 (7), p.3291-3304 [Periódico revisado por pares]

United States: American Chemical Society

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6
Conditional Molecular Design with Deep Generative Models
Conditional Molecular Design with Deep Generative Models
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Conditional Molecular Design with Deep Generative Models

Kang, Seokho ; Cho, Kyunghyun

Journal of chemical information and modeling, 2019-01, Vol.59 (1), p.43-52 [Periódico revisado por pares]

United States: American Chemical Society

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7
Critical Assessment of the Hildebrand and Hansen Solubility Parameters for Polymers
Critical Assessment of the Hildebrand and Hansen Solubility Parameters for Polymers
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Critical Assessment of the Hildebrand and Hansen Solubility Parameters for Polymers

Venkatram, Shruti ; Kim, Chiho ; Chandrasekaran, Anand ; Ramprasad, Rampi

Journal of chemical information and modeling, 2019-10, Vol.59 (10), p.4188-4194 [Periódico revisado por pares]

United States: American Chemical Society

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8
In Need of Bias Control: Evaluating Chemical Data for Machine Learning in Structure-Based Virtual Screening
In Need of Bias Control: Evaluating Chemical Data for Machine Learning in Structure-Based Virtual Screening
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In Need of Bias Control: Evaluating Chemical Data for Machine Learning in Structure-Based Virtual Screening

Sieg, Jochen ; Flachsenberg, Florian ; Rarey, Matthias

Journal of chemical information and modeling, 2019-03, Vol.59 (3), p.947-961 [Periódico revisado por pares]

United States: American Chemical Society

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9
Incorporating Explicit Water Molecules and Ligand Conformation Stability in Machine-Learning Scoring Functions
Incorporating Explicit Water Molecules and Ligand Conformation Stability in Machine-Learning Scoring Functions
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Incorporating Explicit Water Molecules and Ligand Conformation Stability in Machine-Learning Scoring Functions

Lu, Jianing ; Hou, Xuben ; Wang, Cheng ; Zhang, Yingkai

Journal of chemical information and modeling, 2019-11, Vol.59 (11), p.4540-4549 [Periódico revisado por pares]

United States: American Chemical Society

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10
Shape-Based Generative Modeling for de Novo Drug Design
Shape-Based Generative Modeling for de Novo Drug Design
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Shape-Based Generative Modeling for de Novo Drug Design

Skalic, Miha ; Jiménez, José ; Sabbadin, Davide ; De Fabritiis, Gianni

Journal of chemical information and modeling, 2019-03, Vol.59 (3), p.1205-1214 [Periódico revisado por pares]

United States: American Chemical Society

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