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资源简介：
Dataset for the publication: Bayesian Optimization for Conformer Generation
应用场景：
创建时间：
2019-05-13
相关数据集
Conformer models and training datasets
Here you can find pre-trained machine learning models that generate predictions from conformer ensembles. You can also find the PyTorch datasets that were used to train them.
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A Double-Twist Möbius-Aromatic Conformation of [14]Annulene
B3LYP and KMLYP/6-31G(d) calculations predict a double-helical and chiral conformation of [14]annulene with the topological properties of a double-twist Möbius band as highly aromatic; its energy with
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Data for Applying atomistic neural networks to bias conformer ensemble towards bioactive-like conformations
This folder contains all data required to reproduce the work "Applying atomistic neural networks to bias conformer ensemble towards bioactive-like conformations".
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Better Informed Distance Geometry: Using What We Know To Improve Conformation Generation
Small organic molecules are often flexible, i.e., they can adopt a variety of low-energy conformations in solution that exist in equilibrium with each other. Two main search strategies are used to gen
NIAID Data Ecosystem60
Better Informed Distance Geometry: Using What We Know To Improve Conformation Generation
Small organic molecules are often flexible, i.e., they can adopt a variety of low-energy conformations in solution that exist in equilibrium with each other. Two main search strategies are used to gen
NIAID Data Ecosystem40
