【分子指纹】化学分子指纹的概念和应用（非常重要）-CSDN博客
2024年11月15日 · 分子指纹(Molecular fingerprints)可以低计算成本的方式表示大规模化学数据集中化合物的化学(结构、物理化学等)性质。 它们在将化学数据集中的分子转换为适合于计算方 …
分子指纹及其在虚拟筛选中的应用 - 墨灵格的博客
2019年1月29日 · 常见的分子指纹方法包括基于子结构的指纹(substructure key-based fingerprint)，基于拓扑或路径的指纹(topological or path-based fingerprint)和圆形指纹(circular …
One molecular fingerprint to rule them all: drugs, biomolecules, …
2020年6月12日 · MAP4 is a new molecular fingerprint suitable for drugs, biomolecules, and the metabolome and can be adopted as a universal fingerprint to describe and search chemical …
四种分子指纹的介绍：Substructure Fingerprint ... - CSDN博客
2024年10月24日 · 本教程介绍一种方法叫做"分子指纹（molecular fingerprint）"，这是一种简单的表示主法，对于小分子类药物来说通常工作得很好。 In [1] : import deepchem as dc …
An overview of molecular fingerprint similarity search in virtual ...
Molecular fingerprints encode properties of small molecules and assess their similarities computationally through bit string comparisons. Based on the similarity to a biologically active …
Development of Natural Compound Molecular Fingerprint (NC-MFP…
2020年1月22日 · We show that NC-MFP is a robust molecular fingerprint in classifying NC structures and explaining biological activities on target proteins. Therefore, we conclude that …
Efficient and Explainable Virtual Screening of Molecules through ...
5 天之前 · A molecular graph-based deep learning algorithm has been used to encode molecular substructure and generate fingerprints. The graph convolutional neural network (GCN) …
Molecular fingerprints: : application and techniques - ACM Digital …
3 天之前 · Boldini, D., Ballabio, D., Consonni, V., Todeschini, R., Grisoni, F. and Sieber, S.A. Effectiveness of molecular fingerprints for exploring the chemical space of ...
Comparative analysis of molecular fingerprints in prediction of …
Choosing an optimal fingerprint type to represent molecular features is an important step in computational drug discovery. To this end, we systematically compared 11 variants of such …
Fingerprints of molecular reactivity | Nature Reviews Chemistry
2020年4月6日 · The group tested this structure-based machine learning approach to predict common molecular properties such as HOMO–LUMO gaps and then to predict …