计算机科学
下部结构
相似性(几何)
班级(哲学)
表征(材料科学)
指纹(计算)
数据挖掘
算法
口译(哲学)
人工智能
模式识别(心理学)
拓扑(电路)
数学
物理
组合数学
图像(数学)
工程类
结构工程
光学
程序设计语言
作者
David Rogers,Mathew Hahn
摘要
Extended-connectivity fingerprints (ECFPs) are a novel class of topological fingerprints for molecular characterization. Historically, topological fingerprints were developed for substructure and similarity searching. ECFPs were developed specifically for structure-activity modeling. ECFPs are circular fingerprints with a number of useful qualities: they can be very rapidly calculated; they are not predefined and can represent an essentially infinite number of different molecular features (including stereochemical information); their features represent the presence of particular substructures, allowing easier interpretation of analysis results; and the ECFP algorithm can be tailored to generate different types of circular fingerprints, optimized for different uses. While the use of ECFPs has been widely adopted and validated, a description of their implementation has not previously been presented in the literature.
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