Grouping of coefficients for the calculation of inter-molecular similarity and dissimilarity using 2D fragment bit-strings
J. Holliday, C. Hu, and P. Willett. Combinatorial Chemistry and High-Throughput Screening, 5 (2):
155-166(March 2002)
Abstract
This paper compares 22 different similarity coefficients when they are used for searching databases of 2D fragment bit-strings. Experiments with the National Cancer Institute s AIDS and IDAlert databases show that the coefficients fall into several well-marked clusters, in which the members of a cluster will produce comparable rankings of a set of molecules. These clusters provide a basis for selecting combinations of coefficients for use in data fusion experiments. The results of these experiments provide a simple way of increasing the effectiveness of fragment-based similarity searching systems.
%0 Journal Article
%1 holliday2002grouping
%A Holliday, John D
%A Hu, C Y
%A Willett, P
%D 2002
%J Combinatorial Chemistry and High-Throughput Screening
%K similarity similarity-multiheteroset
%N 2
%P 155-166
%T Grouping of coefficients for the calculation of inter-molecular similarity and dissimilarity using 2D fragment bit-strings
%U http://www.ncbi.nlm.nih.gov/pubmed/11966424
%V 5
%X This paper compares 22 different similarity coefficients when they are used for searching databases of 2D fragment bit-strings. Experiments with the National Cancer Institute s AIDS and IDAlert databases show that the coefficients fall into several well-marked clusters, in which the members of a cluster will produce comparable rankings of a set of molecules. These clusters provide a basis for selecting combinations of coefficients for use in data fusion experiments. The results of these experiments provide a simple way of increasing the effectiveness of fragment-based similarity searching systems.
@article{holliday2002grouping,
abstract = {This paper compares 22 different similarity coefficients when they are used for searching databases of 2D fragment bit-strings. Experiments with the National Cancer Institute s AIDS and IDAlert databases show that the coefficients fall into several well-marked clusters, in which the members of a cluster will produce comparable rankings of a set of molecules. These clusters provide a basis for selecting combinations of coefficients for use in data fusion experiments. The results of these experiments provide a simple way of increasing the effectiveness of fragment-based similarity searching systems.},
added-at = {2010-07-27T16:13:35.000+0200},
author = {Holliday, John D and Hu, C Y and Willett, P},
biburl = {https://www.bibsonomy.org/bibtex/203b0287df22c9934a4a8a13dd7969742/asalber},
interhash = {d3c7e52d76ca4aa38816744f092a5d05},
intrahash = {03b0287df22c9934a4a8a13dd7969742},
journal = {Combinatorial Chemistry and High-Throughput Screening},
keywords = {similarity similarity-multiheteroset},
month = mar,
number = 2,
pages = {155-166},
timestamp = {2012-06-07T11:24:17.000+0200},
title = {Grouping of coefficients for the calculation of inter-molecular similarity and dissimilarity using 2D fragment bit-strings},
url = {http://www.ncbi.nlm.nih.gov/pubmed/11966424},
volume = 5,
year = 2002
}