White Rose University Consortium logo
University of Leeds logo University of Sheffield logo York University logo

Combination of fingerprint-based similarity coefficients using data fusion

Salim, N., Holliday, J.D. and Willett, P. (2003) Combination of fingerprint-based similarity coefficients using data fusion. Journal of Chemical Information and Computer Sciences, 43 (2). pp. 435-442. ISSN 0095-2338

Full text not available from this repository. (Request a copy)


Many different types of similarity coefficients have been described in the literature. Since different coefficients take into account different characteristics when assessing the degree of similarity between molecules, it is reasonable to combine them to further optimize the measures of similarity between molecules. This paper describes experiments in which data fusion is used to combine several binary similarity coefficients to get an overall estimate of similarity for searching databases of bioactive molecules. The results show that search performances can be improved by combining coefficients with little extra computational cost. However, there is no single combination which gives a consistently high performance for all search types.

Item Type: Article
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)
Depositing User: Information Studies
Date Deposited: 26 Aug 2009 09:57
Last Modified: 26 Aug 2009 09:57
Published Version: http://dx.doi.org/10.1021/ci025596j
Status: Published
Publisher: American Chemical Society
Identification Number: 10.1021/ci025596j
URI: http://eprints.whiterose.ac.uk/id/eprint/9230

Actions (repository staff only: login required)