Willett, P. (2013) Fusing similarity rankings in ligand-based virtual screening. Computational and Structural Biotechnology Journal, 5. ISSN 2001-0370
Abstract
Data fusion is the name given to a range of methods for combining multiple sources of evidence. This mini-review summarizes the use of one such class of methods for combining the rankings obtained when similarity searching is used for ligand-based virtual screening. Two main approaches are described: similarity fusion involves combining rankings from single searches based on multiple similarity measures; and group fusion involves combining rankings from multiple searches based on a single similarity measure. The review then focuses on the rules that are available for combining similarity rankings, and on the evidence that exists for the superiority of fusion-based methods over conventional similarity searching.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2013 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Combination methods; Ranking methods; Similarity measures; Similarity searching; Virtual screening |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 16 May 2014 13:54 |
Last Modified: | 06 Jun 2014 13:14 |
Published Version: | http://dx.doi.org/10.5936/csbj.201302002 |
Status: | Published |
Publisher: | CSBJ |
Refereed: | Yes |
Identification Number: | 10.5936/csbj.201302002 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:78492 |