期刊名称：Computational and Structural Biotechnology Journal
印刷版ISSN：2001-0370
出版年度：2013
卷号：5
期号：0
DOI：10.5936/csbj.201302002
语种：English
出版社：Computational and Structural Biotechnology Journal
摘要：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.
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