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  • 标题:A note on utilising binary features as ligand descriptors
  • 本地全文:下载
  • 作者:Hamse Y. Mussa ; John B. O. Mitchell ; Robert C. Glen
  • 期刊名称:Journal of Cheminformatics
  • 印刷版ISSN:1758-2946
  • 电子版ISSN:1758-2946
  • 出版年度:2015
  • 卷号:7
  • 期号:1
  • 页码:58
  • DOI:10.1186/s13321-015-0105-3
  • 语种:English
  • 出版社:BioMed Central
  • 摘要:It is common in cheminformatics to represent the properties of a ligand as a string of 1’s and 0’s, with the intention of elucidating, inter alia, the relationship between the chemical structure of a ligand and its bioactivity. In this commentary we note that, where relevant but non-redundant features are binary, they inevitably lead to a classifier capable of capturing only a linear relationship between structural features and activity. If, instead, we were to use relevant but non-redundant real-valued features, the resulting predictive model would be capable of describing a non-linear structure-activity relationship. Hence, we suggest that real-valued features, where available, are to be preferred in this scenario.
  • 关键词:Binary descriptors ; Ligand chemical structure ; Linear relationship ; Bernoulli distribution
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