A note on utilising binary features as ligand descriptors
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 featur...
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| Format: | Online |
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Springer International Publishing
2015
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4665894/ |
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pubmed-46658942015-12-02 A note on utilising binary features as ligand descriptors Mussa, Hamse Y. Mitchell, John B. O. Glen, Robert C. Commentary 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. Springer International Publishing 2015-12-01 /pmc/articles/PMC4665894/ /pubmed/26628925 http://dx.doi.org/10.1186/s13321-015-0105-3 Text en © Mussa et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Mussa, Hamse Y. Mitchell, John B. O. Glen, Robert C. |
| spellingShingle |
Mussa, Hamse Y. Mitchell, John B. O. Glen, Robert C. A note on utilising binary features as ligand descriptors |
| author_facet |
Mussa, Hamse Y. Mitchell, John B. O. Glen, Robert C. |
| author_sort |
Mussa, Hamse Y. |
| title |
A note on utilising binary features as ligand descriptors |
| title_short |
A note on utilising binary features as ligand descriptors |
| title_full |
A note on utilising binary features as ligand descriptors |
| title_fullStr |
A note on utilising binary features as ligand descriptors |
| title_full_unstemmed |
A note on utilising binary features as ligand descriptors |
| title_sort |
note on utilising binary features as ligand descriptors |
| description |
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. |
| publisher |
Springer International Publishing |
| publishDate |
2015 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4665894/ |
| _version_ |
1613508306653937664 |