Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1186/s13321-015-0105-3 | Journal of Cheminformatics |
Keywords | Field | DocType |
Binary descriptors, Ligand chemical structure, Linear relationship, Bernoulli distribution | Data mining,Feature selection,Computer science,Ligand,Mutual information,Bioinformatics,Classifier (linguistics),Cheminformatics,Binary descriptor,Binary number | Journal |
Volume | Issue | ISSN |
7 | 1 | 1758-2946 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hamse Y Mussa | 1 | 192 | 13.13 |
| John B O Mitchell | 2 | 384 | 32.48 |
| Robert C Glen | 3 | 589 | 61.78 |