Data for: Assessment of Several Machine Learning Methods Towards Reliable Prediction of Hormone Receptor Binding Affinity
Description of this data
PM6 optimised cartesian coordinates of 1589 organic molecules extracted from the EADB.
Experiment data files
This data is associated with the following publication:
Cite this dataset
Ho, Junming (2017), “Data for: Assessment of Several Machine Learning Methods Towards Reliable Prediction of Hormone Receptor Binding Affinity”, Mendeley Data, v1 http://dx.doi.org/10.17632/kn44r3v5p3.1
The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.
What does this mean?
This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.