QSAR Androgen Receptor Data Set
QSAR Androgen Receptor Data Set
@kaggle.ishandutta_qsar_androgen_receptor_data_set
QSAR Androgen Receptor Data Set
@kaggle.ishandutta_qsar_androgen_receptor_data_set
This dataset was used to develop classification QSAR models for the discrimination of binder/positive (199) and non-binder/negative (1488) molecules by means of different machine learning methods. Details can be found in the quoted reference: F. Grisoni, V. Consonni, D. Ballabio, (2019) Machine Learning Consensus to Predict the Binding to the Androgen Receptor within the CoMPARA project, Journal of chemical information and modeling, 59, 1839-1848; doi: 10.1021/acs.jcim.8b00794.
Attributes (molecular fingerprints) were calculated at the Milano Chemometrics and QSAR Research Group (Università degli Studi Milano - Bicocca, Milano, Italy) on a set of chemicals provided by the National Center of Computational Toxicology, at the U.S. Environmental Protection Agency in the framework of the CoMPARA collaborative modelling project, which targeted the development of QSAR models to identify binders to the Androgen Receptor.
1024 binary molecular fingerprints and 1 experimental class:
1-1024) binary molecular fingerprint
1025) experimental class: positive (binder) and negative (non-binder)
F. Grisoni, V. Consonni, D. Ballabio, (2019) Machine Learning Consensus to Predict the Binding to the Androgen Receptor within the CoMPARA project, Journal of chemical information and modeling, 59, 1839-1848; doi: 10.1021/acs.jcim.8b00794
CREATE TABLE qsar_androgen_receptor (
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);Anyone who has the link will be able to view this.