QSAR-Bioconcentration-Classes-Data-Set
OpenML dataset with id 43699
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Full work available at URL: https://api.openml.org/data/v1/download/22102524/QSAR-Bioconcentration-Classes-Data-Set.arff
Upload date: 24 March 2022
Dataset Characteristics
Number of features: 13 (numeric: 11, symbolic: 0 and in total binary: 0 )
Number of instances: 779
Number of instances with missing values: 0
Number of missing values: 0
Data Set Information: A dataset of manually-curated BCF for 779 chemicals was used to determine the mechanisms of bioconcentration, i.e. to predict whether a chemical: (1) is mainly stored within lipid tissues, (2) has additional storage sites (e.g. proteins), or (3) is metabolized/eliminated. Data were randomly split into a training set of 584 compounds (75) and a test set of 195 compounds (25), preserving the proportion between the classes. Two QSAR classification trees were developed using CART (Classification and Regression Trees) machine learning technique coupled with Genetic Algorithms. The file contains the selected Dragon descriptors (9) along with CAS, SMILES, experimental BCF, experimental/predicted KOW and mechanistic class (1, 2, 3). Further details on model development and performance along with descriptor definitions and interpretation are provided in the original manuscript (Grisoni et al., 2016). Attribute Information: 3 Compound identifiers:
CAS number Molecular SMILES Train/test splitting
9 molecular descriptors (independent variables)
nHM piPC09 PCD X2Av MLOGP ON1V N-072 B02[C-N] F04[C-O]
2 experimental responses:
Bioconcentration Factor (BCF) in log units (regression) Bioaccumulation class (three classes)
Relevant Papers:
F. Grisoni, V.Consonni, M.Vighi, S.Villa, R.Todeschini (2016). Investigating the mechanisms of bioconcentration through QSAR classification trees, Environment International, 88, 198-205
This page was built for dataset: QSAR-Bioconcentration-Classes-Data-Set
