ames: Hansen Ames Mutagenicity Dataset
In rfFC: Random Forest Feature Contributions
Description
Usage
Format
References
Description
This binary classification dataset
corresponds to the benchmark dataset for Ames mutagenicity modelling presented by Hansen et al.
Usage
1
Format
ames is a data frame with 6512 cases (rows) and 170
variables (columns). This data set consists of two types of
Activity: (1) positive, (0) negative chemical compounds. All chemical
structures are encoded using binary attributes: a bit vector calculated
based upon the MACCS key fingerprint. Dataset structure: CAS_NO, Activity, Canonical_Smiles,
X1-X166 - 166 binary descriptors, Type. The CAS_NO column presents the CAS number (i.e. the instance ID).
The 'Training' and 'Test' labels in the Type column denote the first of the five splits presented by Hansen et al.
References
K. Hansen, S. Mika, T. Schroeter, A. Sutter, A. ter Laak, T. Steger-Hartmann,
N. Heinrich, K.-R. Mueller (2009),Benchmark Data Set for in Silico Prediction of Ames Mutagenicity.
Journal of Chemical Information and Modeling, 49, 2077-2081.
rfFC documentation built on May 2, 2019, 5:18 p.m.
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Description Usage Format References
Description
This binary classification dataset corresponds to the benchmark dataset for Ames mutagenicity modelling presented by Hansen et al.
Usage
1 |
Format
ames is a data frame with 6512 cases (rows) and 170
variables (columns). This data set consists of two types of
Activity: (1) positive, (0) negative chemical compounds. All chemical
structures are encoded using binary attributes: a bit vector calculated
based upon the MACCS key fingerprint. Dataset structure: CAS_NO, Activity, Canonical_Smiles,
X1-X166 - 166 binary descriptors, Type. The CAS_NO column presents the CAS number (i.e. the instance ID).
The 'Training' and 'Test' labels in the Type column denote the first of the five splits presented by Hansen et al.
References
K. Hansen, S. Mika, T. Schroeter, A. Sutter, A. ter Laak, T. Steger-Hartmann, N. Heinrich, K.-R. Mueller (2009),Benchmark Data Set for in Silico Prediction of Ames Mutagenicity. Journal of Chemical Information and Modeling, 49, 2077-2081.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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