Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2096675

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2096675

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 by Noureddin Sadawi
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This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL2096675 (TID: 104830), and it has 275 rows and 51 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent FCFP 1024-bit Molecular Fingerprints which were generated from SMILES strings. Feature selection was applied to this dataset. The fingerprints were obtained using the Pipeline Pilot program, Dassault Systèmes BIOVIA. Generating Fingerprints do not usually require missing value imputation as all bits are generated.

53 features

pXC50 (target)numeric216 unique values
0 missing
molecule_id (row identifier)nominal275 unique values
0 missing
FCFP4_1024b1020numeric2 unique values
0 missing
FCFP4_1024b957numeric2 unique values
0 missing
FCFP4_1024b264numeric2 unique values
0 missing
FCFP4_1024b436numeric2 unique values
0 missing
FCFP4_1024b115numeric2 unique values
0 missing
FCFP4_1024b316numeric2 unique values
0 missing
FCFP4_1024b152numeric2 unique values
0 missing
FCFP4_1024b484numeric2 unique values
0 missing
FCFP4_1024b288numeric2 unique values
0 missing
FCFP4_1024b872numeric2 unique values
0 missing
FCFP4_1024b614numeric2 unique values
0 missing
FCFP4_1024b657numeric2 unique values
0 missing
FCFP4_1024b612numeric2 unique values
0 missing
FCFP4_1024b722numeric2 unique values
0 missing
FCFP4_1024b603numeric2 unique values
0 missing
FCFP4_1024b107numeric2 unique values
0 missing
FCFP4_1024b745numeric2 unique values
0 missing
FCFP4_1024b943numeric2 unique values
0 missing
FCFP4_1024b691numeric2 unique values
0 missing
FCFP4_1024b128numeric2 unique values
0 missing
FCFP4_1024b695numeric2 unique values
0 missing
FCFP4_1024b455numeric2 unique values
0 missing
FCFP4_1024b365numeric2 unique values
0 missing
FCFP4_1024b799numeric2 unique values
0 missing
FCFP4_1024b977numeric2 unique values
0 missing
FCFP4_1024b396numeric2 unique values
0 missing
FCFP4_1024b992numeric2 unique values
0 missing
FCFP4_1024b349numeric2 unique values
0 missing
FCFP4_1024b223numeric2 unique values
0 missing
FCFP4_1024b250numeric2 unique values
0 missing
FCFP4_1024b208numeric2 unique values
0 missing
FCFP4_1024b155numeric2 unique values
0 missing
FCFP4_1024b30numeric2 unique values
0 missing
FCFP4_1024b492numeric2 unique values
0 missing
FCFP4_1024b464numeric2 unique values
0 missing
FCFP4_1024b936numeric2 unique values
0 missing
FCFP4_1024b297numeric2 unique values
0 missing
FCFP4_1024b541numeric2 unique values
0 missing
FCFP4_1024b218numeric2 unique values
0 missing
FCFP4_1024b765numeric2 unique values
0 missing
FCFP4_1024b653numeric2 unique values
0 missing
FCFP4_1024b628numeric2 unique values
0 missing
FCFP4_1024b161numeric2 unique values
0 missing
FCFP4_1024b899numeric2 unique values
0 missing
FCFP4_1024b453numeric2 unique values
0 missing
FCFP4_1024b113numeric2 unique values
0 missing
FCFP4_1024b681numeric2 unique values
0 missing
FCFP4_1024b108numeric2 unique values
0 missing
FCFP4_1024b735numeric2 unique values
0 missing
FCFP4_1024b375numeric2 unique values
0 missing
FCFP4_1024b71numeric2 unique values
0 missing

107 properties

275
Number of instances (rows) of the dataset.
53
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
52
Number of numeric attributes.
1
Number of nominal attributes.
0.35
Third quartile of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.51
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
98.11
Percentage of numeric attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
1.89
Percentage of nominal attributes.
2.83
Third quartile of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
2.96
Mean kurtosis among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.46
Third quartile of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.34
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-1.25
First quartile of kurtosis among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.09
First quartile of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Standard deviation of the number of distinct values among attributes of the nominal type.
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
Average number of distinct values among the attributes of the nominal type.
0.62
First quartile of skewness among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
1.8
Mean skewness among attributes of the numeric type.
0.29
First quartile of standard deviation of attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
Percentage of instances belonging to the most frequent class.
0.39
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Entropy of the target attribute values.
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
1.64
Second quartile (Median) of kurtosis among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-2.01
Minimum kurtosis among attributes of the numeric type.
0.16
Second quartile (Median) of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
18.32
Maximum kurtosis among attributes of the numeric type.
0.04
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
6.75
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
1.9
Second quartile (Median) of skewness among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.19
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
0.36
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
The maximum number of distinct values among attributes of the nominal type.
-1.32
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
6.03
Third quartile of kurtosis among attributes of the numeric type.
-0.05
Average class difference between consecutive instances.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
4.49
Maximum skewness among attributes of the numeric type.
0.2
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.

12 tasks

1 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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