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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5443

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5443

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: CHEMBL5443 (TID: 100077), and it has 935 rows and 28 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent Basic Molecular Descriptors which were generated from SMILES strings. Missing value imputation was applied to this dataset (By choosing the Median). Feature selection was also applied.

30 features

pXC50 (target)numeric221 unique values
0 missing
molecule_id (row identifier)nominal935 unique values
0 missing
nCnumeric29 unique values
0 missing
nSKnumeric33 unique values
0 missing
MWnumeric727 unique values
0 missing
Svnumeric734 unique values
0 missing
SCBOnumeric84 unique values
0 missing
Spnumeric697 unique values
0 missing
nBOnumeric37 unique values
0 missing
Senumeric722 unique values
0 missing
nOnumeric7 unique values
0 missing
N.numeric119 unique values
0 missing
nABnumeric22 unique values
0 missing
O.numeric92 unique values
0 missing
nBMnumeric28 unique values
0 missing
nCsp2numeric26 unique values
0 missing
Sinumeric732 unique values
0 missing
nHetnumeric12 unique values
0 missing
nATnumeric61 unique values
0 missing
nBTnumeric63 unique values
0 missing
nHnumeric35 unique values
0 missing
nSnumeric4 unique values
0 missing
nCLnumeric4 unique values
0 missing
nDBnumeric7 unique values
0 missing
RBNnumeric12 unique values
0 missing
AMWnumeric631 unique values
0 missing
C.numeric128 unique values
0 missing
H.numeric168 unique values
0 missing
Menumeric75 unique values
0 missing
Minumeric73 unique values
0 missing

62 properties

935
Number of instances (rows) of the dataset.
30
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.
29
Number of numeric attributes.
1
Number of nominal attributes.
7.03
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.63
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-0.35
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
4.46
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
0.17
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
6.66
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
1.57
Third quartile of kurtosis among attributes of the numeric type.
350.87
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
96.67
Percentage of numeric attributes.
38.85
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-0.35
Minimum skewness among attributes of the numeric type.
3.33
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
0.01
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.92
Third quartile of skewness among attributes of the numeric type.
2.53
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.15
First quartile of kurtosis among attributes of the numeric type.
6.68
Third quartile of standard deviation of attributes of the numeric type.
78.24
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
3.64
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
1.1
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
30.76
Mean of means among attributes of the numeric type.
0.54
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
1.13
First quartile of standard deviation of attributes of the numeric type.
-0
Average class difference between consecutive instances.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of entropy among attributes.
Entropy of the target attribute values.
Average number of distinct values among the attributes of the nominal type.
0.49
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.03
Number of attributes divided by the number of instances.
0.75
Mean skewness among attributes of the numeric type.
17.38
Second quartile (Median) of means among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.

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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