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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4608

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4608

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 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: CHEMBL4608 (TID: 11006), and it has 692 rows and 102 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.

104 features

pXC50 (target)numeric382 unique values
0 missing
molecule_id (row identifier)nominal692 unique values
0 missing
FCFP4_1024b152numeric2 unique values
0 missing
FCFP4_1024b603numeric2 unique values
0 missing
FCFP4_1024b649numeric2 unique values
0 missing
FCFP4_1024b983numeric2 unique values
0 missing
FCFP4_1024b799numeric2 unique values
0 missing
FCFP4_1024b541numeric2 unique values
0 missing
FCFP4_1024b455numeric2 unique values
0 missing
FCFP4_1024b374numeric2 unique values
0 missing
FCFP4_1024b922numeric2 unique values
0 missing
FCFP4_1024b612numeric2 unique values
0 missing
FCFP4_1024b139numeric2 unique values
0 missing
FCFP4_1024b208numeric2 unique values
0 missing
FCFP4_1024b614numeric2 unique values
0 missing
FCFP4_1024b942numeric2 unique values
0 missing
FCFP4_1024b319numeric2 unique values
0 missing
FCFP4_1024b57numeric2 unique values
0 missing
FCFP4_1024b199numeric2 unique values
0 missing
FCFP4_1024b20numeric2 unique values
0 missing
FCFP4_1024b943numeric2 unique values
0 missing
FCFP4_1024b365numeric2 unique values
0 missing
FCFP4_1024b54numeric2 unique values
0 missing
FCFP4_1024b114numeric2 unique values
0 missing
FCFP4_1024b151numeric2 unique values
0 missing
FCFP4_1024b903numeric2 unique values
0 missing
FCFP4_1024b412numeric2 unique values
0 missing
FCFP4_1024b752numeric2 unique values
0 missing
FCFP4_1024b265numeric2 unique values
0 missing
FCFP4_1024b123numeric2 unique values
0 missing
FCFP4_1024b401numeric2 unique values
0 missing
FCFP4_1024b1018numeric2 unique values
0 missing
FCFP4_1024b173numeric2 unique values
0 missing
FCFP4_1024b847numeric2 unique values
0 missing
FCFP4_1024b348numeric2 unique values
0 missing
FCFP4_1024b678numeric2 unique values
0 missing
FCFP4_1024b657numeric2 unique values
0 missing
FCFP4_1024b33numeric2 unique values
0 missing
FCFP4_1024b821numeric2 unique values
0 missing
FCFP4_1024b492numeric2 unique values
0 missing
FCFP4_1024b31numeric2 unique values
0 missing
FCFP4_1024b615numeric2 unique values
0 missing
FCFP4_1024b728numeric2 unique values
0 missing
FCFP4_1024b171numeric2 unique values
0 missing
FCFP4_1024b18numeric2 unique values
0 missing
FCFP4_1024b461numeric2 unique values
0 missing
FCFP4_1024b106numeric2 unique values
0 missing
FCFP4_1024b105numeric2 unique values
0 missing
FCFP4_1024b309numeric2 unique values
0 missing
FCFP4_1024b318numeric2 unique values
0 missing
FCFP4_1024b134numeric2 unique values
0 missing
FCFP4_1024b872numeric2 unique values
0 missing
FCFP4_1024b525numeric2 unique values
0 missing
FCFP4_1024b113numeric2 unique values
0 missing
FCFP4_1024b42numeric2 unique values
0 missing
FCFP4_1024b138numeric2 unique values
0 missing
FCFP4_1024b589numeric2 unique values
0 missing
FCFP4_1024b714numeric2 unique values
0 missing
FCFP4_1024b820numeric2 unique values
0 missing
FCFP4_1024b430numeric2 unique values
0 missing
FCFP4_1024b122numeric2 unique values
0 missing
FCFP4_1024b531numeric2 unique values
0 missing
FCFP4_1024b61numeric2 unique values
0 missing
FCFP4_1024b599numeric2 unique values
0 missing
FCFP4_1024b826numeric2 unique values
0 missing
FCFP4_1024b413numeric2 unique values
0 missing
FCFP4_1024b164numeric2 unique values
0 missing
FCFP4_1024b124numeric2 unique values
0 missing
FCFP4_1024b868numeric2 unique values
0 missing
FCFP4_1024b43numeric2 unique values
0 missing
FCFP4_1024b363numeric2 unique values
0 missing
FCFP4_1024b9numeric2 unique values
0 missing
FCFP4_1024b669numeric2 unique values
0 missing
FCFP4_1024b345numeric2 unique values
0 missing
FCFP4_1024b902numeric2 unique values
0 missing
FCFP4_1024b280numeric2 unique values
0 missing
FCFP4_1024b735numeric2 unique values
0 missing
FCFP4_1024b133numeric2 unique values
0 missing
FCFP4_1024b466numeric2 unique values
0 missing
FCFP4_1024b521numeric2 unique values
0 missing
FCFP4_1024b78numeric2 unique values
0 missing
FCFP4_1024b342numeric2 unique values
0 missing
FCFP4_1024b853numeric2 unique values
0 missing
FCFP4_1024b701numeric2 unique values
0 missing
FCFP4_1024b313numeric2 unique values
0 missing
FCFP4_1024b892numeric2 unique values
0 missing
FCFP4_1024b65numeric2 unique values
0 missing
FCFP4_1024b992numeric2 unique values
0 missing
FCFP4_1024b264numeric2 unique values
0 missing
FCFP4_1024b376numeric2 unique values
0 missing
FCFP4_1024b1001numeric2 unique values
0 missing
FCFP4_1024b697numeric2 unique values
0 missing
FCFP4_1024b35numeric2 unique values
0 missing
FCFP4_1024b260numeric2 unique values
0 missing
FCFP4_1024b981numeric2 unique values
0 missing
FCFP4_1024b585numeric2 unique values
0 missing
FCFP4_1024b694numeric2 unique values
0 missing
FCFP4_1024b218numeric2 unique values
0 missing
FCFP4_1024b483numeric2 unique values
0 missing
FCFP4_1024b378numeric2 unique values
0 missing
FCFP4_1024b553numeric2 unique values
0 missing
FCFP4_1024b572numeric2 unique values
0 missing
FCFP4_1024b381numeric2 unique values
0 missing
FCFP4_1024b241numeric2 unique values
0 missing

62 properties

692
Number of instances (rows) of the dataset.
104
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.
103
Number of numeric attributes.
1
Number of nominal attributes.
Entropy of the target attribute values.
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.
0.15
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
-0.01
Second quartile (Median) of kurtosis 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.
1.54
Mean skewness among attributes of the numeric type.
0.23
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
0.39
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
1.32
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-2.01
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.41
Second quartile (Median) of standard deviation of attributes of the numeric type.
82.11
Maximum kurtosis among attributes of the numeric type.
0.01
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
5.92
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
5.33
Third quartile of kurtosis among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
99.04
Percentage of numeric attributes.
0.48
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-1.96
Minimum skewness among attributes of the numeric type.
0.96
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
9.16
Maximum skewness among attributes of the numeric type.
0.11
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
2.71
Third quartile of skewness among attributes of the numeric type.
1.19
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.68
First quartile of kurtosis among attributes of the numeric type.
0.48
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
0.1
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
3.9
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.
0.35
Mean of means among attributes of the numeric type.
0.08
First quartile of skewness among attributes of the numeric type.
0.09
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.3
First quartile of standard deviation of attributes of the numeric type.

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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