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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5966

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5966

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: CHEMBL5966 (TID: 101395), and it has 175 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)numeric132 unique values
0 missing
molecule_id (row identifier)nominal175 unique values
0 missing
FCFP4_1024b671numeric2 unique values
0 missing
FCFP4_1024b733numeric2 unique values
0 missing
FCFP4_1024b977numeric2 unique values
0 missing
FCFP4_1024b403numeric2 unique values
0 missing
FCFP4_1024b691numeric2 unique values
0 missing
FCFP4_1024b360numeric2 unique values
0 missing
FCFP4_1024b668numeric2 unique values
0 missing
FCFP4_1024b270numeric2 unique values
0 missing
FCFP4_1024b615numeric2 unique values
0 missing
FCFP4_1024b862numeric2 unique values
0 missing
FCFP4_1024b144numeric2 unique values
0 missing
FCFP4_1024b801numeric2 unique values
0 missing
FCFP4_1024b891numeric2 unique values
0 missing
FCFP4_1024b942numeric2 unique values
0 missing
FCFP4_1024b161numeric2 unique values
0 missing
FCFP4_1024b436numeric2 unique values
0 missing
FCFP4_1024b264numeric2 unique values
0 missing
FCFP4_1024b348numeric2 unique values
0 missing
FCFP4_1024b507numeric2 unique values
0 missing
FCFP4_1024b1020numeric2 unique values
0 missing
FCFP4_1024b272numeric2 unique values
0 missing
FCFP4_1024b844numeric2 unique values
0 missing
FCFP4_1024b478numeric2 unique values
0 missing
FCFP4_1024b559numeric2 unique values
0 missing
FCFP4_1024b725numeric2 unique values
0 missing
FCFP4_1024b589numeric2 unique values
0 missing
FCFP4_1024b105numeric2 unique values
0 missing
FCFP4_1024b483numeric2 unique values
0 missing
FCFP4_1024b46numeric2 unique values
0 missing
FCFP4_1024b1numeric1 unique values
0 missing
FCFP4_1024b10numeric2 unique values
0 missing
FCFP4_1024b100numeric1 unique values
0 missing
FCFP4_1024b1000numeric2 unique values
0 missing
FCFP4_1024b1001numeric1 unique values
0 missing
FCFP4_1024b1002numeric1 unique values
0 missing
FCFP4_1024b1003numeric1 unique values
0 missing
FCFP4_1024b1004numeric1 unique values
0 missing
FCFP4_1024b1005numeric1 unique values
0 missing
FCFP4_1024b1006numeric1 unique values
0 missing
FCFP4_1024b1007numeric1 unique values
0 missing
FCFP4_1024b1008numeric1 unique values
0 missing
FCFP4_1024b1009numeric2 unique values
0 missing
FCFP4_1024b101numeric1 unique values
0 missing
FCFP4_1024b1010numeric1 unique values
0 missing
FCFP4_1024b1011numeric1 unique values
0 missing
FCFP4_1024b1012numeric1 unique values
0 missing
FCFP4_1024b1013numeric1 unique values
0 missing
FCFP4_1024b1014numeric1 unique values
0 missing
FCFP4_1024b1015numeric1 unique values
0 missing
FCFP4_1024b1016numeric1 unique values
0 missing
FCFP4_1024b1017numeric1 unique values
0 missing

62 properties

175
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
Percentage of binary attributes.
0.37
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-2.01
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
175
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
1.3
Third quartile of kurtosis among attributes of the numeric type.
5.41
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
98.11
Percentage of numeric attributes.
0.57
Third quartile of means 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.
1.89
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.
-1.81
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
1.76
Third quartile of skewness among attributes of the numeric type.
13.23
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
-1.45
First quartile of kurtosis among attributes of the numeric type.
0.46
Third quartile of standard deviation of attributes of the numeric type.
1.18
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
First quartile of mutual information between the nominal attributes and the target attribute.
7.24
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
-0.7
First quartile of skewness among attributes of the numeric type.
0.37
Mean of means among attributes of the numeric type.
0
First quartile of standard deviation of attributes of the numeric type.
0.2
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among 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.
0.43
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.3
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.17
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.
1.09
Mean skewness among 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.
0.27
Mean standard deviation of attributes of the numeric type.
0.75
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.

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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