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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2564

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2564

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: CHEMBL2564 (TID: 12476), and it has 1023 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)numeric624 unique values
0 missing
molecule_id (row identifier)nominal1023 unique values
0 missing
FCFP4_1024b768numeric2 unique values
0 missing
FCFP4_1024b660numeric2 unique values
0 missing
FCFP4_1024b925numeric2 unique values
0 missing
FCFP4_1024b451numeric2 unique values
0 missing
FCFP4_1024b419numeric2 unique values
0 missing
FCFP4_1024b416numeric2 unique values
0 missing
FCFP4_1024b971numeric2 unique values
0 missing
FCFP4_1024b986numeric2 unique values
0 missing
FCFP4_1024b353numeric2 unique values
0 missing
FCFP4_1024b243numeric2 unique values
0 missing
FCFP4_1024b29numeric2 unique values
0 missing
FCFP4_1024b579numeric2 unique values
0 missing
FCFP4_1024b374numeric2 unique values
0 missing
FCFP4_1024b251numeric2 unique values
0 missing
FCFP4_1024b290numeric2 unique values
0 missing
FCFP4_1024b829numeric2 unique values
0 missing
FCFP4_1024b4numeric2 unique values
0 missing
FCFP4_1024b666numeric2 unique values
0 missing
FCFP4_1024b58numeric2 unique values
0 missing
FCFP4_1024b110numeric2 unique values
0 missing
FCFP4_1024b826numeric2 unique values
0 missing
FCFP4_1024b774numeric2 unique values
0 missing
FCFP4_1024b617numeric2 unique values
0 missing
FCFP4_1024b787numeric2 unique values
0 missing
FCFP4_1024b842numeric2 unique values
0 missing
FCFP4_1024b445numeric2 unique values
0 missing
FCFP4_1024b65numeric2 unique values
0 missing
FCFP4_1024b69numeric2 unique values
0 missing
FCFP4_1024b330numeric2 unique values
0 missing
FCFP4_1024b2numeric2 unique values
0 missing
FCFP4_1024b283numeric2 unique values
0 missing
FCFP4_1024b18numeric2 unique values
0 missing
FCFP4_1024b948numeric2 unique values
0 missing
FCFP4_1024b412numeric2 unique values
0 missing
FCFP4_1024b773numeric2 unique values
0 missing
FCFP4_1024b298numeric2 unique values
0 missing
FCFP4_1024b521numeric2 unique values
0 missing
FCFP4_1024b960numeric2 unique values
0 missing
FCFP4_1024b107numeric2 unique values
0 missing
FCFP4_1024b390numeric2 unique values
0 missing
FCFP4_1024b310numeric2 unique values
0 missing
FCFP4_1024b323numeric2 unique values
0 missing
FCFP4_1024b553numeric2 unique values
0 missing
FCFP4_1024b137numeric2 unique values
0 missing
FCFP4_1024b847numeric2 unique values
0 missing
FCFP4_1024b153numeric2 unique values
0 missing
FCFP4_1024b529numeric2 unique values
0 missing
FCFP4_1024b458numeric2 unique values
0 missing
FCFP4_1024b376numeric2 unique values
0 missing
FCFP4_1024b525numeric2 unique values
0 missing
FCFP4_1024b360numeric2 unique values
0 missing
FCFP4_1024b817numeric2 unique values
0 missing
FCFP4_1024b680numeric2 unique values
0 missing
FCFP4_1024b240numeric2 unique values
0 missing
FCFP4_1024b478numeric2 unique values
0 missing
FCFP4_1024b71numeric2 unique values
0 missing
FCFP4_1024b541numeric2 unique values
0 missing
FCFP4_1024b685numeric2 unique values
0 missing
FCFP4_1024b731numeric2 unique values
0 missing
FCFP4_1024b54numeric2 unique values
0 missing
FCFP4_1024b22numeric2 unique values
0 missing
FCFP4_1024b163numeric2 unique values
0 missing
FCFP4_1024b492numeric2 unique values
0 missing
FCFP4_1024b917numeric2 unique values
0 missing
FCFP4_1024b429numeric2 unique values
0 missing
FCFP4_1024b430numeric2 unique values
0 missing
FCFP4_1024b1020numeric2 unique values
0 missing
FCFP4_1024b453numeric2 unique values
0 missing
FCFP4_1024b461numeric2 unique values
0 missing
FCFP4_1024b596numeric2 unique values
0 missing
FCFP4_1024b933numeric2 unique values
0 missing
FCFP4_1024b282numeric2 unique values
0 missing
FCFP4_1024b626numeric2 unique values
0 missing
FCFP4_1024b551numeric2 unique values
0 missing
FCFP4_1024b913numeric2 unique values
0 missing
FCFP4_1024b696numeric2 unique values
0 missing
FCFP4_1024b1019numeric2 unique values
0 missing
FCFP4_1024b187numeric2 unique values
0 missing
FCFP4_1024b364numeric2 unique values
0 missing
FCFP4_1024b764numeric2 unique values
0 missing
FCFP4_1024b763numeric2 unique values
0 missing
FCFP4_1024b8numeric2 unique values
0 missing
FCFP4_1024b924numeric2 unique values
0 missing
FCFP4_1024b468numeric2 unique values
0 missing
FCFP4_1024b848numeric2 unique values
0 missing
FCFP4_1024b139numeric2 unique values
0 missing
FCFP4_1024b914numeric2 unique values
0 missing
FCFP4_1024b1003numeric2 unique values
0 missing
FCFP4_1024b669numeric2 unique values
0 missing
FCFP4_1024b527numeric2 unique values
0 missing
FCFP4_1024b678numeric2 unique values
0 missing
FCFP4_1024b898numeric2 unique values
0 missing
FCFP4_1024b780numeric2 unique values
0 missing
FCFP4_1024b203numeric2 unique values
0 missing
FCFP4_1024b904numeric2 unique values
0 missing
FCFP4_1024b160numeric2 unique values
0 missing
FCFP4_1024b977numeric2 unique values
0 missing
FCFP4_1024b855numeric2 unique values
0 missing
FCFP4_1024b97numeric2 unique values
0 missing
FCFP4_1024b143numeric2 unique values
0 missing
FCFP4_1024b940numeric2 unique values
0 missing
FCFP4_1024b204numeric2 unique values
0 missing

62 properties

1023
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.
0.31
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.
2.69
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-1.97
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.3
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
0.01
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
74.07
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
18.39
Third quartile of kurtosis among attributes of the numeric type.
6.17
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
99.04
Percentage of numeric attributes.
0.21
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.37
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.
The maximum number of distinct values among attributes of the nominal type.
0.11
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
4.51
Third quartile of skewness among attributes of the numeric type.
8.71
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.16
First quartile of kurtosis among attributes of the numeric type.
0.4
Third quartile of standard deviation of attributes of the numeric type.
1.29
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
0.04
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
12.16
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.
0.22
Mean of means among attributes of the numeric type.
1.42
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.2
First quartile of standard deviation of attributes of the numeric type.
0.12
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.
5.27
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.1
Number of attributes divided by the number of instances.
2.98
Mean skewness among attributes of the numeric type.
0.1
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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