Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2042

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2042

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: CHEMBL2042 (TID: 18077), and it has 16 rows and 1024 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. They were obtained using the Pipeline Pilot program, Dassault Systèmes BIOVIA. Generating Fingerprints do not usually require missing value imputation as all bits are generated.

1026 features

pXC50 (target)numeric14 unique values
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molecule_id (row identifier)nominal16 unique values
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FCFP4_1024b306numeric1 unique values
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FCFP4_1024b517numeric1 unique values
0 missing
FCFP4_1024b748numeric1 unique values
0 missing
FCFP4_1024b979numeric1 unique values
0 missing
FCFP4_1024b288numeric1 unique values
0 missing
FCFP4_1024b518numeric1 unique values
0 missing
FCFP4_1024b749numeric1 unique values
0 missing
FCFP4_1024b98numeric1 unique values
0 missing
FCFP4_1024b289numeric1 unique values
0 missing
FCFP4_1024b519numeric1 unique values
0 missing
FCFP4_1024b75numeric1 unique values
0 missing
FCFP4_1024b980numeric1 unique values
0 missing
FCFP4_1024b29numeric1 unique values
0 missing
FCFP4_1024b52numeric1 unique values
0 missing
FCFP4_1024b750numeric1 unique values
0 missing
FCFP4_1024b981numeric1 unique values
0 missing
FCFP4_1024b290numeric1 unique values
0 missing
FCFP4_1024b520numeric1 unique values
0 missing
FCFP4_1024b751numeric1 unique values
0 missing
FCFP4_1024b982numeric1 unique values
0 missing
FCFP4_1024b291numeric1 unique values
0 missing
FCFP4_1024b521numeric1 unique values
0 missing
FCFP4_1024b752numeric1 unique values
0 missing
FCFP4_1024b983numeric1 unique values
0 missing
FCFP4_1024b292numeric1 unique values
0 missing
FCFP4_1024b522numeric1 unique values
0 missing
FCFP4_1024b753numeric1 unique values
0 missing
FCFP4_1024b984numeric1 unique values
0 missing
FCFP4_1024b293numeric1 unique values
0 missing
FCFP4_1024b523numeric1 unique values
0 missing
FCFP4_1024b754numeric1 unique values
0 missing
FCFP4_1024b985numeric1 unique values
0 missing
FCFP4_1024b294numeric1 unique values
0 missing
FCFP4_1024b524numeric1 unique values
0 missing
FCFP4_1024b755numeric1 unique values
0 missing
FCFP4_1024b986numeric1 unique values
0 missing
FCFP4_1024b295numeric1 unique values
0 missing
FCFP4_1024b525numeric1 unique values
0 missing
FCFP4_1024b756numeric1 unique values
0 missing
FCFP4_1024b987numeric1 unique values
0 missing
FCFP4_1024b296numeric1 unique values
0 missing
FCFP4_1024b526numeric1 unique values
0 missing
FCFP4_1024b757numeric1 unique values
0 missing
FCFP4_1024b988numeric1 unique values
0 missing
FCFP4_1024b297numeric1 unique values
0 missing
FCFP4_1024b527numeric1 unique values
0 missing
FCFP4_1024b758numeric2 unique values
0 missing
FCFP4_1024b989numeric1 unique values
0 missing
FCFP4_1024b298numeric1 unique values
0 missing
FCFP4_1024b528numeric1 unique values
0 missing
FCFP4_1024b759numeric1 unique values
0 missing
FCFP4_1024b99numeric1 unique values
0 missing
FCFP4_1024b299numeric1 unique values
0 missing
FCFP4_1024b529numeric1 unique values
0 missing
FCFP4_1024b76numeric1 unique values
0 missing
FCFP4_1024b990numeric1 unique values
0 missing
FCFP4_1024b3numeric1 unique values
0 missing
FCFP4_1024b53numeric1 unique values
0 missing
FCFP4_1024b760numeric1 unique values
0 missing
FCFP4_1024b991numeric1 unique values
0 missing
FCFP4_1024b30numeric1 unique values
0 missing
FCFP4_1024b530numeric1 unique values
0 missing

62 properties

16
Number of instances (rows) of the dataset.
1026
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.
1025
Number of numeric attributes.
1
Number of nominal attributes.
-1.39
Second quartile (Median) of kurtosis among attributes of the numeric type.
64.13
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0
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.
0.81
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.
0.01
Mean standard deviation of attributes of the numeric type.
0.9
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0
Percentage of binary attributes.
0
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-2.22
Minimum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
16
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
4.9
Third quartile of kurtosis among attributes of the numeric type.
7.89
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
99.9
Percentage of numeric attributes.
0
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.51
Minimum skewness among attributes of the numeric type.
0.1
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
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
2.2
Third quartile of skewness among attributes of the numeric type.
4
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.39
First quartile of kurtosis among attributes of the numeric type.
0
Third quartile of standard deviation of attributes of the numeric type.
0.68
Maximum standard deviation of attributes of the numeric type.
Number 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.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
2.62
Mean kurtosis among attributes of the numeric type.
-0.9
First quartile of skewness among attributes of the numeric type.
0.07
Mean of means among attributes of the numeric type.
0
First quartile of standard deviation of attributes of the numeric type.
0.15
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.

12 tasks

3 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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