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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3587

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3587

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: CHEMBL3587 (TID: 11409), and it has 927 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)numeric345 unique values
0 missing
molecule_id (row identifier)nominal927 unique values
0 missing
FCFP4_1024b453numeric2 unique values
0 missing
FCFP4_1024b54numeric2 unique values
0 missing
FCFP4_1024b641numeric2 unique values
0 missing
FCFP4_1024b186numeric2 unique values
0 missing
FCFP4_1024b585numeric2 unique values
0 missing
FCFP4_1024b361numeric2 unique values
0 missing
FCFP4_1024b635numeric2 unique values
0 missing
FCFP4_1024b536numeric2 unique values
0 missing
FCFP4_1024b492numeric2 unique values
0 missing
FCFP4_1024b993numeric2 unique values
0 missing
FCFP4_1024b669numeric2 unique values
0 missing
FCFP4_1024b332numeric2 unique values
0 missing
FCFP4_1024b446numeric2 unique values
0 missing
FCFP4_1024b57numeric2 unique values
0 missing
FCFP4_1024b950numeric2 unique values
0 missing
FCFP4_1024b319numeric2 unique values
0 missing
FCFP4_1024b649numeric2 unique values
0 missing
FCFP4_1024b858numeric2 unique values
0 missing
FCFP4_1024b207numeric2 unique values
0 missing
FCFP4_1024b553numeric2 unique values
0 missing
FCFP4_1024b176numeric2 unique values
0 missing
FCFP4_1024b4numeric2 unique values
0 missing
FCFP4_1024b985numeric2 unique values
0 missing
FCFP4_1024b330numeric2 unique values
0 missing
FCFP4_1024b108numeric2 unique values
0 missing
FCFP4_1024b521numeric2 unique values
0 missing
FCFP4_1024b33numeric2 unique values
0 missing
FCFP4_1024b787numeric2 unique values
0 missing
FCFP4_1024b312numeric2 unique values
0 missing
FCFP4_1024b825numeric2 unique values
0 missing
FCFP4_1024b594numeric2 unique values
0 missing
FCFP4_1024b504numeric2 unique values
0 missing
FCFP4_1024b876numeric2 unique values
0 missing
FCFP4_1024b451numeric2 unique values
0 missing
FCFP4_1024b658numeric2 unique values
0 missing
FCFP4_1024b530numeric2 unique values
0 missing
FCFP4_1024b670numeric2 unique values
0 missing
FCFP4_1024b987numeric2 unique values
0 missing
FCFP4_1024b796numeric2 unique values
0 missing
FCFP4_1024b475numeric2 unique values
0 missing
FCFP4_1024b699numeric2 unique values
0 missing
FCFP4_1024b908numeric2 unique values
0 missing
FCFP4_1024b19numeric2 unique values
0 missing
FCFP4_1024b2numeric2 unique values
0 missing
FCFP4_1024b842numeric2 unique values
0 missing
FCFP4_1024b241numeric2 unique values
0 missing
FCFP4_1024b698numeric2 unique values
0 missing
FCFP4_1024b947numeric2 unique values
0 missing
FCFP4_1024b751numeric2 unique values
0 missing
FCFP4_1024b331numeric2 unique values
0 missing
FCFP4_1024b20numeric2 unique values
0 missing
FCFP4_1024b372numeric2 unique values
0 missing
FCFP4_1024b524numeric2 unique values
0 missing
FCFP4_1024b992numeric2 unique values
0 missing
FCFP4_1024b173numeric2 unique values
0 missing
FCFP4_1024b18numeric2 unique values
0 missing
FCFP4_1024b957numeric2 unique values
0 missing
FCFP4_1024b367numeric2 unique values
0 missing
FCFP4_1024b995numeric2 unique values
0 missing
FCFP4_1024b295numeric2 unique values
0 missing
FCFP4_1024b26numeric2 unique values
0 missing
FCFP4_1024b259numeric2 unique values
0 missing
FCFP4_1024b775numeric2 unique values
0 missing
FCFP4_1024b859numeric2 unique values
0 missing
FCFP4_1024b334numeric2 unique values
0 missing
FCFP4_1024b776numeric2 unique values
0 missing
FCFP4_1024b58numeric2 unique values
0 missing
FCFP4_1024b253numeric2 unique values
0 missing
FCFP4_1024b107numeric2 unique values
0 missing
FCFP4_1024b199numeric2 unique values
0 missing
FCFP4_1024b846numeric2 unique values
0 missing
FCFP4_1024b472numeric2 unique values
0 missing
FCFP4_1024b958numeric2 unique values
0 missing
FCFP4_1024b402numeric2 unique values
0 missing
FCFP4_1024b139numeric2 unique values
0 missing
FCFP4_1024b628numeric2 unique values
0 missing
FCFP4_1024b928numeric2 unique values
0 missing
FCFP4_1024b288numeric2 unique values
0 missing
FCFP4_1024b316numeric2 unique values
0 missing
FCFP4_1024b256numeric2 unique values
0 missing
FCFP4_1024b468numeric2 unique values
0 missing
FCFP4_1024b764numeric2 unique values
0 missing
FCFP4_1024b855numeric2 unique values
0 missing
FCFP4_1024b708numeric2 unique values
0 missing
FCFP4_1024b381numeric2 unique values
0 missing
FCFP4_1024b972numeric2 unique values
0 missing
FCFP4_1024b511numeric2 unique values
0 missing
FCFP4_1024b940numeric2 unique values
0 missing
FCFP4_1024b677numeric2 unique values
0 missing
FCFP4_1024b570numeric2 unique values
0 missing
FCFP4_1024b397numeric2 unique values
0 missing
FCFP4_1024b479numeric2 unique values
0 missing
FCFP4_1024b414numeric2 unique values
0 missing
FCFP4_1024b788numeric2 unique values
0 missing
FCFP4_1024b760numeric2 unique values
0 missing
FCFP4_1024b519numeric2 unique values
0 missing
FCFP4_1024b639numeric2 unique values
0 missing
FCFP4_1024b667numeric2 unique values
0 missing
FCFP4_1024b68numeric2 unique values
0 missing
FCFP4_1024b601numeric2 unique values
0 missing
FCFP4_1024b229numeric2 unique values
0 missing
FCFP4_1024b164numeric2 unique values
0 missing

62 properties

927
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.
8.57
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.11
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.07
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.
3.37
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.
0.29
Mean standard deviation of attributes of the numeric type.
3.25
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.
0.26
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-2
Minimum 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.
79.72
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
24.14
Third quartile of kurtosis among attributes of the numeric type.
6.14
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.
0.17
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.41
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.
5.11
Third quartile of skewness among attributes of the numeric type.
9.03
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
1.08
First quartile of kurtosis among attributes of the numeric type.
0.38
Third quartile of standard deviation of attributes of the numeric type.
1.13
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0.03
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.
15.28
Mean kurtosis among attributes of the numeric type.
1.73
First quartile of skewness among attributes of the numeric type.
0.21
Mean of means among attributes of the numeric type.
0.18
First quartile of standard deviation of attributes of the numeric type.
0.05
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

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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