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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2049

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2049

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: CHEMBL2049 (TID: 116), and it has 794 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)numeric372 unique values
0 missing
molecule_id (row identifier)nominal794 unique values
0 missing
FCFP4_1024b135numeric2 unique values
0 missing
FCFP4_1024b673numeric2 unique values
0 missing
FCFP4_1024b28numeric2 unique values
0 missing
FCFP4_1024b708numeric2 unique values
0 missing
FCFP4_1024b643numeric2 unique values
0 missing
FCFP4_1024b264numeric2 unique values
0 missing
FCFP4_1024b299numeric2 unique values
0 missing
FCFP4_1024b403numeric2 unique values
0 missing
FCFP4_1024b124numeric2 unique values
0 missing
FCFP4_1024b178numeric2 unique values
0 missing
FCFP4_1024b799numeric2 unique values
0 missing
FCFP4_1024b746numeric2 unique values
0 missing
FCFP4_1024b868numeric2 unique values
0 missing
FCFP4_1024b524numeric2 unique values
0 missing
FCFP4_1024b24numeric2 unique values
0 missing
FCFP4_1024b859numeric2 unique values
0 missing
FCFP4_1024b873numeric2 unique values
0 missing
FCFP4_1024b170numeric2 unique values
0 missing
FCFP4_1024b926numeric2 unique values
0 missing
FCFP4_1024b589numeric2 unique values
0 missing
FCFP4_1024b17numeric2 unique values
0 missing
FCFP4_1024b525numeric2 unique values
0 missing
FCFP4_1024b872numeric2 unique values
0 missing
FCFP4_1024b436numeric2 unique values
0 missing
FCFP4_1024b412numeric2 unique values
0 missing
FCFP4_1024b429numeric2 unique values
0 missing
FCFP4_1024b595numeric2 unique values
0 missing
FCFP4_1024b390numeric2 unique values
0 missing
FCFP4_1024b679numeric2 unique values
0 missing
FCFP4_1024b320numeric2 unique values
0 missing
FCFP4_1024b173numeric2 unique values
0 missing
FCFP4_1024b4numeric2 unique values
0 missing
FCFP4_1024b603numeric2 unique values
0 missing
FCFP4_1024b706numeric2 unique values
0 missing
FCFP4_1024b756numeric2 unique values
0 missing
FCFP4_1024b376numeric2 unique values
0 missing
FCFP4_1024b35numeric2 unique values
0 missing
FCFP4_1024b653numeric2 unique values
0 missing
FCFP4_1024b714numeric2 unique values
0 missing
FCFP4_1024b227numeric2 unique values
0 missing
FCFP4_1024b1020numeric2 unique values
0 missing
FCFP4_1024b461numeric2 unique values
0 missing
FCFP4_1024b754numeric2 unique values
0 missing
FCFP4_1024b65numeric2 unique values
0 missing
FCFP4_1024b850numeric2 unique values
0 missing
FCFP4_1024b964numeric2 unique values
0 missing
FCFP4_1024b689numeric2 unique values
0 missing
FCFP4_1024b619numeric2 unique values
0 missing
FCFP4_1024b153numeric2 unique values
0 missing
FCFP4_1024b32numeric2 unique values
0 missing
FCFP4_1024b908numeric2 unique values
0 missing
FCFP4_1024b78numeric2 unique values
0 missing
FCFP4_1024b591numeric2 unique values
0 missing
FCFP4_1024b574numeric2 unique values
0 missing
FCFP4_1024b430numeric2 unique values
0 missing
FCFP4_1024b930numeric2 unique values
0 missing
FCFP4_1024b698numeric2 unique values
0 missing
FCFP4_1024b234numeric2 unique values
0 missing
FCFP4_1024b785numeric2 unique values
0 missing
FCFP4_1024b508numeric2 unique values
0 missing
FCFP4_1024b60numeric2 unique values
0 missing
FCFP4_1024b6numeric2 unique values
0 missing
FCFP4_1024b781numeric2 unique values
0 missing
FCFP4_1024b353numeric2 unique values
0 missing
FCFP4_1024b253numeric2 unique values
0 missing
FCFP4_1024b797numeric2 unique values
0 missing
FCFP4_1024b431numeric2 unique values
0 missing
FCFP4_1024b55numeric2 unique values
0 missing
FCFP4_1024b606numeric2 unique values
0 missing
FCFP4_1024b909numeric2 unique values
0 missing
FCFP4_1024b1numeric1 unique values
0 missing
FCFP4_1024b10numeric2 unique values
0 missing
FCFP4_1024b100numeric2 unique values
0 missing
FCFP4_1024b1000numeric2 unique values
0 missing
FCFP4_1024b1001numeric2 unique values
0 missing
FCFP4_1024b1002numeric2 unique values
0 missing
FCFP4_1024b1003numeric2 unique values
0 missing
FCFP4_1024b1004numeric2 unique values
0 missing
FCFP4_1024b1005numeric2 unique values
0 missing
FCFP4_1024b1006numeric2 unique values
0 missing
FCFP4_1024b1007numeric2 unique values
0 missing
FCFP4_1024b1008numeric1 unique values
0 missing
FCFP4_1024b1009numeric2 unique values
0 missing
FCFP4_1024b101numeric1 unique values
0 missing
FCFP4_1024b1010numeric2 unique values
0 missing
FCFP4_1024b1011numeric2 unique values
0 missing
FCFP4_1024b1012numeric2 unique values
0 missing
FCFP4_1024b1013numeric2 unique values
0 missing
FCFP4_1024b1014numeric2 unique values
0 missing
FCFP4_1024b1015numeric2 unique values
0 missing
FCFP4_1024b1016numeric2 unique values
0 missing
FCFP4_1024b1017numeric1 unique values
0 missing
FCFP4_1024b1018numeric2 unique values
0 missing
FCFP4_1024b1019numeric2 unique values
0 missing
FCFP4_1024b102numeric2 unique values
0 missing
FCFP4_1024b1021numeric2 unique values
0 missing
FCFP4_1024b1022numeric2 unique values
0 missing
FCFP4_1024b1023numeric2 unique values
0 missing
FCFP4_1024b1024numeric2 unique values
0 missing
FCFP4_1024b103numeric2 unique values
0 missing
FCFP4_1024b104numeric2 unique values
0 missing
FCFP4_1024b105numeric2 unique values
0 missing

62 properties

794
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.
77.03
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.
0.25
Mean of means among attributes of the numeric type.
1.13
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.14
First quartile of standard deviation of attributes of the numeric type.
0.04
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.
9.58
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.13
Number of attributes divided by the number of instances.
5.28
Mean skewness among attributes of the numeric type.
0.08
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.
0.27
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.
3.03
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Maximum entropy among attributes.
-2
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.23
Second quartile (Median) of standard deviation of attributes of the numeric type.
794
Maximum 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.
7.08
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.
39.39
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.
0.25
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-7.08
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.
28.18
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
6.43
Third quartile of skewness among attributes of the numeric type.
1.43
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.56
First quartile of kurtosis among attributes of the numeric type.
0.42
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.
0.02
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 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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