Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2363

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2363

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: CHEMBL2363 (TID: 10358), and it has 903 rows and 67 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent Molecular Descriptors which were generated from SMILES strings. Missing value imputation was applied to this dataset (By choosing the Median). Feature selection was also applied.

69 features

pXC50 (target)numeric522 unique values
0 missing
molecule_id (row identifier)nominal903 unique values
0 missing
SpMin2_Bh.i.numeric252 unique values
0 missing
SpMin1_Bh.v.numeric187 unique values
0 missing
SpMin2_Bh.v.numeric211 unique values
0 missing
nR10numeric4 unique values
0 missing
SpMin2_Bh.m.numeric268 unique values
0 missing
CATS2D_07_PLnumeric7 unique values
0 missing
Eig06_EA.bo.numeric384 unique values
0 missing
Eta_betaPnumeric39 unique values
0 missing
DECCnumeric387 unique values
0 missing
SpMin2_Bh.e.numeric267 unique values
0 missing
Uinumeric23 unique values
0 missing
nBMnumeric20 unique values
0 missing
Ucnumeric20 unique values
0 missing
Eig05_EA.bo.numeric326 unique values
0 missing
SM15_AEA.ri.numeric326 unique values
0 missing
nR06numeric5 unique values
0 missing
SpMin1_Bh.p.numeric161 unique values
0 missing
GATS6inumeric433 unique values
0 missing
TRSnumeric13 unique values
0 missing
nPyridinesnumeric2 unique values
0 missing
ICRnumeric314 unique values
0 missing
CATS2D_07_DLnumeric10 unique values
0 missing
Xindexnumeric226 unique values
0 missing
Vindexnumeric180 unique values
0 missing
Eig03_EA.ri.numeric467 unique values
0 missing
Eig05_AEA.bo.numeric296 unique values
0 missing
SpMax2_Bh.e.numeric251 unique values
0 missing
Eig06_AEA.ed.numeric324 unique values
0 missing
Yindexnumeric355 unique values
0 missing
SpMax2_Bh.v.numeric265 unique values
0 missing
SpMax2_Bh.p.numeric265 unique values
0 missing
D.Dtr10numeric299 unique values
0 missing
Eig06_EAnumeric333 unique values
0 missing
SM14_AEA.bo.numeric333 unique values
0 missing
SpMax2_Bh.i.numeric232 unique values
0 missing
C.043numeric3 unique values
0 missing
Eig06_AEA.ri.numeric416 unique values
0 missing
SpMax2_Bh.m.numeric297 unique values
0 missing
SRW09numeric23 unique values
0 missing
nCarnumeric17 unique values
0 missing
D.Dtr09numeric156 unique values
0 missing
nR09numeric4 unique values
0 missing
IDEnumeric433 unique values
0 missing
Eig05_EA.ri.numeric334 unique values
0 missing
Rperimnumeric18 unique values
0 missing
MATS6inumeric404 unique values
0 missing
SpMax1_Bh.s.numeric94 unique values
0 missing
SM07_EA.dm.numeric44 unique values
0 missing
SM09_EA.dm.numeric38 unique values
0 missing
SM11_EA.dm.numeric36 unique values
0 missing
SM13_EA.dm.numeric35 unique values
0 missing
SM15_EA.dm.numeric35 unique values
0 missing
SRW07numeric11 unique values
0 missing
HVcpxnumeric411 unique values
0 missing
N.075numeric4 unique values
0 missing
NaaNnumeric4 unique values
0 missing
Eig01_EA.bo.numeric195 unique values
0 missing
SM11_AEA.ri.numeric195 unique values
0 missing
SpDiam_EA.bo.numeric194 unique values
0 missing
SpMax_EA.bo.numeric195 unique values
0 missing
nABnumeric14 unique values
0 missing
SpMin2_Bh.s.numeric294 unique values
0 missing
SM03_EA.dm.numeric25 unique values
0 missing
SM05_EA.dm.numeric46 unique values
0 missing
Eig03_AEA.bo.numeric391 unique values
0 missing
CATS2D_06_DAnumeric6 unique values
0 missing
piPC05numeric450 unique values
0 missing

62 properties

903
Number of instances (rows) of the dataset.
69
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.
68
Number of numeric attributes.
1
Number of nominal attributes.
14.84
Maximum skewness among attributes of the numeric type.
0.04
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.11
Third quartile of skewness among attributes of the numeric type.
67.91
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.07
First quartile of kurtosis among attributes of the numeric type.
1.52
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.
1.58
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
6.31
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.
4.94
Mean of means among attributes of the numeric type.
-1.64
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.19
First quartile of standard deviation of attributes of the numeric type.
-0.17
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.
1.62
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.08
Number of attributes divided by the number of instances.
0.14
Mean skewness among attributes of the numeric type.
2.39
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.
Percentage of instances belonging to the most frequent class.
2.63
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.21
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-0.92
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.32
Second quartile (Median) of standard deviation of attributes of the numeric type.
236.7
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.
65.97
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.
6.06
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.
98.55
Percentage of numeric attributes.
4.07
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.62
Minimum skewness among attributes of the numeric type.
1.45
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.

12 tasks

2 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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