Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL245

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL245

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: CHEMBL245 (TID: 219), and it has 1584 rows and 69 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.

71 features

pXC50 (target)numeric784 unique values
0 missing
molecule_id (row identifier)nominal1584 unique values
0 missing
Eig01_AEA.dm.numeric494 unique values
0 missing
SpMax_AEA.dm.numeric494 unique values
0 missing
Eig09_EA.bo.numeric661 unique values
0 missing
Eig01_AEA.bo.numeric459 unique values
0 missing
SpMax_AEA.bo.numeric459 unique values
0 missing
Eig01_AEA.ed.numeric412 unique values
0 missing
SpMax_AEA.ed.numeric412 unique values
0 missing
CATS2D_08_PLnumeric8 unique values
0 missing
ATSC8pnumeric1381 unique values
0 missing
ATSC2pnumeric1213 unique values
0 missing
SpMin6_Bh.i.numeric565 unique values
0 missing
SpMax6_Bh.v.numeric601 unique values
0 missing
ATS1pnumeric663 unique values
0 missing
ATS7enumeric904 unique values
0 missing
ATSC3vnumeric1342 unique values
0 missing
ATSC8vnumeric1394 unique values
0 missing
ATSC1vnumeric1084 unique values
0 missing
ATS8snumeric959 unique values
0 missing
SpMax6_Bh.p.numeric567 unique values
0 missing
ATS6mnumeric901 unique values
0 missing
SpDiam_AEA.dm.numeric524 unique values
0 missing
Eig01_EA.dm.numeric138 unique values
0 missing
SpMax_EA.dm.numeric138 unique values
0 missing
LLS_01numeric7 unique values
0 missing
Eig03_AEA.ri.numeric631 unique values
0 missing
Svnumeric1048 unique values
0 missing
SM08_EA.dm.numeric410 unique values
0 missing
ATS1vnumeric681 unique values
0 missing
ATSC6inumeric1065 unique values
0 missing
nBTnumeric104 unique values
0 missing
Eig03_EA.ri.numeric623 unique values
0 missing
ATS7snumeric940 unique values
0 missing
ISIZnumeric101 unique values
0 missing
nATnumeric101 unique values
0 missing
VvdwZAZnumeric1102 unique values
0 missing
Senumeric1061 unique values
0 missing
CATS2D_06_APnumeric4 unique values
0 missing
VvdwMGnumeric1042 unique values
0 missing
Vxnumeric1042 unique values
0 missing
ATSC6vnumeric1393 unique values
0 missing
CATS2D_06_LLnumeric40 unique values
0 missing
Eig02_EA.ed.numeric663 unique values
0 missing
SM11_AEA.dm.numeric663 unique values
0 missing
ATSC4inumeric1055 unique values
0 missing
SM05_EA.dm.numeric220 unique values
0 missing
TIC5numeric1048 unique values
0 missing
Eig03_AEA.ed.numeric565 unique values
0 missing
ATSC5inumeric1084 unique values
0 missing
TIC3numeric1189 unique values
0 missing
SM10_EA.dm.numeric367 unique values
0 missing
TIC4numeric1084 unique values
0 missing
SM09_EA.dm.numeric207 unique values
0 missing
Eig03_EAnumeric559 unique values
0 missing
SM11_AEA.bo.numeric559 unique values
0 missing
AMRnumeric1319 unique values
0 missing
SpDiam_AEA.bo.numeric484 unique values
0 missing
CATS2D_05_APnumeric4 unique values
0 missing
ATSC2inumeric853 unique values
0 missing
SpDiam_EA.dm.numeric172 unique values
0 missing
SpMaxA_EA.ed.numeric402 unique values
0 missing
ATS6enumeric902 unique values
0 missing
CATS2D_09_PLnumeric6 unique values
0 missing
ATSC4vnumeric1391 unique values
0 missing
SM07_EA.dm.numeric215 unique values
0 missing
SpDiam_EA.ri.numeric476 unique values
0 missing
ATS8pnumeric935 unique values
0 missing
SpMin5_Bh.e.numeric544 unique values
0 missing
ATS4pnumeric843 unique values
0 missing
TIC2numeric1291 unique values
0 missing

62 properties

1584
Number of instances (rows) of the dataset.
71
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.
70
Number of numeric attributes.
1
Number of nominal attributes.
2.11
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.04
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
4.93
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.
0.14
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.
14.6
Mean standard deviation of attributes of the numeric type.
0.42
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.
0.79
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.19
Minimum kurtosis among attributes of the numeric type.
0.14
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
13.7
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
2.95
Third quartile of kurtosis among attributes of the numeric type.
518.16
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.59
Percentage of numeric attributes.
13.57
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.85
Minimum skewness among attributes of the numeric type.
1.41
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.
0.14
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.8
Third quartile of skewness among attributes of the numeric type.
3.11
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.78
First quartile of kurtosis among attributes of the numeric type.
6.28
Third quartile of standard deviation of attributes of the numeric type.
148.88
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
2.56
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.
2.22
Mean kurtosis among attributes of the numeric type.
-0.82
First quartile of skewness among attributes of the numeric type.
45.52
Mean of means among attributes of the numeric type.
0.4
First quartile of standard deviation of attributes of the numeric type.
-0.19
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

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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