Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4600

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4600

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: CHEMBL4600 (TID: 30025), and it has 813 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)numeric47 unique values
0 missing
molecule_id (row identifier)nominal813 unique values
0 missing
VvdwMGnumeric687 unique values
0 missing
Vxnumeric687 unique values
0 missing
X1solnumeric631 unique values
0 missing
SpMax8_Bh.p.numeric434 unique values
0 missing
Svnumeric726 unique values
0 missing
MWnumeric716 unique values
0 missing
ATS1mnumeric514 unique values
0 missing
AMRnumeric777 unique values
0 missing
X1vnumeric755 unique values
0 missing
X0solnumeric468 unique values
0 missing
X2solnumeric690 unique values
0 missing
XMODnumeric775 unique values
0 missing
SpMax8_Bh.m.numeric465 unique values
0 missing
TIC2numeric728 unique values
0 missing
Eig11_AEA.dm.numeric510 unique values
0 missing
Spnumeric692 unique values
0 missing
X0vnumeric735 unique values
0 missing
SpMax6_Bh.m.numeric503 unique values
0 missing
SpMax6_Bh.e.numeric465 unique values
0 missing
Eig15_EA.ed.numeric601 unique values
0 missing
SM10_AEA.ri.numeric601 unique values
0 missing
VvdwZAZnumeric736 unique values
0 missing
TIC3numeric627 unique values
0 missing
TIC5numeric592 unique values
0 missing
Eta_alphanumeric504 unique values
0 missing
TIC1numeric744 unique values
0 missing
Eig15_EAnumeric518 unique values
0 missing
Eig15_EA.bo.numeric578 unique values
0 missing
Eig15_EA.ri.numeric619 unique values
0 missing
SM09_AEA.dm.numeric518 unique values
0 missing
TIC4numeric596 unique values
0 missing
Eig15_AEA.ri.numeric602 unique values
0 missing
ATS1enumeric526 unique values
0 missing
X3solnumeric701 unique values
0 missing
SpMax6_Bh.p.numeric444 unique values
0 missing
SpMin8_Bh.v.numeric425 unique values
0 missing
Eig10_EAnumeric496 unique values
0 missing
SM04_AEA.dm.numeric496 unique values
0 missing
Eig06_EA.ed.numeric663 unique values
0 missing
SM15_AEA.dm.numeric663 unique values
0 missing
Eig12_AEA.ri.numeric561 unique values
0 missing
Eig12_EA.ri.numeric566 unique values
0 missing
Chi1_EA.dm.numeric703 unique values
0 missing
ATS1vnumeric506 unique values
0 missing
Eig13_AEA.dm.numeric551 unique values
0 missing
Eig11_EAnumeric485 unique values
0 missing
SM05_AEA.dm.numeric485 unique values
0 missing
Eig15_AEA.bo.numeric518 unique values
0 missing
SpMax6_Bh.i.numeric444 unique values
0 missing
SpMaxA_EAnumeric126 unique values
0 missing
Eig06_AEA.ed.numeric568 unique values
0 missing
Eig12_AEA.dm.numeric524 unique values
0 missing
Eig11_EA.ed.numeric543 unique values
0 missing
SM06_AEA.ri.numeric543 unique values
0 missing
Eig11_AEA.bo.numeric494 unique values
0 missing
Eig11_AEA.ri.numeric550 unique values
0 missing
Eig11_EA.ri.numeric526 unique values
0 missing
ATS2mnumeric529 unique values
0 missing
ATS2pnumeric535 unique values
0 missing
SpMax8_Bh.v.numeric452 unique values
0 missing
ATS1pnumeric508 unique values
0 missing
ISIZnumeric68 unique values
0 missing
nATnumeric68 unique values
0 missing
ZM2Madnumeric788 unique values
0 missing
Chi0_EA.dm.numeric691 unique values
0 missing
SpMaxA_AEA.ed.numeric218 unique values
0 missing
SpMax8_Bh.i.numeric443 unique values
0 missing
SpMax6_Bh.v.numeric447 unique values
0 missing
Chi0_EA.ed.numeric705 unique values
0 missing

62 properties

813
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.
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.
Second quartile (Median) of entropy among attributes.
0.09
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.6
Second quartile (Median) of kurtosis 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
Mean skewness among attributes of the numeric type.
3.47
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
13.41
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.
0.03
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-0.64
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.75
Second quartile (Median) of standard deviation of attributes of the numeric type.
34.63
Maximum kurtosis among attributes of the numeric type.
-0.94
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
453.12
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.
1.43
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.
98.59
Percentage of numeric attributes.
20.01
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-1.74
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.
5.24
Maximum skewness among attributes of the numeric type.
0.03
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.65
Third quartile of skewness among attributes of the numeric type.
108.08
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.03
First quartile of kurtosis among attributes of the numeric type.
7.52
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.
0.91
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
1.42
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.
48.5
Mean of means among attributes of the numeric type.
-0.8
First quartile of skewness among attributes of the numeric type.
0.82
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.31
First quartile of standard deviation of attributes of the numeric type.

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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