Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4167

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4167

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: CHEMBL4167 (TID: 100599), and it has 28 rows and 113 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.

115 features

pXC50 (target)numeric11 unique values
0 missing
molecule_id (row identifier)nominal28 unique values
0 missing
ATSC3snumeric28 unique values
0 missing
Eig04_AEA.ri.numeric27 unique values
0 missing
Eig04_EAnumeric24 unique values
0 missing
MPC10numeric26 unique values
0 missing
MWC05numeric27 unique values
0 missing
piIDnumeric27 unique values
0 missing
P_VSA_m_2numeric27 unique values
0 missing
SM02_AEA.ed.numeric26 unique values
0 missing
SM03_AEA.ed.numeric26 unique values
0 missing
SM04_EAnumeric25 unique values
0 missing
SM12_AEA.bo.numeric24 unique values
0 missing
ATS4snumeric28 unique values
0 missing
BIC1numeric25 unique values
0 missing
BIC2numeric28 unique values
0 missing
CIC1numeric27 unique values
0 missing
CIC2numeric28 unique values
0 missing
SIC1numeric26 unique values
0 missing
SIC2numeric27 unique values
0 missing
ATSC5pnumeric28 unique values
0 missing
Vindexnumeric27 unique values
0 missing
Xindexnumeric27 unique values
0 missing
Eig06_AEA.dm.numeric21 unique values
0 missing
SsCH3numeric28 unique values
0 missing
Eig03_AEA.bo.numeric26 unique values
0 missing
Eig03_AEA.ri.numeric24 unique values
0 missing
Eig03_EAnumeric25 unique values
0 missing
Eig04_AEA.bo.numeric27 unique values
0 missing
Eig04_AEA.ed.numeric25 unique values
0 missing
Eig04_EA.ed.numeric26 unique values
0 missing
Eig04_EA.ri.numeric27 unique values
0 missing
Eig06_AEA.ed.numeric25 unique values
0 missing
Eig06_EA.ed.numeric25 unique values
0 missing
Eig07_AEA.ed.numeric25 unique values
0 missing
MPC03numeric23 unique values
0 missing
SM02_EA.ed.numeric27 unique values
0 missing
SM03_EA.ed.numeric26 unique values
0 missing
SM04_AEA.ed.numeric26 unique values
0 missing
SM04_EA.ed.numeric27 unique values
0 missing
SM05_AEA.ed.numeric27 unique values
0 missing
SM05_EAnumeric21 unique values
0 missing
SM05_EA.ed.numeric27 unique values
0 missing
SM05_EA.ri.numeric28 unique values
0 missing
SM06_AEA.ed.numeric27 unique values
0 missing
SM06_EAnumeric27 unique values
0 missing
SM06_EA.ed.numeric27 unique values
0 missing
SM06_EA.ri.numeric28 unique values
0 missing
SM07_AEA.ed.numeric27 unique values
0 missing
SM07_EAnumeric27 unique values
0 missing
SM07_EA.ed.numeric27 unique values
0 missing
SM07_EA.ri.numeric26 unique values
0 missing
SM08_AEA.ed.numeric27 unique values
0 missing
SM08_EAnumeric27 unique values
0 missing
SM09_AEA.ed.numeric27 unique values
0 missing
SM09_EAnumeric27 unique values
0 missing
SM10_AEA.ed.numeric27 unique values
0 missing
SM10_EAnumeric27 unique values
0 missing
SM11_AEA.bo.numeric25 unique values
0 missing
SM11_AEA.ed.numeric27 unique values
0 missing
SM11_EAnumeric27 unique values
0 missing
SM12_AEA.ed.numeric27 unique values
0 missing
SM12_EAnumeric27 unique values
0 missing
SM13_AEA.dm.numeric26 unique values
0 missing
SM13_AEA.ed.numeric27 unique values
0 missing
SM14_AEA.ed.numeric27 unique values
0 missing
SM15_AEA.dm.numeric25 unique values
0 missing
SM15_AEA.ed.numeric27 unique values
0 missing
SRW08numeric27 unique values
0 missing
ZM2MulPernumeric28 unique values
0 missing
ATS6inumeric28 unique values
0 missing
ATSC6mnumeric28 unique values
0 missing
ATSC6vnumeric28 unique values
0 missing
SpMax5_Bh.v.numeric25 unique values
0 missing
Eig01_AEA.dm.numeric19 unique values
0 missing
SpMax_AEA.dm.numeric19 unique values
0 missing
ATS1enumeric26 unique values
0 missing
ATS1inumeric26 unique values
0 missing
ATS1pnumeric25 unique values
0 missing
ATS2enumeric26 unique values
0 missing
ATS2inumeric28 unique values
0 missing
ATS2pnumeric28 unique values
0 missing
ATS3enumeric28 unique values
0 missing
ATS3pnumeric28 unique values
0 missing
ATS4enumeric28 unique values
0 missing
ATS4inumeric28 unique values
0 missing
ATS5enumeric27 unique values
0 missing
ATS5inumeric28 unique values
0 missing
ATSC1vnumeric26 unique values
0 missing
ATSC2snumeric28 unique values
0 missing
ATSC2vnumeric28 unique values
0 missing
ATSC3mnumeric28 unique values
0 missing
ATSC3pnumeric28 unique values
0 missing
ATSC4pnumeric28 unique values
0 missing
ATSC4vnumeric28 unique values
0 missing
ATSC5mnumeric28 unique values
0 missing
CIC0numeric26 unique values
0 missing
Eta_Lnumeric28 unique values
0 missing
Inflammat.80numeric2 unique values
0 missing
MAXDNnumeric27 unique values
0 missing
nBTnumeric20 unique values
0 missing
O.numeric20 unique values
0 missing
ON0Vnumeric28 unique values
0 missing
SAtotnumeric27 unique values
0 missing
Spnumeric26 unique values
0 missing
SpMax4_Bh.i.numeric25 unique values
0 missing
SpMax6_Bh.e.numeric26 unique values
0 missing
SpMax6_Bh.m.numeric25 unique values
0 missing
SpMax8_Bh.e.numeric25 unique values
0 missing
SpMax8_Bh.m.numeric25 unique values
0 missing
SpMin5_Bh.e.numeric24 unique values
0 missing
SpMin6_Bh.i.numeric24 unique values
0 missing
SpMin6_Bh.p.numeric25 unique values
0 missing
SpMin6_Bh.v.numeric25 unique values
0 missing
SpMin7_Bh.m.numeric25 unique values
0 missing

62 properties

28
Number of instances (rows) of the dataset.
115
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.
114
Number of numeric attributes.
1
Number of nominal attributes.
0
Percentage of binary attributes.
0.4
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.49
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
9.28
Maximum kurtosis among attributes of the numeric type.
0.25
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
3.07
Third quartile of kurtosis among attributes of the numeric type.
628.47
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
99.13
Percentage of numeric attributes.
13.17
Third quartile of means 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.
0.87
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.
-2.3
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
0.08
Third quartile of skewness among attributes of the numeric type.
2.06
Maximum skewness among attributes of the numeric type.
0.09
Minimum standard deviation of attributes of the numeric type.
-0.1
First quartile of kurtosis among attributes of the numeric type.
0.94
Third quartile of standard deviation of attributes of the numeric type.
159.97
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
3.61
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.
Number of instances belonging to the least frequent class.
First quartile of mutual information between the nominal attributes and the target attribute.
1.58
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
-1.06
First quartile of skewness among attributes of the numeric type.
20.9
Mean of means among attributes of the numeric type.
0.28
First quartile of standard deviation of attributes of the numeric type.
0.52
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.
1.28
Second quartile (Median) of kurtosis among attributes of the numeric type.
4.11
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
6.11
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.
-0.35
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.
4.82
Mean standard deviation of attributes of the numeric type.
-0.61
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.

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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