Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL202

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL202

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 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: CHEMBL202 (TID: 6), and it has 778 rows and 68 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.

70 features

pXC50 (target)numeric430 unique values
0 missing
molecule_id (row identifier)nominal778 unique values
0 missing
SpMin1_Bh.v.numeric187 unique values
0 missing
SpMAD_EA.dm.numeric290 unique values
0 missing
SpMax1_Bh.s.numeric99 unique values
0 missing
N.069numeric4 unique values
0 missing
nArNH2numeric4 unique values
0 missing
D.Dtr10numeric317 unique values
0 missing
SpDiam_EA.dm.numeric68 unique values
0 missing
P_VSA_LogP_3numeric89 unique values
0 missing
SpMin1_Bh.p.numeric168 unique values
0 missing
nR10numeric5 unique values
0 missing
CATS2D_06_DDnumeric7 unique values
0 missing
SM02_EA.dm.numeric209 unique values
0 missing
SM04_EA.dm.numeric215 unique values
0 missing
SM06_EA.dm.numeric189 unique values
0 missing
SM08_EA.dm.numeric169 unique values
0 missing
SM10_EA.dm.numeric157 unique values
0 missing
SpAD_EA.dm.numeric217 unique values
0 missing
SpMaxA_AEA.dm.numeric135 unique values
0 missing
SaaNnumeric486 unique values
0 missing
SpMaxA_EA.dm.numeric107 unique values
0 missing
SM13_EA.ed.numeric461 unique values
0 missing
SsNH2numeric497 unique values
0 missing
CATS2D_08_DPnumeric4 unique values
0 missing
SM12_EA.ed.numeric465 unique values
0 missing
SM14_EA.ed.numeric447 unique values
0 missing
CATS2D_06_DPnumeric4 unique values
0 missing
SM11_EA.ed.numeric468 unique values
0 missing
C.043numeric2 unique values
0 missing
Eig01_AEA.ri.numeric270 unique values
0 missing
SpMax_AEA.ri.numeric270 unique values
0 missing
SM10_EA.ed.numeric467 unique values
0 missing
P_VSA_m_2numeric636 unique values
0 missing
CATS2D_04_PPnumeric2 unique values
0 missing
X3Anumeric50 unique values
0 missing
SM09_EA.ed.numeric463 unique values
0 missing
CATS2D_08_DDnumeric6 unique values
0 missing
CATS2D_00_DDnumeric4 unique values
0 missing
CATS2D_00_DPnumeric4 unique values
0 missing
CATS2D_00_PPnumeric4 unique values
0 missing
NsNH2numeric4 unique values
0 missing
PCDnumeric456 unique values
0 missing
X5Anumeric32 unique values
0 missing
D.Dtr05numeric153 unique values
0 missing
SpDiam_AEA.bo.numeric310 unique values
0 missing
SpMAD_AEA.ed.numeric164 unique values
0 missing
Eig01_EA.bo.numeric229 unique values
0 missing
SM11_AEA.ri.numeric229 unique values
0 missing
SpDiam_EA.bo.numeric235 unique values
0 missing
SpMax_EA.bo.numeric229 unique values
0 missing
D.Dtr09numeric142 unique values
0 missing
Eig01_AEA.ed.numeric225 unique values
0 missing
SpMax_AEA.ed.numeric225 unique values
0 missing
C.032numeric3 unique values
0 missing
SM07_EA.bo.numeric432 unique values
0 missing
CATS2D_06_DAnumeric11 unique values
0 missing
SpMin6_Bh.p.numeric360 unique values
0 missing
SpMin1_Bh.m.numeric211 unique values
0 missing
nRNR2numeric2 unique values
0 missing
SM12_EA.dm.numeric145 unique values
0 missing
SM14_EA.dm.numeric142 unique values
0 missing
N.075numeric6 unique values
0 missing
NaaNnumeric6 unique values
0 missing
SRW07numeric12 unique values
0 missing
SRW09numeric28 unique values
0 missing
N.070numeric3 unique values
0 missing
Eig01_EA.dm.numeric60 unique values
0 missing
SpMax_EA.dm.numeric60 unique values
0 missing
SM05_EA.bo.numeric376 unique values
0 missing

62 properties

778
Number of instances (rows) of the dataset.
70
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.
69
Number of numeric attributes.
1
Number of nominal attributes.
Maximum entropy among attributes.
-1.75
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.77
Second quartile (Median) of standard deviation of attributes of the numeric type.
35.24
Maximum kurtosis among attributes of the numeric type.
0.06
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
208.11
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.
2.42
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.
98.57
Percentage of numeric attributes.
7.55
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-1.4
Minimum skewness among attributes of the numeric type.
1.43
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
4.32
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.05
Third quartile of skewness among attributes of the numeric type.
85.37
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.57
First quartile of kurtosis among attributes of the numeric type.
1.72
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.
1.37
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
2.3
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.
11.35
Mean of means among attributes of the numeric type.
-0.54
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.29
First quartile of standard deviation of attributes of the numeric type.
-0.21
Average class difference between consecutive instances.
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.
0.84
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.
0.4
Mean skewness among attributes of the numeric type.
2.94
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
4.59
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.
0.11
Second quartile (Median) of skewness among 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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