Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3106

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3106

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: CHEMBL3106 (TID: 11723), and it has 118 rows and 66 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.

68 features

pXC50 (target)numeric98 unique values
0 missing
molecule_id (row identifier)nominal118 unique values
0 missing
H.054numeric3 unique values
0 missing
MATS3mnumeric101 unique values
0 missing
P_VSA_e_2numeric98 unique values
0 missing
C.029numeric4 unique values
0 missing
P_VSA_MR_5numeric70 unique values
0 missing
P_VSA_MR_6numeric62 unique values
0 missing
P_VSA_s_4numeric53 unique values
0 missing
CATS2D_04_DAnumeric7 unique values
0 missing
N.071numeric3 unique values
0 missing
nArNR2numeric3 unique values
0 missing
GATS3snumeric99 unique values
0 missing
X4Anumeric31 unique values
0 missing
GATS3mnumeric94 unique values
0 missing
MATS6pnumeric103 unique values
0 missing
SM09_EA.bo.numeric75 unique values
0 missing
CATS2D_02_DDnumeric4 unique values
0 missing
CATS2D_06_DDnumeric4 unique values
0 missing
GATS6vnumeric103 unique values
0 missing
Eig01_AEA.bo.numeric55 unique values
0 missing
SpMax_AEA.bo.numeric55 unique values
0 missing
MATS3snumeric99 unique values
0 missing
BIC2numeric76 unique values
0 missing
SM10_EA.bo.numeric78 unique values
0 missing
SM11_EA.bo.numeric76 unique values
0 missing
GATS6snumeric113 unique values
0 missing
MATS8enumeric99 unique values
0 missing
GATS8enumeric99 unique values
0 missing
MATS8snumeric103 unique values
0 missing
SsssNnumeric54 unique values
0 missing
MATS3enumeric104 unique values
0 missing
SRW07numeric9 unique values
0 missing
SM13_EA.bo.numeric75 unique values
0 missing
MATS6vnumeric98 unique values
0 missing
GATS3enumeric105 unique values
0 missing
GATS8snumeric97 unique values
0 missing
SM12_EA.bo.numeric78 unique values
0 missing
SM14_EA.bo.numeric76 unique values
0 missing
SM15_EA.bo.numeric73 unique values
0 missing
Eig01_EA.bo.numeric58 unique values
0 missing
SM11_AEA.ri.numeric58 unique values
0 missing
SpMax_EA.bo.numeric58 unique values
0 missing
GATS6mnumeric109 unique values
0 missing
P_VSA_i_2numeric98 unique values
0 missing
Eig06_AEA.ri.numeric76 unique values
0 missing
X2Anumeric45 unique values
0 missing
Eig11_AEA.dm.numeric79 unique values
0 missing
Uinumeric15 unique values
0 missing
P_VSA_MR_2numeric29 unique values
0 missing
Eig06_EA.bo.numeric80 unique values
0 missing
SpMin5_Bh.e.numeric76 unique values
0 missing
MATS5mnumeric103 unique values
0 missing
Eig06_AEA.ed.numeric48 unique values
0 missing
Eig12_AEA.dm.numeric84 unique values
0 missing
IC2numeric80 unique values
0 missing
MATS6enumeric106 unique values
0 missing
nArXnumeric3 unique values
0 missing
JGI5numeric33 unique values
0 missing
MATS6mnumeric99 unique values
0 missing
GATS6enumeric106 unique values
0 missing
Eig01_EA.dm.numeric24 unique values
0 missing
SpDiam_EA.dm.numeric28 unique values
0 missing
SpMax_EA.dm.numeric24 unique values
0 missing
SpMAD_EA.ri.numeric81 unique values
0 missing
SM03_EA.dm.numeric19 unique values
0 missing
SM05_EA.dm.numeric24 unique values
0 missing
Eig13_AEA.ri.numeric74 unique values
0 missing

62 properties

118
Number of instances (rows) of the dataset.
68
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.
67
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.
0.58
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.1
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.
0.55
Mean skewness among attributes of the numeric type.
1.24
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
5.06
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.
0.35
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.86
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.67
Second quartile (Median) of standard deviation of attributes of the numeric type.
16.03
Maximum kurtosis among attributes of the numeric type.
-0.28
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
75.22
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.
1.51
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.
98.53
Percentage of numeric attributes.
4.19
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.
1.47
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2.91
Maximum skewness among attributes of the numeric type.
0.01
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.14
Third quartile of skewness among attributes of the numeric type.
64.13
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.38
First quartile of kurtosis among attributes of the numeric type.
1.03
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.
0.16
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
1.19
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.
8.03
Mean of means among attributes of the numeric type.
-0.12
First quartile of skewness among attributes of the numeric type.
0.17
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.24
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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