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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3559

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3559

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 by unknown
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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: CHEMBL3559 (TID: 11267), and it has 354 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)numeric231 unique values
0 missing
SM13_EA.dm.numeric40 unique values
0 missing
SpMax_EAnumeric114 unique values
0 missing
SM11_EA.dm.numeric40 unique values
0 missing
SM09_EA.dm.numeric40 unique values
0 missing
SM07_EA.dm.numeric41 unique values
0 missing
SM05_EA.dm.numeric39 unique values
0 missing
SM03_EA.dm.numeric33 unique values
0 missing
ATSC5pnumeric346 unique values
0 missing
SpMax1_Bh.m.numeric95 unique values
0 missing
SpMax_AEA.ed.numeric113 unique values
0 missing
Eig01_AEA.ed.numeric113 unique values
0 missing
ATSC5vnumeric348 unique values
0 missing
SM13_AEA.ri.numeric191 unique values
0 missing
Eig03_EA.bo.numeric191 unique values
0 missing
Eig03_AEA.ri.numeric221 unique values
0 missing
SpMax_EA.ed.numeric128 unique values
0 missing
SpDiam_EA.ed.numeric163 unique values
0 missing
SM15_EA.dm.numeric39 unique values
0 missing
piPC08numeric255 unique values
0 missing
P_VSA_s_1numeric11 unique values
0 missing
Eig01_AEA.ri.numeric119 unique values
0 missing
SpMax_AEA.ri.numeric119 unique values
0 missing
GATS5enumeric301 unique values
0 missing
X4vnumeric334 unique values
0 missing
SM04_EA.bo.numeric237 unique values
0 missing
SM11_EA.ed.numeric202 unique values
0 missing
SM12_EA.ed.numeric194 unique values
0 missing
SM13_EA.ed.numeric193 unique values
0 missing
SM14_EA.ed.numeric188 unique values
0 missing
SM15_EA.ed.numeric189 unique values
0 missing
piPC09numeric260 unique values
0 missing
NddssSnumeric3 unique values
0 missing
S.110numeric3 unique values
0 missing
MATS1enumeric185 unique values
0 missing
C.041numeric3 unique values
0 missing
D.Dtr05numeric146 unique values
0 missing
SpMin3_Bh.i.numeric172 unique values
0 missing
SM12_AEA.ri.numeric188 unique values
0 missing
Eig02_EA.bo.numeric188 unique values
0 missing
NdssCnumeric5 unique values
0 missing
SpMax3_Bh.i.numeric198 unique values
0 missing
ATS1mnumeric222 unique values
0 missing
Eig01_AEA.dm.numeric73 unique values
0 missing
SpMax3_Bh.v.numeric196 unique values
0 missing
P_VSA_LogP_3numeric63 unique values
0 missing
SdssCnumeric211 unique values
0 missing
SpMax3_Bh.e.numeric198 unique values
0 missing
X5vnumeric330 unique values
0 missing
Eta_sh_xnumeric92 unique values
0 missing
SpMax2_Bh.m.numeric162 unique values
0 missing
ZM1Madnumeric267 unique values
0 missing
SpDiam_EAnumeric114 unique values
0 missing
SM10_AEA.dm.numeric128 unique values
0 missing
SM09_AEA.bo.numeric114 unique values
0 missing
Eig01_EA.ed.numeric128 unique values
0 missing
Eig01_EAnumeric114 unique values
0 missing
CATS2D_04_NLnumeric4 unique values
0 missing
N.072numeric4 unique values
0 missing
piPC06numeric246 unique values
0 missing
molecule_id (row identifier)nominal354 unique values
0 missing
Eig03_AEA.bo.numeric201 unique values
0 missing
Eig02_AEA.bo.numeric174 unique values
0 missing
piPC07numeric258 unique values
0 missing
SM11_AEA.bo.numeric189 unique values
0 missing
Eig03_EAnumeric189 unique values
0 missing
SpMax_AEA.dm.numeric73 unique values
0 missing
SpDiam_AEA.dm.numeric73 unique values
0 missing

62 properties

354
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.
First quartile of mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
98.53
Percentage of numeric attributes.
1.47
Percentage of nominal attributes.
First quartile of entropy among attributes.
-0.68
First quartile of kurtosis among attributes of the numeric type.
3.05
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
-0.42
First quartile of skewness among attributes of the numeric type.
0.31
First quartile of standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
-0.3
Second quartile (Median) of kurtosis among attributes of the numeric type.
4.31
Second quartile (Median) of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
-0.01
Second quartile (Median) of skewness among attributes of the numeric type.
0.71
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
1.05
Third quartile of kurtosis among attributes of the numeric type.
7.13
Third quartile of means among attributes of the numeric type.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.58
Third quartile of skewness among attributes of the numeric type.
2.36
Third quartile of standard deviation of attributes of the numeric type.
-0.13
Average class difference between consecutive instances.
11.13
Mean of means among attributes of the numeric type.
Entropy of the target attribute values.
0.19
Number of attributes divided by the number of instances.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Maximum entropy among attributes.
41.14
Maximum kurtosis among attributes of the numeric type.
195.36
Maximum of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
4.9
Maximum skewness among attributes of the numeric type.
53.58
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
1.17
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
Average mutual information between the nominal attributes and the target attribute.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Average number of distinct values among the attributes of the nominal type.
0.08
Mean skewness among attributes of the numeric type.
3.19
Mean standard deviation of attributes of the numeric type.
Minimal entropy among attributes.
-1.32
Minimum kurtosis among attributes of the numeric type.
-0.29
Minimum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
-1.64
Minimum skewness among attributes of the numeric type.
0.04
Minimum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.

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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