Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5414

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5414

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: CHEMBL5414 (TID: 100863), and it has 350 rows and 65 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.

67 features

pXC50 (target)numeric234 unique values
0 missing
molecule_id (row identifier)nominal350 unique values
0 missing
CATS2D_04_DLnumeric19 unique values
0 missing
Eig05_AEA.dm.numeric239 unique values
0 missing
CATS2D_07_LLnumeric23 unique values
0 missing
N.072numeric5 unique values
0 missing
P_VSA_LogP_3numeric59 unique values
0 missing
CATS2D_07_DDnumeric3 unique values
0 missing
LLS_01numeric6 unique values
0 missing
CATS2D_06_DDnumeric5 unique values
0 missing
CATS2D_08_LLnumeric26 unique values
0 missing
Eig04_EA.ri.numeric231 unique values
0 missing
CATS2D_09_LLnumeric25 unique values
0 missing
NssNHnumeric5 unique values
0 missing
SssNHnumeric238 unique values
0 missing
SpMin3_Bh.e.numeric184 unique values
0 missing
Eig04_AEA.ri.numeric239 unique values
0 missing
SpMin1_Bh.i.numeric109 unique values
0 missing
Eig12_AEA.dm.numeric212 unique values
0 missing
Chi1_EA.dm.numeric237 unique values
0 missing
IC4numeric248 unique values
0 missing
CATS2D_02_DLnumeric11 unique values
0 missing
SdOnumeric127 unique values
0 missing
SpMin1_Bh.e.numeric111 unique values
0 missing
Eig13_AEA.dm.numeric201 unique values
0 missing
IC5numeric245 unique values
0 missing
Eig12_EAnumeric183 unique values
0 missing
SM06_AEA.dm.numeric183 unique values
0 missing
ATS3pnumeric276 unique values
0 missing
Eig13_EAnumeric171 unique values
0 missing
SM07_AEA.dm.numeric171 unique values
0 missing
Eig11_EA.ri.numeric218 unique values
0 missing
C.025numeric7 unique values
0 missing
ATSC8inumeric282 unique values
0 missing
Eig13_EA.ed.numeric221 unique values
0 missing
SM08_AEA.ri.numeric221 unique values
0 missing
ATSC8vnumeric304 unique values
0 missing
D.Dtr06numeric224 unique values
0 missing
Eig14_AEA.dm.numeric191 unique values
0 missing
Eig13_EA.bo.numeric194 unique values
0 missing
Eig10_AEA.ri.numeric227 unique values
0 missing
CATS2D_05_DLnumeric15 unique values
0 missing
Eig13_AEA.ri.numeric216 unique values
0 missing
Eig13_EA.ri.numeric216 unique values
0 missing
Eig10_EA.ri.numeric232 unique values
0 missing
Eig10_EA.bo.numeric202 unique values
0 missing
Eig11_EA.ed.numeric207 unique values
0 missing
SM06_AEA.ri.numeric207 unique values
0 missing
Eig10_EAnumeric196 unique values
0 missing
SM04_AEA.dm.numeric196 unique values
0 missing
DLS_01numeric3 unique values
0 missing
ATS3vnumeric275 unique values
0 missing
C.041numeric2 unique values
0 missing
Eig11_AEA.ri.numeric226 unique values
0 missing
Eig12_AEA.ri.numeric219 unique values
0 missing
Eig12_EA.ri.numeric225 unique values
0 missing
ATS2pnumeric260 unique values
0 missing
ATS2vnumeric254 unique values
0 missing
ATS5snumeric282 unique values
0 missing
SpMax6_Bh.v.numeric187 unique values
0 missing
SM02_EA.ri.numeric241 unique values
0 missing
Eig12_EA.ed.numeric217 unique values
0 missing
SM07_AEA.ri.numeric217 unique values
0 missing
Eig11_EAnumeric185 unique values
0 missing
SM05_AEA.dm.numeric185 unique values
0 missing
CATS2D_03_DLnumeric16 unique values
0 missing
BIC4numeric157 unique values
0 missing

62 properties

350
Number of instances (rows) of the dataset.
67
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.
66
Number of numeric attributes.
1
Number of nominal attributes.
-0.52
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.19
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.93
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.
0.41
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.
4.63
Mean standard deviation of attributes of the numeric type.
0.12
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0
Percentage of binary attributes.
0.97
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.39
Minimum kurtosis among attributes of the numeric type.
-0.96
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
9.32
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
2.02
Third quartile of kurtosis among attributes of the numeric type.
160.87
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.51
Percentage of numeric attributes.
3.75
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.67
Minimum skewness among attributes of the numeric type.
1.49
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.
0.06
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.21
Third quartile of skewness among attributes of the numeric type.
2.79
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.23
First quartile of kurtosis among attributes of the numeric type.
2.33
Third quartile of standard deviation of attributes of the numeric type.
164.21
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
-0.03
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.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.85
Mean kurtosis among attributes of the numeric type.
-0.06
First quartile of skewness among attributes of the numeric type.
6.09
Mean of means among attributes of the numeric type.
0.51
First quartile of standard deviation of attributes of the numeric type.
-0.32
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.

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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