Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1293274

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1293274

deactivated ARFF Publicly available Visibility: public Uploaded 16-07-2016 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: CHEMBL1293274 (TID: 103707), and it has 224 rows and 67 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.

69 features

pXC50 (target)numeric102 unique values
0 missing
molecule_id (row identifier)nominal224 unique values
0 missing
SM04_EA.bo.numeric187 unique values
0 missing
piIDnumeric208 unique values
0 missing
P_VSA_LogP_4numeric113 unique values
0 missing
piPC04numeric188 unique values
0 missing
piPC03numeric174 unique values
0 missing
D.Dtr05numeric116 unique values
0 missing
Eig03_EA.bo.numeric177 unique values
0 missing
SM13_AEA.ri.numeric177 unique values
0 missing
SpMax3_Bh.s.numeric141 unique values
0 missing
nCsp2numeric24 unique values
0 missing
O.numeric94 unique values
0 missing
TPSA.Tot.numeric160 unique values
0 missing
TPSA.NO.numeric156 unique values
0 missing
SpMax4_Bh.s.numeric169 unique values
0 missing
PCDnumeric208 unique values
0 missing
Eig05_EA.bo.numeric190 unique values
0 missing
SM15_AEA.ri.numeric190 unique values
0 missing
Eig06_AEA.ri.numeric195 unique values
0 missing
ZM2Kupnumeric215 unique values
0 missing
Eig05_AEA.bo.numeric191 unique values
0 missing
Eig09_AEA.bo.numeric154 unique values
0 missing
Eig09_EA.bo.numeric156 unique values
0 missing
Xindexnumeric149 unique values
0 missing
SM06_EA.bo.numeric195 unique values
0 missing
Eta_epsi_Anumeric128 unique values
0 missing
Eig07_EA.bo.numeric178 unique values
0 missing
Menumeric70 unique values
0 missing
piPC02numeric125 unique values
0 missing
SM02_EA.bo.numeric125 unique values
0 missing
SM03_AEA.bo.numeric176 unique values
0 missing
SaaOnumeric42 unique values
0 missing
nFuranesnumeric3 unique values
0 missing
SM03_EA.bo.numeric80 unique values
0 missing
Eig08_AEA.bo.numeric167 unique values
0 missing
NaasCnumeric9 unique values
0 missing
SM04_AEA.bo.numeric186 unique values
0 missing
Eig06_EA.ed.numeric202 unique values
0 missing
SM15_AEA.dm.numeric202 unique values
0 missing
SM05_AEA.bo.numeric186 unique values
0 missing
SM05_EA.bo.numeric191 unique values
0 missing
piPC05numeric199 unique values
0 missing
Uinumeric27 unique values
0 missing
P_VSA_s_6numeric140 unique values
0 missing
P_VSA_e_5numeric74 unique values
0 missing
ZM1Pernumeric218 unique values
0 missing
Yindexnumeric182 unique values
0 missing
SpMax2_Bh.s.numeric110 unique values
0 missing
Eig07_EA.ed.numeric198 unique values
0 missing
SM02_AEA.ri.numeric198 unique values
0 missing
NaaOnumeric3 unique values
0 missing
Vindexnumeric125 unique values
0 missing
SpMax4_Bh.m.numeric186 unique values
0 missing
Eig07_AEA.ed.numeric190 unique values
0 missing
nCb.numeric10 unique values
0 missing
SM06_AEA.bo.numeric189 unique values
0 missing
ZM2Pernumeric221 unique values
0 missing
Eig04_EA.bo.numeric196 unique values
0 missing
SM14_AEA.ri.numeric196 unique values
0 missing
Eig06_EA.bo.numeric185 unique values
0 missing
ZM1MulPernumeric218 unique values
0 missing
P_VSA_p_2numeric156 unique values
0 missing
Eig10_EA.ed.numeric167 unique values
0 missing
SM05_AEA.ri.numeric167 unique values
0 missing
SpMAD_EA.bo.numeric158 unique values
0 missing
ATSC1enumeric130 unique values
0 missing
Eig08_EA.bo.numeric167 unique values
0 missing
P_VSA_LogP_6numeric49 unique values
0 missing

62 properties

224
Number of instances (rows) of the dataset.
69
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.
68
Number of numeric attributes.
1
Number of nominal attributes.
98.55
Percentage of numeric attributes.
8.12
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.
1.45
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.
-2.41
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
0.56
Third quartile of skewness among attributes of the numeric type.
1.81
Maximum skewness among attributes of the numeric type.
0.02
Minimum standard deviation of attributes of the numeric type.
0.2
First quartile of kurtosis among attributes of the numeric type.
1.83
Third quartile of standard deviation of attributes of the numeric type.
159.58
Maximum 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.
2.3
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.
1.44
Mean kurtosis among attributes of the numeric type.
-0.99
First quartile of skewness among attributes of the numeric type.
39.29
Mean of means among attributes of the numeric type.
0.35
First quartile of standard deviation of attributes of the numeric type.
0.58
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.
1.17
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.31
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
4.09
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.
-0.21
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.
13.57
Mean standard deviation of attributes of the numeric type.
-0.33
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.
0.52
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.58
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
9.35
Maximum kurtosis among attributes of the numeric type.
0.09
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
1.91
Third quartile of kurtosis among attributes of the numeric type.
570.65
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.

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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