Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5619

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5619

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: CHEMBL5619 (TID: 101476), and it has 223 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)numeric48 unique values
0 missing
molecule_id (row identifier)nominal223 unique values
0 missing
Eta_sh_ynumeric149 unique values
0 missing
Eta_sh_xnumeric66 unique values
0 missing
MATS1mnumeric153 unique values
0 missing
P_VSA_s_1numeric13 unique values
0 missing
NddssSnumeric5 unique values
0 missing
S.110numeric5 unique values
0 missing
SddssSnumeric93 unique values
0 missing
MATS1enumeric164 unique values
0 missing
SpMax1_Bh.m.numeric128 unique values
0 missing
NdssCnumeric9 unique values
0 missing
MAXDNnumeric208 unique values
0 missing
SpMax1_Bh.s.numeric52 unique values
0 missing
SpDiam_AEA.dm.numeric159 unique values
0 missing
CATS2D_02_AAnumeric8 unique values
0 missing
GATS1enumeric172 unique values
0 missing
Eig01_AEA.dm.numeric159 unique values
0 missing
SpMax_AEA.dm.numeric159 unique values
0 missing
MATS1pnumeric161 unique values
0 missing
GATS1pnumeric183 unique values
0 missing
nCconjnumeric9 unique values
0 missing
nSO2Nnumeric4 unique values
0 missing
CATS2D_05_NLnumeric8 unique values
0 missing
GATS3mnumeric182 unique values
0 missing
IVDEnumeric138 unique values
0 missing
C.017numeric4 unique values
0 missing
nR.Ctnumeric4 unique values
0 missing
Eig01_AEA.bo.numeric148 unique values
0 missing
SpMax_AEA.bo.numeric148 unique values
0 missing
SpDiam_AEA.bo.numeric170 unique values
0 missing
PW5numeric61 unique values
0 missing
SpMax3_Bh.m.numeric186 unique values
0 missing
SpMax3_Bh.p.numeric196 unique values
0 missing
SdssCnumeric180 unique values
0 missing
C.019numeric4 unique values
0 missing
SM11_EAnumeric195 unique values
0 missing
MATS2snumeric165 unique values
0 missing
GATS1mnumeric163 unique values
0 missing
Eig01_EA.bo.numeric152 unique values
0 missing
SM11_AEA.ri.numeric152 unique values
0 missing
SpMax_EA.bo.numeric152 unique values
0 missing
C.numeric109 unique values
0 missing
SM05_EA.ed.numeric190 unique values
0 missing
SM05_EA.bo.numeric181 unique values
0 missing
SpDiam_EA.bo.numeric153 unique values
0 missing
GATS2mnumeric178 unique values
0 missing
DECCnumeric175 unique values
0 missing
SM11_EA.ed.numeric189 unique values
0 missing
Eig01_AEA.ed.numeric140 unique values
0 missing
SpMax_AEA.ed.numeric140 unique values
0 missing
SM13_EA.ed.numeric190 unique values
0 missing
SpMax3_Bh.e.numeric181 unique values
0 missing
Eig03_EA.bo.numeric183 unique values
0 missing
SM13_AEA.ri.numeric183 unique values
0 missing
SM10_EA.ed.numeric195 unique values
0 missing
SM15_EA.ed.numeric182 unique values
0 missing
GATS6pnumeric191 unique values
0 missing
SM15_AEA.ed.numeric195 unique values
0 missing
Eig01_EAnumeric152 unique values
0 missing
SM09_AEA.bo.numeric152 unique values
0 missing
SpMax_EAnumeric152 unique values
0 missing
N.numeric91 unique values
0 missing
nHetnumeric14 unique values
0 missing
SM14_AEA.ed.numeric200 unique values
0 missing
SM09_EAnumeric194 unique values
0 missing
SM12_EA.ed.numeric190 unique values
0 missing
SM14_EA.ed.numeric187 unique values
0 missing
SM09_EA.ed.numeric193 unique values
0 missing
ATSC1mnumeric214 unique values
0 missing

62 properties

223
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.
1.06
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.
3.52
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.
0.1
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.
0.92
Mean standard deviation of attributes of the numeric type.
-0.06
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.
0.51
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.17
Minimum kurtosis among attributes of the numeric type.
-2.02
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
37.46
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
2.35
Third quartile of kurtosis among attributes of the numeric type.
39.74
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.57
Percentage of numeric attributes.
7.46
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-3.41
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.
The maximum number of distinct values among attributes of the nominal type.
0.01
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.73
Third quartile of skewness among attributes of the numeric type.
4.89
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.14
First quartile of kurtosis among attributes of the numeric type.
1.28
Third quartile of standard deviation of attributes of the numeric type.
5.33
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0.77
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.
2.34
Mean kurtosis among attributes of the numeric type.
-0.86
First quartile of skewness among attributes of the numeric type.
7.27
Mean of means among attributes of the numeric type.
0.22
First quartile of standard deviation of attributes of the numeric type.
0.63
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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