Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2425

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2425

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: CHEMBL2425 (TID: 10457), and it has 679 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)numeric379 unique values
0 missing
molecule_id (row identifier)nominal679 unique values
0 missing
SRW09numeric22 unique values
0 missing
SRW07numeric11 unique values
0 missing
D.Dtr09numeric155 unique values
0 missing
nR09numeric4 unique values
0 missing
C.043numeric3 unique values
0 missing
D.Dtr05numeric170 unique values
0 missing
nR05numeric3 unique values
0 missing
SRW05numeric4 unique values
0 missing
SpMin1_Bh.p.numeric153 unique values
0 missing
D.Dtr10numeric250 unique values
0 missing
nR10numeric4 unique values
0 missing
NaaOnumeric2 unique values
0 missing
nFuranesnumeric2 unique values
0 missing
SaaOnumeric63 unique values
0 missing
DECCnumeric303 unique values
0 missing
SpMin2_Bh.m.numeric226 unique values
0 missing
nR06numeric5 unique values
0 missing
SpMin2_Bh.i.numeric196 unique values
0 missing
nPyridinesnumeric2 unique values
0 missing
SpMin2_Bh.e.numeric209 unique values
0 missing
ICRnumeric254 unique values
0 missing
CATS2D_07_DLnumeric10 unique values
0 missing
SpMin2_Bh.s.numeric244 unique values
0 missing
SpMin2_Bh.v.numeric177 unique values
0 missing
SpMin1_Bh.v.numeric178 unique values
0 missing
Eig01_AEA.bo.numeric141 unique values
0 missing
SpMax_AEA.bo.numeric141 unique values
0 missing
Eig03_EA.ri.numeric369 unique values
0 missing
Eig06_EA.ed.numeric302 unique values
0 missing
SM15_AEA.dm.numeric302 unique values
0 missing
SpMin1_Bh.i.numeric160 unique values
0 missing
CATS2D_07_PLnumeric8 unique values
0 missing
CATS2D_04_PLnumeric8 unique values
0 missing
D.Dtr06numeric449 unique values
0 missing
Eig06_EAnumeric269 unique values
0 missing
SM14_AEA.bo.numeric269 unique values
0 missing
NaaNHnumeric2 unique values
0 missing
SaaNHnumeric93 unique values
0 missing
Eig06_EA.bo.numeric308 unique values
0 missing
SpMax5_Bh.i.numeric271 unique values
0 missing
Eig06_EA.ri.numeric346 unique values
0 missing
nArNR2numeric2 unique values
0 missing
Eig01_EA.bo.numeric116 unique values
0 missing
SM11_AEA.ri.numeric116 unique values
0 missing
SpDiam_EA.bo.numeric116 unique values
0 missing
SpMax_EA.bo.numeric116 unique values
0 missing
Chi1_EA.dm.numeric508 unique values
0 missing
P_VSA_LogP_4numeric74 unique values
0 missing
X3Anumeric40 unique values
0 missing
JGI3numeric49 unique values
0 missing
ATSC6snumeric666 unique values
0 missing
SpMin1_Bh.e.numeric178 unique values
0 missing
X4Anumeric29 unique values
0 missing
Eig01_EAnumeric162 unique values
0 missing
SM09_AEA.bo.numeric162 unique values
0 missing
SpDiam_EAnumeric162 unique values
0 missing
SpMax_EAnumeric162 unique values
0 missing
IDEnumeric335 unique values
0 missing
SpMin1_Bh.m.numeric205 unique values
0 missing
CATS2D_06_DAnumeric6 unique values
0 missing
GATS6inumeric384 unique values
0 missing
SpMax1_Bh.s.numeric73 unique values
0 missing
Eig06_AEA.bo.numeric294 unique values
0 missing
SpMax1_Bh.m.numeric231 unique values
0 missing
SpMax1_Bh.e.numeric161 unique values
0 missing
GGI10numeric117 unique values
0 missing

62 properties

679
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.
0.66
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.1
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
2.07
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.
0.34
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.
5.13
Mean standard deviation of attributes of the numeric type.
0.23
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.
0.24
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.7
Minimum kurtosis among attributes of the numeric type.
0.05
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
90.08
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
3.88
Third quartile of kurtosis among attributes of the numeric type.
205.04
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.53
Percentage of numeric attributes.
4.48
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.16
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.
The maximum number of distinct values among attributes of the nominal type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.01
Third quartile of skewness among attributes of the numeric type.
8.68
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.07
First quartile of kurtosis among attributes of the numeric type.
1.02
Third quartile of standard deviation of attributes of the numeric type.
74.59
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0.87
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.
3.03
Mean kurtosis among attributes of the numeric type.
-0.68
First quartile of skewness among attributes of the numeric type.
9.15
Mean of means among attributes of the numeric type.
0.09
First quartile of standard deviation of attributes of the numeric type.
-0.08
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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