Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5413

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5413

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: CHEMBL5413 (TID: 100862), and it has 177 rows and 63 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.

65 features

pXC50 (target)numeric136 unique values
0 missing
molecule_id (row identifier)nominal177 unique values
0 missing
Eig01_AEA.ed.numeric25 unique values
0 missing
Eig01_EAnumeric25 unique values
0 missing
Eig01_EA.ed.numeric28 unique values
0 missing
SM09_AEA.bo.numeric25 unique values
0 missing
SM10_AEA.dm.numeric28 unique values
0 missing
SpDiam_EAnumeric25 unique values
0 missing
SpDiam_EA.ed.numeric36 unique values
0 missing
SpMax_AEA.ed.numeric25 unique values
0 missing
SpMax_EAnumeric25 unique values
0 missing
SpMax_EA.ed.numeric28 unique values
0 missing
SpMAD_AEA.dm.numeric71 unique values
0 missing
SpMAD_EA.ed.numeric104 unique values
0 missing
SpMAD_AEA.ed.numeric50 unique values
0 missing
X4Anumeric17 unique values
0 missing
SpMAD_AEA.bo.numeric61 unique values
0 missing
GATS7enumeric139 unique values
0 missing
GATS7snumeric148 unique values
0 missing
CATS2D_02_ALnumeric11 unique values
0 missing
CATS2D_05_LLnumeric15 unique values
0 missing
piPC08numeric111 unique values
0 missing
X5Anumeric15 unique values
0 missing
piPC07numeric113 unique values
0 missing
piPC09numeric120 unique values
0 missing
GATS4mnumeric115 unique values
0 missing
SaaaCnumeric67 unique values
0 missing
SpDiam_AEA.ed.numeric42 unique values
0 missing
CATS2D_07_PPnumeric3 unique values
0 missing
GATS7mnumeric113 unique values
0 missing
SaaNHnumeric55 unique values
0 missing
MATS4mnumeric99 unique values
0 missing
SaaOnumeric28 unique values
0 missing
PW4numeric38 unique values
0 missing
SM15_EA.ed.numeric82 unique values
0 missing
SM13_EA.ed.numeric90 unique values
0 missing
SM14_EA.ed.numeric88 unique values
0 missing
Eig01_AEA.dm.numeric21 unique values
0 missing
SpDiam_AEA.dm.numeric21 unique values
0 missing
SpMax_AEA.dm.numeric21 unique values
0 missing
Eig02_EA.ed.numeric43 unique values
0 missing
SM11_AEA.dm.numeric43 unique values
0 missing
GATS2mnumeric87 unique values
0 missing
SpMin1_Bh.p.numeric39 unique values
0 missing
GATS6snumeric142 unique values
0 missing
SpDiam_AEA.ri.numeric45 unique values
0 missing
Eig15_EA.ri.numeric69 unique values
0 missing
Eig01_EA.dm.numeric18 unique values
0 missing
SpMax_EA.dm.numeric18 unique values
0 missing
piIDnumeric102 unique values
0 missing
SsFnumeric37 unique values
0 missing
Eig09_AEA.dm.numeric74 unique values
0 missing
AMRnumeric147 unique values
0 missing
Eig14_AEA.dm.numeric73 unique values
0 missing
SpMax8_Bh.e.numeric83 unique values
0 missing
piPC06numeric108 unique values
0 missing
X3Anumeric21 unique values
0 missing
C.008numeric10 unique values
0 missing
CATS2D_06_DAnumeric14 unique values
0 missing
CATS2D_09_DAnumeric20 unique values
0 missing
Eig04_AEA.dm.numeric62 unique values
0 missing
MPC05numeric79 unique values
0 missing
SpMin4_Bh.s.numeric72 unique values
0 missing
Eig15_EA.ed.numeric66 unique values
0 missing
SM10_AEA.ri.numeric66 unique values
0 missing

62 properties

177
Number of instances (rows) of the dataset.
65
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.
64
Number of numeric attributes.
1
Number of nominal 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.
Second quartile (Median) of entropy among attributes.
0.37
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
1.09
Second quartile (Median) of kurtosis 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.
0.58
Mean skewness among attributes of the numeric type.
3.96
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
2.61
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.35
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.56
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.29
Second quartile (Median) of standard deviation of attributes of the numeric type.
34.5
Maximum kurtosis among attributes of the numeric type.
0.02
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
256.41
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
8.58
Third quartile of kurtosis 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.
98.46
Percentage of numeric attributes.
7.29
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-1.88
Minimum skewness among attributes of the numeric type.
1.54
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
4
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.65
Third quartile of skewness among attributes of the numeric type.
110.71
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.99
First quartile of kurtosis among attributes of the numeric type.
0.71
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
1.51
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
4.77
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
9.69
Mean of means among attributes of the numeric type.
-0.45
First quartile of skewness among attributes of the numeric type.
0
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.1
First quartile of standard deviation of attributes of the numeric type.

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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