Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL291

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL291

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: CHEMBL291 (TID: 11396), and it has 107 rows and 64 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.

66 features

pXC50 (target)numeric85 unique values
0 missing
molecule_id (row identifier)nominal107 unique values
0 missing
SpMax4_Bh.m.numeric93 unique values
0 missing
ATS6pnumeric100 unique values
0 missing
ATS6vnumeric102 unique values
0 missing
ATS7pnumeric101 unique values
0 missing
SM03_AEA.bo.numeric88 unique values
0 missing
SpAD_EA.bo.numeric98 unique values
0 missing
ATSC7pnumeric100 unique values
0 missing
ATSC8pnumeric103 unique values
0 missing
X2solnumeric91 unique values
0 missing
Eig12_AEA.ri.numeric78 unique values
0 missing
Eig12_EA.ri.numeric78 unique values
0 missing
piPC01numeric58 unique values
0 missing
SCBOnumeric58 unique values
0 missing
SpMax5_Bh.m.numeric89 unique values
0 missing
Eig06_AEA.bo.numeric80 unique values
0 missing
Eig06_EA.ri.numeric79 unique values
0 missing
Eig04_EA.bo.numeric82 unique values
0 missing
Eig11_AEA.bo.numeric70 unique values
0 missing
SM02_AEA.bo.numeric86 unique values
0 missing
SM04_AEA.bo.numeric94 unique values
0 missing
SM14_AEA.ri.numeric82 unique values
0 missing
ATSC6pnumeric103 unique values
0 missing
Eta_Fnumeric103 unique values
0 missing
ATS5pnumeric100 unique values
0 missing
SpMax4_Bh.v.numeric89 unique values
0 missing
Eig09_EA.bo.numeric84 unique values
0 missing
AMRnumeric101 unique values
0 missing
Eta_betanumeric71 unique values
0 missing
Eig11_EA.bo.numeric74 unique values
0 missing
Eta_alphanumeric92 unique values
0 missing
SpMax4_Bh.p.numeric87 unique values
0 missing
ATS1mnumeric95 unique values
0 missing
Eig13_AEA.bo.numeric71 unique values
0 missing
Eig13_EA.bo.numeric80 unique values
0 missing
Eig14_AEA.bo.numeric72 unique values
0 missing
Eig14_EA.bo.numeric77 unique values
0 missing
piPC02numeric75 unique values
0 missing
SM02_EA.bo.numeric75 unique values
0 missing
Eig10_EA.bo.numeric81 unique values
0 missing
Eig06_AEA.ri.numeric86 unique values
0 missing
Eig10_AEA.bo.numeric79 unique values
0 missing
SpMin4_Bh.i.numeric77 unique values
0 missing
ATS5vnumeric100 unique values
0 missing
ATS1vnumeric96 unique values
0 missing
ATS7vnumeric101 unique values
0 missing
Eig09_AEA.bo.numeric82 unique values
0 missing
Eig12_EAnumeric69 unique values
0 missing
SM02_EA.ri.numeric98 unique values
0 missing
SM06_AEA.dm.numeric69 unique values
0 missing
SpAD_EA.ri.numeric103 unique values
0 missing
Eig10_AEA.ri.numeric79 unique values
0 missing
Eig10_EA.ri.numeric83 unique values
0 missing
X1vnumeric102 unique values
0 missing
X2vnumeric102 unique values
0 missing
ZM2Madnumeric102 unique values
0 missing
Eig06_EA.bo.numeric80 unique values
0 missing
Eig15_AEA.bo.numeric82 unique values
0 missing
Eig15_AEA.ed.numeric85 unique values
0 missing
Eig15_EAnumeric76 unique values
0 missing
Eig15_EA.bo.numeric75 unique values
0 missing
Eta_betaPnumeric42 unique values
0 missing
SM09_AEA.dm.numeric76 unique values
0 missing
ATSC3pnumeric102 unique values
0 missing
ATSC5pnumeric103 unique values
0 missing

62 properties

107
Number of instances (rows) of the dataset.
66
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.
65
Number of numeric attributes.
1
Number of nominal attributes.
-0.03
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.62
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
3.62
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.
-0.7
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.
3.82
Mean standard deviation of attributes of the numeric type.
-0.55
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.
0.68
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.25
Minimum kurtosis among attributes of the numeric type.
0.06
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
19.52
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
3.66
Third quartile of kurtosis among attributes of the numeric type.
234.21
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.48
Percentage of numeric attributes.
10.06
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-3.06
Minimum skewness among attributes of the numeric type.
1.52
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.
0.22
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
-0.05
Third quartile of skewness among attributes of the numeric type.
0.75
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.59
First quartile of kurtosis among attributes of the numeric type.
3.47
Third quartile of standard deviation of attributes of the numeric type.
75.96
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
1.85
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.
2.12
Mean kurtosis among attributes of the numeric type.
-1.35
First quartile of skewness among attributes of the numeric type.
13.28
Mean of means among attributes of the numeric type.
0.42
First quartile of standard deviation of attributes of the numeric type.
-0.01
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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