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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3116

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3116

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 by unknown
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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: CHEMBL3116 (TID: 11626), and it has 507 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)numeric107 unique values
0 missing
SRW04numeric124 unique values
0 missing
ZM1numeric87 unique values
0 missing
ATS8pnumeric420 unique values
0 missing
Eta_Lnumeric466 unique values
0 missing
SM02_AEA.bo.numeric290 unique values
0 missing
Eig10_AEA.bo.numeric338 unique values
0 missing
Eig12_EA.bo.numeric331 unique values
0 missing
Eig10_AEA.ri.numeric382 unique values
0 missing
SRW02numeric41 unique values
0 missing
nBOnumeric41 unique values
0 missing
MWC01numeric41 unique values
0 missing
MPC01numeric41 unique values
0 missing
SM14_AEA.bo.numeric352 unique values
0 missing
Eig06_EAnumeric352 unique values
0 missing
SpMax3_Bh.m.numeric323 unique values
0 missing
X1Madnumeric459 unique values
0 missing
SpAD_EAnumeric440 unique values
0 missing
ATS8inumeric428 unique values
0 missing
SM07_AEA.ri.numeric357 unique values
0 missing
Eig12_EA.ed.numeric357 unique values
0 missing
ATS3inumeric395 unique values
0 missing
ZM2Madnumeric474 unique values
0 missing
Eig14_AEA.ed.numeric325 unique values
0 missing
SpAD_EA.ri.numeric488 unique values
0 missing
Eig05_AEA.bo.numeric346 unique values
0 missing
Eig12_EA.ri.numeric374 unique values
0 missing
SpMax7_Bh.i.numeric324 unique values
0 missing
SpMin3_Bh.m.numeric307 unique values
0 missing
SpMax3_Bh.i.numeric312 unique values
0 missing
ATS6vnumeric432 unique values
0 missing
SpMin3_Bh.v.numeric302 unique values
0 missing
ATS8enumeric432 unique values
0 missing
X3numeric427 unique values
0 missing
ATS8vnumeric423 unique values
0 missing
SM14_AEA.dm.numeric416 unique values
0 missing
Eig10_EA.bo.numeric355 unique values
0 missing
Eig10_EAnumeric332 unique values
0 missing
SpMax4_Bh.m.numeric373 unique values
0 missing
X1Pernumeric470 unique values
0 missing
SpMin3_Bh.e.numeric305 unique values
0 missing
X1Kupnumeric460 unique values
0 missing
ATS6mnumeric418 unique values
0 missing
ATS7vnumeric429 unique values
0 missing
SM04_AEA.dm.numeric332 unique values
0 missing
Eig05_EA.ed.numeric416 unique values
0 missing
ATS7mnumeric430 unique values
0 missing
X2solnumeric433 unique values
0 missing
Psi_i_1numeric462 unique values
0 missing
SpMax3_Bh.v.numeric322 unique values
0 missing
Eig10_EA.ri.numeric373 unique values
0 missing
SpMax3_Bh.p.numeric339 unique values
0 missing
X1vnumeric459 unique values
0 missing
Chi1_AEA.ri.numeric411 unique values
0 missing
SpAD_AEA.ri.numeric488 unique values
0 missing
MWC02numeric87 unique values
0 missing
X2vnumeric468 unique values
0 missing
ATS2pnumeric378 unique values
0 missing
SpMax3_Bh.e.numeric332 unique values
0 missing
SpAD_AEA.bo.numeric445 unique values
0 missing
ATS1pnumeric381 unique values
0 missing
Chi1_EAnumeric411 unique values
0 missing
molecule_id (row identifier)nominal507 unique values
0 missing
Chi1_AEA.ed.numeric411 unique values
0 missing
Chi1_AEA.dm.numeric411 unique values
0 missing
Chi1_AEA.bo.numeric411 unique values
0 missing
X3solnumeric430 unique values
0 missing
SpMax7_Bh.v.numeric346 unique values
0 missing
X1MulPernumeric463 unique values
0 missing
ATS2vnumeric379 unique values
0 missing

62 properties

507
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.
First quartile of mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
98.57
Percentage of numeric attributes.
1.43
Percentage of nominal attributes.
First quartile of entropy among attributes.
0.09
First quartile of kurtosis among attributes of the numeric type.
2.84
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
-1.3
First quartile of skewness among attributes of the numeric type.
0.31
First quartile of standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.4
Second quartile (Median) of kurtosis among attributes of the numeric type.
3.78
Second quartile (Median) of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
-0.58
Second quartile (Median) of skewness among attributes of the numeric type.
0.88
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
2.13
Third quartile of kurtosis among attributes of the numeric type.
9.17
Third quartile of means among attributes of the numeric type.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.26
Third quartile of skewness among attributes of the numeric type.
2.66
Third quartile of standard deviation of attributes of the numeric type.
-0.09
Average class difference between consecutive instances.
12.16
Mean of means among attributes of the numeric type.
Entropy of the target attribute values.
0.14
Number of attributes divided by the number of instances.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Maximum entropy among attributes.
46.67
Maximum kurtosis among attributes of the numeric type.
190.28
Maximum of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
3.16
Maximum skewness among attributes of the numeric type.
55.42
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
2.41
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
Average mutual information between the nominal attributes and the target attribute.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Average number of distinct values among the attributes of the nominal type.
-0.56
Mean skewness among attributes of the numeric type.
3.35
Mean standard deviation of attributes of the numeric type.
Minimal entropy among attributes.
-0.48
Minimum kurtosis among attributes of the numeric type.
0.2
Minimum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
-2.46
Minimum skewness among attributes of the numeric type.
0.16
Minimum 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.

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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