Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5137

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5137

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 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: CHEMBL5137 (TID: 12895), and it has 547 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)numeric344 unique values
0 missing
molecule_id (row identifier)nominal547 unique values
0 missing
Eig03_EAnumeric290 unique values
0 missing
SM11_AEA.bo.numeric290 unique values
0 missing
Eig03_EA.bo.numeric274 unique values
0 missing
SM13_AEA.ri.numeric274 unique values
0 missing
RDSQnumeric380 unique values
0 missing
Eig06_AEA.bo.numeric286 unique values
0 missing
X2numeric372 unique values
0 missing
ZM2Vnumeric260 unique values
0 missing
ZM2Pernumeric500 unique values
0 missing
ATS1mnumeric319 unique values
0 missing
ATS5mnumeric431 unique values
0 missing
ZM2MulPernumeric504 unique values
0 missing
Eig08_AEA.dm.numeric360 unique values
0 missing
SM03_AEA.bo.numeric265 unique values
0 missing
ZM2Kupnumeric463 unique values
0 missing
Psi_e_1numeric471 unique values
0 missing
Eig05_AEA.dm.numeric363 unique values
0 missing
Eta_epsinumeric358 unique values
0 missing
MWnumeric376 unique values
0 missing
ZM1Pernumeric498 unique values
0 missing
Eig03_AEA.ri.numeric366 unique values
0 missing
Eig13_AEA.bo.numeric282 unique values
0 missing
Eig13_AEA.ed.numeric240 unique values
0 missing
GGI5numeric240 unique values
0 missing
Eig07_AEA.bo.numeric293 unique values
0 missing
ZM1MulPernumeric500 unique values
0 missing
ATSC6pnumeric502 unique values
0 missing
Eig08_EA.bo.numeric283 unique values
0 missing
MPC01numeric33 unique values
0 missing
MWC01numeric33 unique values
0 missing
nBOnumeric33 unique values
0 missing
SRW02numeric33 unique values
0 missing
ZM1Vnumeric183 unique values
0 missing
ZM2Madnumeric467 unique values
0 missing
SpAD_AEA.ed.numeric378 unique values
0 missing
Dznumeric167 unique values
0 missing
GGI10numeric131 unique values
0 missing
Eig07_EAnumeric284 unique values
0 missing
SM15_AEA.bo.numeric284 unique values
0 missing
XMODnumeric453 unique values
0 missing
ATS8mnumeric414 unique values
0 missing
ATS4mnumeric416 unique values
0 missing
X3solnumeric360 unique values
0 missing
piPC02numeric163 unique values
0 missing
SM02_EA.bo.numeric163 unique values
0 missing
SRW04numeric103 unique values
0 missing
SpAD_EA.ed.numeric379 unique values
0 missing
Eig07_AEA.ri.numeric350 unique values
0 missing
ATSC4inumeric429 unique values
0 missing
ATS2mnumeric334 unique values
0 missing
Eig15_AEA.ed.numeric255 unique values
0 missing
SpMax4_Bh.m.numeric341 unique values
0 missing
P_VSA_LogP_5numeric258 unique values
0 missing
Eig08_EA.ed.numeric297 unique values
0 missing
SM03_AEA.ri.numeric297 unique values
0 missing
GMTIVnumeric500 unique values
0 missing
SM08_AEA.bo.numeric347 unique values
0 missing
Eig06_AEA.ed.numeric312 unique values
0 missing
SpMax4_Bh.p.numeric339 unique values
0 missing
SpMax4_Bh.v.numeric338 unique values
0 missing
IC3numeric352 unique values
0 missing
Eig07_EA.bo.numeric303 unique values
0 missing
ATSC5pnumeric513 unique values
0 missing
GMTInumeric374 unique values
0 missing
SpAD_EA.bo.numeric395 unique values
0 missing
S1Knumeric350 unique values
0 missing
Polnumeric49 unique values
0 missing
X5vnumeric459 unique values
0 missing

62 properties

547
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.
284.05
Mean standard deviation of 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.
Minimal entropy among attributes.
-0.8
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-0.83
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.79
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
0.1
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
5.03
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
1.34
Third quartile of kurtosis among attributes of the numeric type.
22648.8
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.
42.54
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.23
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.
0.07
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
-0.19
Third quartile of skewness among attributes of the numeric type.
0.8
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.45
First quartile of kurtosis among attributes of the numeric type.
11.19
Third quartile of standard deviation of attributes of the numeric type.
13547.03
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
2.56
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
0.72
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.
505.54
Mean of means among attributes of the numeric type.
-1.11
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.35
First quartile of standard deviation of attributes of the numeric type.
0.17
Average class difference between consecutive instances.
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.
Entropy of the target attribute values.
Average number of distinct values among the attributes of the nominal type.
0.57
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.13
Number of attributes divided by the number of instances.
-0.71
Mean skewness among attributes of the numeric type.
4.07
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.

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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