Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5543

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5543

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: CHEMBL5543 (TID: 101014), and it has 448 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)numeric109 unique values
0 missing
molecule_id (row identifier)nominal448 unique values
0 missing
SpMaxA_AEA.bo.numeric170 unique values
0 missing
SpMax3_Bh.v.numeric319 unique values
0 missing
Psi_i_0numeric418 unique values
0 missing
Chi1_EA.bo.numeric393 unique values
0 missing
X1vnumeric416 unique values
0 missing
SpMaxA_AEA.ed.numeric205 unique values
0 missing
X0solnumeric310 unique values
0 missing
SpMax3_Bh.p.numeric318 unique values
0 missing
Psi_i_1numeric423 unique values
0 missing
SMTInumeric392 unique values
0 missing
SpMaxA_AEA.ri.numeric164 unique values
0 missing
X1solnumeric369 unique values
0 missing
ATS8snumeric377 unique values
0 missing
SpMaxA_EAnumeric139 unique values
0 missing
X2solnumeric395 unique values
0 missing
Eta_Cnumeric433 unique values
0 missing
Chi1_EA.ri.numeric432 unique values
0 missing
ATS6mnumeric381 unique values
0 missing
GMTInumeric393 unique values
0 missing
Eig11_AEA.ed.numeric302 unique values
0 missing
Eig12_EA.bo.numeric307 unique values
0 missing
Spnumeric393 unique values
0 missing
Svnumeric403 unique values
0 missing
TIC2numeric409 unique values
0 missing
SpMax7_Bh.p.numeric311 unique values
0 missing
Eig10_EA.ri.numeric352 unique values
0 missing
Chi0_EA.bo.numeric390 unique values
0 missing
SpMax3_Bh.e.numeric309 unique values
0 missing
SpMin3_Bh.e.numeric310 unique values
0 missing
ATS2enumeric361 unique values
0 missing
ATS1enumeric360 unique values
0 missing
nBTnumeric72 unique values
0 missing
SpMaxA_EA.ri.numeric136 unique values
0 missing
Senumeric398 unique values
0 missing
Eta_Lnumeric425 unique values
0 missing
X2numeric384 unique values
0 missing
ATS8pnumeric379 unique values
0 missing
ATS2vnumeric364 unique values
0 missing
SpMax7_Bh.v.numeric328 unique values
0 missing
ATS7pnumeric383 unique values
0 missing
Eig10_EAnumeric317 unique values
0 missing
Eig10_EA.ed.numeric355 unique values
0 missing
SM04_AEA.dm.numeric317 unique values
0 missing
SM05_AEA.ri.numeric355 unique values
0 missing
Eig06_AEA.ri.numeric363 unique values
0 missing
ATS7vnumeric394 unique values
0 missing
CIDnumeric289 unique values
0 missing
SpMin3_Bh.i.numeric312 unique values
0 missing
ATS1inumeric359 unique values
0 missing
S0Knumeric184 unique values
0 missing
ATS5mnumeric380 unique values
0 missing
SpMax3_Bh.i.numeric298 unique values
0 missing
ISIZnumeric69 unique values
0 missing
nATnumeric69 unique values
0 missing
SpMax4_Bh.m.numeric345 unique values
0 missing
SpMax5_Bh.e.numeric326 unique values
0 missing
Sinumeric400 unique values
0 missing
ATS1vnumeric358 unique values
0 missing
X1MulPernumeric418 unique values
0 missing
SpMaxA_EA.ed.numeric254 unique values
0 missing
Chi0_EA.ri.numeric427 unique values
0 missing
Eig10_EA.bo.numeric338 unique values
0 missing
IVDMnumeric217 unique values
0 missing
X1numeric341 unique values
0 missing
SpMaxA_EA.bo.numeric170 unique values
0 missing
ATS2inumeric369 unique values
0 missing
ATS8enumeric381 unique values
0 missing
Eig11_EA.bo.numeric338 unique values
0 missing

62 properties

448
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.
Third quartile of entropy among attributes.
25.81
Maximum kurtosis among attributes of the numeric type.
0.12
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
1.48
Third quartile of kurtosis among attributes of the numeric type.
9923.96
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.
14.85
Third quartile of means 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.
98.57
Percentage of numeric 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.
-2.27
Minimum skewness among attributes of the numeric type.
1.43
Percentage of nominal attributes.
0.28
Third quartile of skewness among attributes of the numeric type.
1.98
Maximum skewness among attributes of the numeric type.
0.04
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
4.6
Third quartile of standard deviation of attributes of the numeric type.
8175.2
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.36
First quartile of kurtosis 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.
Number of instances belonging to the least frequent class.
2.13
First quartile of means among attributes of the numeric type.
1.12
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.
296.49
Mean of means among attributes of the numeric type.
-1.04
First quartile of skewness among attributes of the numeric type.
0.09
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.34
First quartile of standard deviation of attributes of the numeric type.
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.
0.16
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.02
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.
-0.24
Mean skewness among attributes of the numeric type.
3.85
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
234.8
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.
0.11
Second quartile (Median) of skewness among attributes of the numeric type.
0.97
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.61
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.

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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