Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5626

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5626

deactivated ARFF Publicly available Visibility: public Uploaded 16-07-2016 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: CHEMBL5626 (TID: 101483), and it has 50 rows and 116 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.

118 features

pXC50 (target)numeric45 unique values
0 missing
molecule_id (row identifier)nominal50 unique values
0 missing
SpMin3_Bh.m.numeric26 unique values
0 missing
SpMin2_Bh.s.numeric23 unique values
0 missing
SsNH2numeric46 unique values
0 missing
SpMin1_Bh.p.numeric15 unique values
0 missing
SpMin1_Bh.v.numeric14 unique values
0 missing
SpMin3_Bh.s.numeric24 unique values
0 missing
SpMin4_Bh.s.numeric36 unique values
0 missing
SpMin3_Bh.e.numeric28 unique values
0 missing
SpMin3_Bh.v.numeric27 unique values
0 missing
X5Avnumeric12 unique values
0 missing
ATSC1enumeric37 unique values
0 missing
CATS2D_07_DLnumeric14 unique values
0 missing
Eta_F_Anumeric49 unique values
0 missing
GATS3vnumeric45 unique values
0 missing
Hynumeric28 unique values
0 missing
MATS1mnumeric19 unique values
0 missing
PCRnumeric30 unique values
0 missing
SdssCnumeric49 unique values
0 missing
X3Avnumeric23 unique values
0 missing
X4Avnumeric16 unique values
0 missing
ATS3snumeric43 unique values
0 missing
ATS4inumeric44 unique values
0 missing
ATS7mnumeric45 unique values
0 missing
ATS8mnumeric48 unique values
0 missing
ATS8pnumeric48 unique values
0 missing
ATS8vnumeric44 unique values
0 missing
ATSC4mnumeric49 unique values
0 missing
ATSC8inumeric49 unique values
0 missing
CENTnumeric36 unique values
0 missing
Chi1_AEA.bo.numeric36 unique values
0 missing
Chi1_AEA.dm.numeric36 unique values
0 missing
Chi1_AEA.ed.numeric36 unique values
0 missing
Chi1_AEA.ri.numeric36 unique values
0 missing
Chi1_EAnumeric36 unique values
0 missing
Chi1_EA.bo.numeric45 unique values
0 missing
Chi1_EA.ed.numeric36 unique values
0 missing
Chi1_EA.ri.numeric41 unique values
0 missing
Eig04_EA.ri.numeric21 unique values
0 missing
Eig10_AEA.ri.numeric26 unique values
0 missing
Eig10_EAnumeric25 unique values
0 missing
Eig11_AEA.ri.numeric37 unique values
0 missing
Eig11_EAnumeric26 unique values
0 missing
Eig11_EA.ri.numeric37 unique values
0 missing
Eig12_AEA.ed.numeric29 unique values
0 missing
Eig12_AEA.ri.numeric40 unique values
0 missing
Eig12_EAnumeric32 unique values
0 missing
Eig12_EA.ed.numeric33 unique values
0 missing
Eig12_EA.ri.numeric37 unique values
0 missing
Eig13_AEA.bo.numeric23 unique values
0 missing
Eig13_AEA.ed.numeric31 unique values
0 missing
Eig13_AEA.ri.numeric35 unique values
0 missing
Eig13_EAnumeric31 unique values
0 missing
Eig13_EA.bo.numeric22 unique values
0 missing
Eig13_EA.ed.numeric30 unique values
0 missing
Eig13_EA.ri.numeric32 unique values
0 missing
Eig14_AEA.bo.numeric30 unique values
0 missing
Eig14_EA.bo.numeric29 unique values
0 missing
Eig15_AEA.ed.numeric22 unique values
0 missing
Eig15_EAnumeric22 unique values
0 missing
Eig15_EA.ed.numeric24 unique values
0 missing
Eta_Fnumeric49 unique values
0 missing
GGI8numeric28 unique values
0 missing
IDMnumeric33 unique values
0 missing
MDDDnumeric36 unique values
0 missing
MPC07numeric31 unique values
0 missing
Psi_e_0numeric48 unique values
0 missing
Psi_e_1numeric47 unique values
0 missing
RDSQnumeric36 unique values
0 missing
SdOnumeric49 unique values
0 missing
SM04_AEA.dm.numeric25 unique values
0 missing
SM05_AEA.dm.numeric26 unique values
0 missing
SM06_AEA.dm.numeric32 unique values
0 missing
SM07_AEA.dm.numeric31 unique values
0 missing
SM07_AEA.ri.numeric33 unique values
0 missing
SM08_AEA.ri.numeric30 unique values
0 missing
SM09_AEA.dm.numeric22 unique values
0 missing
SM10_AEA.ri.numeric24 unique values
0 missing
SpAD_AEA.bo.numeric45 unique values
0 missing
SpAD_EA.bo.numeric45 unique values
0 missing
SpMax6_Bh.e.numeric32 unique values
0 missing
SpMax7_Bh.e.numeric23 unique values
0 missing
SpMax7_Bh.i.numeric28 unique values
0 missing
SpMax7_Bh.m.numeric37 unique values
0 missing
SpMax8_Bh.p.numeric39 unique values
0 missing
SpMaxA_AEA.ed.numeric23 unique values
0 missing
SpMaxA_EA.ed.numeric23 unique values
0 missing
SpMin6_Bh.m.numeric37 unique values
0 missing
SpMin6_Bh.s.numeric29 unique values
0 missing
SpMin7_Bh.e.numeric36 unique values
0 missing
SpMin7_Bh.i.numeric25 unique values
0 missing
SpMin7_Bh.p.numeric32 unique values
0 missing
SpMin7_Bh.v.numeric31 unique values
0 missing
SpMin8_Bh.s.numeric25 unique values
0 missing
VARnumeric24 unique values
0 missing
X2numeric36 unique values
0 missing
X2solnumeric36 unique values
0 missing
X2vnumeric49 unique values
0 missing
X4numeric36 unique values
0 missing
X4solnumeric36 unique values
0 missing
SpMAD_EA.ri.numeric28 unique values
0 missing
SpMin3_Bh.i.numeric25 unique values
0 missing
ATSC1snumeric48 unique values
0 missing
GATS2mnumeric35 unique values
0 missing
GATS3pnumeric40 unique values
0 missing
SaaCHnumeric47 unique values
0 missing
CATS2D_06_ALnumeric13 unique values
0 missing
DELSnumeric49 unique values
0 missing
Eig04_AEA.ed.numeric17 unique values
0 missing
Eig04_AEA.ri.numeric22 unique values
0 missing
Eig04_EA.ed.numeric21 unique values
0 missing
Eig09_AEA.ed.numeric20 unique values
0 missing
Eig09_AEA.ri.numeric20 unique values
0 missing
Eig09_EAnumeric20 unique values
0 missing
Eig09_EA.ed.numeric22 unique values
0 missing
Eig11_EA.ed.numeric30 unique values
0 missing
GGI10numeric33 unique values
0 missing

62 properties

50
Number of instances (rows) of the dataset.
118
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.
117
Number of numeric attributes.
1
Number of nominal attributes.
Third quartile of entropy among attributes.
1.63
Maximum kurtosis among attributes of the numeric type.
-5.05
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
-1.53
Third quartile of kurtosis among attributes of the numeric type.
13576.04
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.
9.83
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.
99.15
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.
-1.54
Minimum skewness among attributes of the numeric type.
0.85
Percentage of nominal attributes.
0.42
Third quartile of skewness among attributes of the numeric type.
1.07
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
2.57
Third quartile of standard deviation of attributes of the numeric type.
9459.81
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.8
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.
1.75
First quartile of means among attributes of the numeric type.
-1.56
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.
137.74
Mean of means among attributes of the numeric type.
0.22
First quartile of skewness among attributes of the numeric type.
0.47
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.11
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.
2.36
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
-1.75
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.
0.27
Mean skewness among attributes of the numeric type.
3.62
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
88.23
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.
0.36
Second quartile (Median) of skewness among attributes of the numeric type.
0.41
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.88
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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