Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3024

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3024

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: CHEMBL3024 (TID: 10907), and it has 1443 rows and 70 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.

72 features

pXC50 (target)numeric351 unique values
0 missing
molecule_id (row identifier)nominal1443 unique values
0 missing
nArCONH2numeric3 unique values
0 missing
C.042numeric2 unique values
0 missing
CATS2D_08_PLnumeric8 unique values
0 missing
Chi0_EA.dm.numeric1128 unique values
0 missing
CATS2D_07_APnumeric6 unique values
0 missing
NaasNnumeric3 unique values
0 missing
TPSA.Tot.numeric798 unique values
0 missing
D.Dtr05numeric933 unique values
0 missing
CATS2D_05_APnumeric4 unique values
0 missing
CATS2D_04_APnumeric5 unique values
0 missing
Eig03_EA.dm.numeric80 unique values
0 missing
CATS2D_09_ALnumeric21 unique values
0 missing
Eig02_EA.ed.numeric864 unique values
0 missing
SM11_AEA.dm.numeric864 unique values
0 missing
SsNH2numeric475 unique values
0 missing
CATS2D_02_ALnumeric18 unique values
0 missing
Eig04_EA.dm.numeric69 unique values
0 missing
nArORnumeric5 unique values
0 missing
CATS2D_04_PLnumeric8 unique values
0 missing
SdssCnumeric725 unique values
0 missing
C.035numeric3 unique values
0 missing
P_VSA_s_3numeric1145 unique values
0 missing
CATS2D_04_DAnumeric7 unique values
0 missing
SaaSnumeric255 unique values
0 missing
CATS2D_03_ALnumeric23 unique values
0 missing
SaasNnumeric329 unique values
0 missing
ATSC4enumeric752 unique values
0 missing
X5vnumeric1122 unique values
0 missing
P_VSA_s_6numeric708 unique values
0 missing
ATSC7enumeric754 unique values
0 missing
TWCnumeric760 unique values
0 missing
GATS8inumeric551 unique values
0 missing
SRW07numeric35 unique values
0 missing
P_VSA_LogP_6numeric242 unique values
0 missing
CATS2D_05_DAnumeric11 unique values
0 missing
ATSC2enumeric608 unique values
0 missing
Eig01_AEA.bo.numeric414 unique values
0 missing
SpMax_AEA.bo.numeric414 unique values
0 missing
NssOnumeric5 unique values
0 missing
Eig01_AEA.ed.numeric541 unique values
0 missing
SpMax_AEA.ed.numeric541 unique values
0 missing
Neoplastic.80numeric2 unique values
0 missing
SM15_EAnumeric940 unique values
0 missing
ATS7pnumeric964 unique values
0 missing
SpDiam_EA.ed.numeric777 unique values
0 missing
SpMax3_Bh.m.numeric520 unique values
0 missing
nImidazolesnumeric3 unique values
0 missing
SM13_AEA.ed.numeric912 unique values
0 missing
SpMin5_Bh.s.numeric612 unique values
0 missing
SM14_EAnumeric941 unique values
0 missing
MPC06numeric193 unique values
0 missing
SM08_AEA.bo.numeric733 unique values
0 missing
SpDiam_AEA.ri.numeric480 unique values
0 missing
SM12_AEA.ed.numeric863 unique values
0 missing
CATS2D_02_AAnumeric7 unique values
0 missing
SM11_AEA.ed.numeric878 unique values
0 missing
SM14_AEA.ed.numeric939 unique values
0 missing
CATS2D_06_AAnumeric9 unique values
0 missing
SpMin4_Bh.p.numeric559 unique values
0 missing
CATS2D_03_PLnumeric7 unique values
0 missing
Infective.80numeric2 unique values
0 missing
SpMin7_Bh.p.numeric617 unique values
0 missing
CATS2D_04_AAnumeric9 unique values
0 missing
Eig03_AEA.dm.numeric732 unique values
0 missing
ATSC2snumeric1383 unique values
0 missing
SM15_AEA.ed.numeric949 unique values
0 missing
SM09_EA.ed.numeric953 unique values
0 missing
SM03_EA.bo.numeric137 unique values
0 missing
SpDiam_EA.dm.numeric125 unique values
0 missing
SM10_EA.ed.numeric959 unique values
0 missing

62 properties

1443
Number of instances (rows) of the dataset.
72
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.
71
Number of numeric attributes.
1
Number of nominal attributes.
7.38
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.
1.19
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-1.58
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.66
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.37
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
1027.81
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
17.12
Third quartile of kurtosis among attributes of the numeric type.
117.74
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.61
Percentage of numeric attributes.
12.62
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-19.65
Minimum skewness among attributes of the numeric type.
1.39
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.
0.14
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
2.66
Third quartile of skewness among attributes of the numeric type.
29.81
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
1.68
First quartile of kurtosis among attributes of the numeric type.
1.38
Third quartile of standard deviation of attributes of the numeric type.
220.18
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
0.57
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
50.59
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.
11.26
Mean of means among attributes of the numeric type.
-0.22
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.38
First quartile of standard deviation of attributes of the numeric type.
0.4
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.
2.82
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.05
Number of attributes divided by the number of instances.
2.13
Mean skewness among attributes of the numeric type.
3.04
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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