Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2868

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2868

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: CHEMBL2868 (TID: 11680), and it has 395 rows and 66 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.

68 features

pXC50 (target)numeric273 unique values
0 missing
molecule_id (row identifier)nominal395 unique values
0 missing
NNRSnumeric11 unique values
0 missing
SdOnumeric355 unique values
0 missing
ATSC5snumeric371 unique values
0 missing
BACnumeric104 unique values
0 missing
ATSC5enumeric328 unique values
0 missing
PW5numeric31 unique values
0 missing
DELSnumeric372 unique values
0 missing
Rbridnumeric5 unique values
0 missing
ATSC4enumeric318 unique values
0 missing
Eig06_EA.dm.numeric40 unique values
0 missing
Eig07_EA.dm.numeric25 unique values
0 missing
Eig08_EA.dm.numeric24 unique values
0 missing
Eig09_EA.dm.numeric17 unique values
0 missing
CATS2D_08_DAnumeric15 unique values
0 missing
nHAccnumeric25 unique values
0 missing
nHetnumeric25 unique values
0 missing
TPSA.NO.numeric141 unique values
0 missing
TPSA.Tot.numeric148 unique values
0 missing
SsssCHnumeric233 unique values
0 missing
ATSC7enumeric310 unique values
0 missing
ATSC6snumeric370 unique values
0 missing
SM03_EA.dm.numeric52 unique values
0 missing
GGI5numeric186 unique values
0 missing
nDBnumeric15 unique values
0 missing
ATSC2snumeric367 unique values
0 missing
SsNH2numeric99 unique values
0 missing
Eig05_EA.dm.numeric35 unique values
0 missing
P_VSA_p_3numeric295 unique values
0 missing
P_VSA_v_3numeric295 unique values
0 missing
CATS2D_08_PLnumeric8 unique values
0 missing
SM04_EA.dm.numeric132 unique values
0 missing
ATSC2enumeric255 unique values
0 missing
P_VSA_e_3numeric85 unique values
0 missing
Eig11_EA.dm.numeric15 unique values
0 missing
P_VSA_s_6numeric106 unique values
0 missing
Eig12_EA.dm.numeric16 unique values
0 missing
Eig13_EA.dm.numeric20 unique values
0 missing
Eig14_EA.dm.numeric17 unique values
0 missing
Eig15_EA.dm.numeric18 unique values
0 missing
SM02_EA.dm.numeric127 unique values
0 missing
SpAD_EA.dm.numeric134 unique values
0 missing
NdOnumeric13 unique values
0 missing
SpMax4_Bh.e.numeric180 unique values
0 missing
ATSC4snumeric370 unique values
0 missing
SpMax4_Bh.i.numeric172 unique values
0 missing
MSDnumeric274 unique values
0 missing
SpMaxA_EA.ed.numeric147 unique values
0 missing
SM05_EA.dm.numeric82 unique values
0 missing
SpMax4_Bh.v.numeric184 unique values
0 missing
SdssCnumeric328 unique values
0 missing
C.008numeric9 unique values
0 missing
Eig12_AEA.dm.numeric150 unique values
0 missing
SM07_EA.dm.numeric84 unique values
0 missing
GATS5snumeric301 unique values
0 missing
DECCnumeric244 unique values
0 missing
AECCnumeric259 unique values
0 missing
ATSC6enumeric329 unique values
0 missing
SpMin4_Bh.e.numeric171 unique values
0 missing
Chi1_EA.dm.numeric287 unique values
0 missing
CATS2D_07_DPnumeric6 unique values
0 missing
PW4numeric59 unique values
0 missing
SpMax7_Bh.m.numeric232 unique values
0 missing
CATS2D_09_APnumeric11 unique values
0 missing
SpMin4_Bh.i.numeric162 unique values
0 missing
Eig07_EAnumeric202 unique values
0 missing
SM15_AEA.bo.numeric202 unique values
0 missing

62 properties

395
Number of instances (rows) of the dataset.
68
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.
67
Number of numeric attributes.
1
Number of nominal attributes.
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.
0.17
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
-0.51
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.
0.73
Mean skewness among attributes of the numeric type.
2.26
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
24.67
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.
0.97
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.38
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
1.28
Second quartile (Median) of standard deviation of attributes of the numeric type.
5.46
Maximum kurtosis among attributes of the numeric type.
-2.85
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
238.44
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.
0.24
Third quartile of kurtosis 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.
98.53
Percentage of numeric attributes.
11.78
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-1.26
Minimum skewness among attributes of the numeric type.
1.47
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2.33
Maximum skewness among attributes of the numeric type.
0.01
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.17
Third quartile of skewness among attributes of the numeric type.
224.89
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.78
First quartile of kurtosis among attributes of the numeric type.
8.79
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
0.7
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
-0.04
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.
30.61
Mean of means among attributes of the numeric type.
0.21
First quartile of skewness among attributes of the numeric type.
0.03
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.4
First quartile of standard deviation of attributes of the numeric type.

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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