Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3041

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3041

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: CHEMBL3041 (TID: 10528), and it has 62 rows and 122 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.

124 features

pXC50 (target)numeric59 unique values
0 missing
molecule_id (row identifier)nominal62 unique values
0 missing
Eta_sh_ynumeric41 unique values
0 missing
MATS2inumeric54 unique values
0 missing
CATS2D_06_DAnumeric4 unique values
0 missing
ATSC3snumeric56 unique values
0 missing
MAXDNnumeric52 unique values
0 missing
SpMax3_Bh.s.numeric28 unique values
0 missing
GATS1vnumeric52 unique values
0 missing
CATS2D_03_DAnumeric5 unique values
0 missing
ATSC7snumeric56 unique values
0 missing
P_VSA_s_6numeric23 unique values
0 missing
SpMax4_Bh.s.numeric32 unique values
0 missing
P_VSA_LogP_4numeric16 unique values
0 missing
DELSnumeric56 unique values
0 missing
ATSC8snumeric56 unique values
0 missing
CATS2D_06_DLnumeric10 unique values
0 missing
D.Dtr12numeric42 unique values
0 missing
Eig01_AEA.bo.numeric31 unique values
0 missing
Eig01_AEA.ed.numeric27 unique values
0 missing
Eig01_AEA.ri.numeric28 unique values
0 missing
Eig01_EAnumeric29 unique values
0 missing
Eig01_EA.ed.numeric32 unique values
0 missing
Eig01_EA.ri.numeric25 unique values
0 missing
Eig03_AEA.ed.numeric37 unique values
0 missing
Eig03_EA.ed.numeric39 unique values
0 missing
MAXDPnumeric56 unique values
0 missing
SM03_EA.ed.numeric41 unique values
0 missing
SM04_EA.ed.numeric44 unique values
0 missing
SM05_EA.ed.numeric44 unique values
0 missing
SM06_EA.ed.numeric43 unique values
0 missing
SM07_AEA.ed.numeric44 unique values
0 missing
SM07_EAnumeric45 unique values
0 missing
SM07_EA.ed.numeric44 unique values
0 missing
SM08_AEA.ed.numeric44 unique values
0 missing
SM08_EAnumeric45 unique values
0 missing
SM08_EA.ed.numeric41 unique values
0 missing
SM09_AEA.bo.numeric29 unique values
0 missing
SM09_AEA.ed.numeric44 unique values
0 missing
SM09_EAnumeric44 unique values
0 missing
SM09_EA.ed.numeric39 unique values
0 missing
SM10_AEA.dm.numeric32 unique values
0 missing
SM10_AEA.ed.numeric44 unique values
0 missing
SM10_EAnumeric45 unique values
0 missing
SM10_EA.ed.numeric37 unique values
0 missing
SM10_EA.ri.numeric46 unique values
0 missing
SM11_AEA.ed.numeric44 unique values
0 missing
SM11_EAnumeric45 unique values
0 missing
SM11_EA.ed.numeric36 unique values
0 missing
SM11_EA.ri.numeric46 unique values
0 missing
SM12_AEA.dm.numeric39 unique values
0 missing
SM12_AEA.ed.numeric44 unique values
0 missing
SM12_EAnumeric44 unique values
0 missing
SM12_EA.ed.numeric37 unique values
0 missing
SM12_EA.ri.numeric43 unique values
0 missing
SM13_AEA.ed.numeric42 unique values
0 missing
SM13_EAnumeric44 unique values
0 missing
SM13_EA.ed.numeric36 unique values
0 missing
SM13_EA.ri.numeric43 unique values
0 missing
SM14_AEA.ed.numeric43 unique values
0 missing
SM14_EAnumeric43 unique values
0 missing
SM14_EA.ed.numeric35 unique values
0 missing
SM14_EA.ri.numeric44 unique values
0 missing
SM15_AEA.ed.numeric44 unique values
0 missing
SM15_EAnumeric45 unique values
0 missing
SM15_EA.ed.numeric35 unique values
0 missing
SM15_EA.ri.numeric42 unique values
0 missing
SpDiam_AEA.bo.numeric30 unique values
0 missing
SpDiam_AEA.ri.numeric41 unique values
0 missing
SpDiam_EAnumeric29 unique values
0 missing
SpDiam_EA.ed.numeric38 unique values
0 missing
SpDiam_EA.ri.numeric25 unique values
0 missing
SpMax_AEA.bo.numeric31 unique values
0 missing
SpMax_AEA.ed.numeric27 unique values
0 missing
SpMax_AEA.ri.numeric28 unique values
0 missing
SpMax_EAnumeric29 unique values
0 missing
SpMax_EA.ed.numeric32 unique values
0 missing
SpMax_EA.ri.numeric25 unique values
0 missing
SRW09numeric20 unique values
0 missing
ATSC6snumeric56 unique values
0 missing
SssssCnumeric56 unique values
0 missing
Eig14_AEA.ed.numeric39 unique values
0 missing
CATS2D_07_LLnumeric16 unique values
0 missing
Vindexnumeric39 unique values
0 missing
Xindexnumeric42 unique values
0 missing
GATS3pnumeric49 unique values
0 missing
MATS2pnumeric52 unique values
0 missing
TIEnumeric56 unique values
0 missing
D.Dtr05numeric33 unique values
0 missing
Eig07_EA.ed.numeric44 unique values
0 missing
SM02_AEA.ri.numeric44 unique values
0 missing
SpDiam_AEA.ed.numeric34 unique values
0 missing
SsCH3numeric49 unique values
0 missing
GATS2inumeric52 unique values
0 missing
Eig01_EA.bo.numeric33 unique values
0 missing
Eig03_AEA.ri.numeric38 unique values
0 missing
Eig03_EAnumeric35 unique values
0 missing
Eig04_AEA.dm.numeric41 unique values
0 missing
Eig04_AEA.ed.numeric42 unique values
0 missing
Eig05_AEA.dm.numeric52 unique values
0 missing
Eig05_AEA.ed.numeric35 unique values
0 missing
GGI2numeric25 unique values
0 missing
GGI4numeric40 unique values
0 missing
MWC07numeric45 unique values
0 missing
MWC08numeric45 unique values
0 missing
MWC09numeric43 unique values
0 missing
MWC10numeric44 unique values
0 missing
SM06_AEA.ed.numeric44 unique values
0 missing
SM09_EA.ri.numeric45 unique values
0 missing
SM11_AEA.bo.numeric35 unique values
0 missing
SM11_AEA.ri.numeric33 unique values
0 missing
SpDiam_EA.bo.numeric33 unique values
0 missing
SpMax3_Bh.m.numeric44 unique values
0 missing
SpMax_EA.bo.numeric33 unique values
0 missing
SRW07numeric15 unique values
0 missing
SRW10numeric45 unique values
0 missing
TWCnumeric45 unique values
0 missing
MATS2vnumeric48 unique values
0 missing
AACnumeric46 unique values
0 missing
AECCnumeric44 unique values
0 missing
ALOGPnumeric56 unique values
0 missing
ALOGP2numeric56 unique values
0 missing
AMRnumeric56 unique values
0 missing
AMWnumeric48 unique values
0 missing

62 properties

62
Number of instances (rows) of the dataset.
124
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.
123
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.
2
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
-0.63
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.
-0.25
Mean skewness among attributes of the numeric type.
9.78
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
5.88
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.
-0.48
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.9
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.68
Second quartile (Median) of standard deviation of attributes of the numeric type.
12.02
Maximum kurtosis among attributes of the numeric type.
-1.31
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
127.92
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.
-0.27
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.
99.19
Percentage of numeric attributes.
19.53
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-1.48
Minimum skewness among attributes of the numeric type.
0.81
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2.56
Maximum skewness among attributes of the numeric type.
0.05
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.06
Third quartile of skewness among attributes of the numeric type.
101.71
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.9
First quartile of kurtosis among attributes of the numeric type.
1.68
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.
4.36
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
-0.18
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.
18.46
Mean of means among attributes of the numeric type.
-0.78
First quartile of skewness among attributes of the numeric type.
-0.4
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.25
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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