Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5936

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5936

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 by Noureddin Sadawi
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL5936 (TID: 101608), and it has 163 rows and 65 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.

67 features

pXC50 (target)numeric149 unique values
0 missing
molecule_id (row identifier)nominal163 unique values
0 missing
SpMax4_Bh.s.numeric77 unique values
0 missing
SaaaCnumeric76 unique values
0 missing
C.029numeric4 unique values
0 missing
CATS2D_02_DAnumeric7 unique values
0 missing
CATS2D_04_DLnumeric11 unique values
0 missing
P_VSA_e_3numeric43 unique values
0 missing
P_VSA_i_4numeric50 unique values
0 missing
PCDnumeric128 unique values
0 missing
SpMax3_Bh.s.numeric76 unique values
0 missing
CATS2D_04_APnumeric5 unique values
0 missing
C.041numeric2 unique values
0 missing
nCONNnumeric2 unique values
0 missing
Eig04_EAnumeric103 unique values
0 missing
SM12_AEA.bo.numeric103 unique values
0 missing
D.Dtr10numeric58 unique values
0 missing
NaaaCnumeric5 unique values
0 missing
NNRSnumeric8 unique values
0 missing
nR10numeric4 unique values
0 missing
Rbridnumeric4 unique values
0 missing
RCInumeric15 unique values
0 missing
RFDnumeric15 unique values
0 missing
C.034numeric4 unique values
0 missing
Eig01_EA.ri.numeric60 unique values
0 missing
SpDiam_EA.ri.numeric66 unique values
0 missing
SpMax_EA.ri.numeric60 unique values
0 missing
CATS2D_00_DDnumeric5 unique values
0 missing
CATS2D_00_DPnumeric5 unique values
0 missing
CATS2D_00_PPnumeric5 unique values
0 missing
N.069numeric3 unique values
0 missing
NsNH2numeric5 unique values
0 missing
SpMin1_Bh.v.numeric69 unique values
0 missing
SpMin1_Bh.m.numeric74 unique values
0 missing
SM05_EA.bo.numeric89 unique values
0 missing
CATS2D_03_DPnumeric2 unique values
0 missing
nImidazolesnumeric3 unique values
0 missing
Eig03_EA.dm.numeric15 unique values
0 missing
Eig01_AEA.bo.numeric46 unique values
0 missing
Eig01_EA.bo.numeric35 unique values
0 missing
SM11_AEA.ri.numeric35 unique values
0 missing
SpDiam_EA.bo.numeric35 unique values
0 missing
SpMax_AEA.bo.numeric46 unique values
0 missing
SpMax_EA.bo.numeric35 unique values
0 missing
N.073numeric3 unique values
0 missing
NaasNnumeric3 unique values
0 missing
CATS2D_02_APnumeric4 unique values
0 missing
nArNH2numeric3 unique values
0 missing
SpMax6_Bh.s.numeric118 unique values
0 missing
Eig01_AEA.dm.numeric62 unique values
0 missing
SpDiam_AEA.dm.numeric62 unique values
0 missing
SpMax_AEA.dm.numeric62 unique values
0 missing
CATS2D_03_DDnumeric3 unique values
0 missing
SM08_EA.bo.numeric115 unique values
0 missing
SpMin1_Bh.e.numeric67 unique values
0 missing
SpMin1_Bh.i.numeric67 unique values
0 missing
SpMin1_Bh.p.numeric68 unique values
0 missing
piPC10numeric122 unique values
0 missing
CATS2D_04_DAnumeric5 unique values
0 missing
Eig04_EA.ed.numeric107 unique values
0 missing
H.050numeric9 unique values
0 missing
Hynumeric107 unique values
0 missing
nHDonnumeric9 unique values
0 missing
SM13_AEA.dm.numeric107 unique values
0 missing
nHAccnumeric13 unique values
0 missing
MATS2enumeric114 unique values
0 missing
Eig04_AEA.ri.numeric123 unique values
0 missing

62 properties

163
Number of instances (rows) of the dataset.
67
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.
66
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.
0.41
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
-0.35
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.
0.6
Mean skewness among attributes of the numeric type.
2.2
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
4.51
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.
0.54
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-2.01
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.51
Second quartile (Median) of standard deviation of attributes of the numeric type.
10.03
Maximum kurtosis among attributes of the numeric type.
0.17
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
105.37
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.
2.56
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.
98.51
Percentage of numeric attributes.
4.68
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-0.59
Minimum skewness among attributes of the numeric type.
1.49
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2.77
Maximum skewness among attributes of the numeric type.
0.06
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.14
Third quartile of skewness among attributes of the numeric type.
178.07
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.23
First quartile of kurtosis among attributes of the numeric type.
0.95
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.
0.95
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
1
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.
7.15
Mean of means among attributes of the numeric type.
0.07
First quartile of skewness among attributes of the numeric type.
0.28
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.22
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
Define a new task