Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1628481

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1628481

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 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: CHEMBL1628481 (TID: 103800), and it has 91 rows and 63 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.

65 features

pXC50 (target)numeric41 unique values
0 missing
molecule_id (row identifier)nominal91 unique values
0 missing
piPC07numeric69 unique values
0 missing
GATS5pnumeric84 unique values
0 missing
Eig01_EA.ri.numeric61 unique values
0 missing
SM12_EA.bo.numeric68 unique values
0 missing
SpMax_EA.ri.numeric61 unique values
0 missing
piPC03numeric54 unique values
0 missing
SM13_EA.bo.numeric70 unique values
0 missing
SM14_EA.bo.numeric70 unique values
0 missing
SM15_EA.bo.numeric72 unique values
0 missing
JGI5numeric22 unique values
0 missing
CATS2D_04_ALnumeric15 unique values
0 missing
SpMax6_Bh.s.numeric65 unique values
0 missing
Eig04_EA.bo.numeric61 unique values
0 missing
MPC07numeric49 unique values
0 missing
SM14_AEA.ri.numeric61 unique values
0 missing
SpMax4_Bh.e.numeric75 unique values
0 missing
Eig01_AEA.bo.numeric52 unique values
0 missing
Eig01_AEA.ed.numeric45 unique values
0 missing
Eig01_AEA.ri.numeric62 unique values
0 missing
Eig01_EAnumeric51 unique values
0 missing
Eig01_EA.ed.numeric53 unique values
0 missing
Eig12_AEA.bo.numeric41 unique values
0 missing
Eig14_AEA.bo.numeric44 unique values
0 missing
Eta_betanumeric54 unique values
0 missing
Eta_Fnumeric91 unique values
0 missing
Eta_FLnumeric81 unique values
0 missing
MPC06numeric44 unique values
0 missing
MWC07numeric69 unique values
0 missing
MWC08numeric64 unique values
0 missing
MWC09numeric67 unique values
0 missing
MWC10numeric68 unique values
0 missing
piIDnumeric68 unique values
0 missing
piPC02numeric42 unique values
0 missing
piPC04numeric61 unique values
0 missing
SM02_EA.bo.numeric42 unique values
0 missing
SM03_EA.ed.numeric54 unique values
0 missing
SM04_EA.ed.numeric69 unique values
0 missing
SM05_AEA.ed.numeric67 unique values
0 missing
SM05_EA.bo.numeric55 unique values
0 missing
SM05_EA.ed.numeric69 unique values
0 missing
SM06_AEA.ed.numeric65 unique values
0 missing
SM06_EAnumeric65 unique values
0 missing
SM06_EA.ed.numeric68 unique values
0 missing
SM06_EA.ri.numeric87 unique values
0 missing
SM07_AEA.bo.numeric65 unique values
0 missing
SM07_AEA.ed.numeric67 unique values
0 missing
SM07_EA.ed.numeric66 unique values
0 missing
SM07_EA.ri.numeric89 unique values
0 missing
SM08_AEA.bo.numeric68 unique values
0 missing
SM08_AEA.ed.numeric68 unique values
0 missing
SM08_EAnumeric68 unique values
0 missing
SM08_EA.ed.numeric68 unique values
0 missing
SM08_EA.ri.numeric89 unique values
0 missing
SM09_AEA.bo.numeric51 unique values
0 missing
SM09_AEA.ed.numeric69 unique values
0 missing
SM09_EAnumeric68 unique values
0 missing
SM09_EA.ed.numeric68 unique values
0 missing
SM09_EA.ri.numeric88 unique values
0 missing
SM10_AEA.dm.numeric53 unique values
0 missing
SM10_AEA.ed.numeric69 unique values
0 missing
SM10_EAnumeric69 unique values
0 missing
SM10_EA.ed.numeric67 unique values
0 missing
SM10_EA.ri.numeric89 unique values
0 missing

62 properties

91
Number of instances (rows) of the dataset.
65
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.
64
Number of numeric attributes.
1
Number of nominal attributes.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
4.44
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
5.4
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.
10.09
Mean of means among attributes of the numeric type.
-0.52
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.34
First quartile of standard deviation of attributes of the numeric type.
0.64
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.
5.04
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.71
Number of attributes divided by the number of instances.
0.47
Mean skewness among attributes of the numeric type.
9.55
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.
0.86
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.
0.97
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-0.5
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.
Maximum entropy among attributes.
16.07
Maximum kurtosis among attributes of the numeric type.
0.03
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
36.08
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.
7.95
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.
98.46
Percentage of numeric attributes.
12.78
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.63
Minimum skewness among attributes of the numeric type.
1.54
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2.55
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.
1.16
Third quartile of skewness among attributes of the numeric type.
8.25
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
2.4
First quartile of kurtosis among attributes of the numeric type.
0.82
Third 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