Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3572

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3572

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: CHEMBL3572 (TID: 10517), and it has 801 rows and 67 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.

69 features

pXC50 (target)numeric452 unique values
0 missing
molecule_id (row identifier)nominal801 unique values
0 missing
Eig07_AEA.ed.numeric394 unique values
0 missing
Eig08_AEA.ed.numeric402 unique values
0 missing
TPCnumeric377 unique values
0 missing
Eig09_AEA.ri.numeric433 unique values
0 missing
Eig10_AEA.ed.numeric390 unique values
0 missing
SM05_AEA.bo.numeric407 unique values
0 missing
Eig04_AEA.dm.numeric412 unique values
0 missing
Eig09_AEA.bo.numeric393 unique values
0 missing
Eig04_EA.ed.numeric398 unique values
0 missing
SM13_AEA.dm.numeric398 unique values
0 missing
SM02_AEA.bo.numeric249 unique values
0 missing
Eig04_AEA.ed.numeric344 unique values
0 missing
Eig11_EA.ed.numeric416 unique values
0 missing
SM06_AEA.ri.numeric416 unique values
0 missing
Chi1_AEA.bo.numeric520 unique values
0 missing
Chi1_AEA.dm.numeric520 unique values
0 missing
Chi1_AEA.ed.numeric520 unique values
0 missing
Chi1_AEA.ri.numeric520 unique values
0 missing
Chi1_EAnumeric520 unique values
0 missing
Eig06_AEA.dm.numeric456 unique values
0 missing
MPC01numeric40 unique values
0 missing
MWC01numeric40 unique values
0 missing
nBOnumeric40 unique values
0 missing
SRW02numeric40 unique values
0 missing
TIC2numeric662 unique values
0 missing
SpMax6_Bh.e.numeric337 unique values
0 missing
Svnumeric562 unique values
0 missing
X1Madnumeric670 unique values
0 missing
SNarnumeric176 unique values
0 missing
Eig06_AEA.bo.numeric401 unique values
0 missing
SpAD_EA.bo.numeric591 unique values
0 missing
Eig12_EAnumeric330 unique values
0 missing
SM06_AEA.dm.numeric330 unique values
0 missing
Eig14_AEA.dm.numeric338 unique values
0 missing
SpMaxA_EAnumeric85 unique values
0 missing
Xtnumeric95 unique values
0 missing
SpMax6_Bh.p.numeric308 unique values
0 missing
SpMaxA_AEA.ed.numeric140 unique values
0 missing
GMTInumeric549 unique values
0 missing
nBTnumeric62 unique values
0 missing
SpMaxA_AEA.ri.numeric105 unique values
0 missing
X1numeric486 unique values
0 missing
SpMax6_Bh.i.numeric318 unique values
0 missing
IVDMnumeric281 unique values
0 missing
Eig03_AEA.bo.numeric298 unique values
0 missing
ON0Vnumeric483 unique values
0 missing
X3solnumeric519 unique values
0 missing
SpMax7_Bh.e.numeric320 unique values
0 missing
VvdwMGnumeric555 unique values
0 missing
Vxnumeric555 unique values
0 missing
ISIZnumeric57 unique values
0 missing
nATnumeric57 unique values
0 missing
SpMax2_Bh.e.numeric179 unique values
0 missing
AMRnumeric661 unique values
0 missing
SpMin8_Bh.i.numeric273 unique values
0 missing
piPC01numeric75 unique values
0 missing
SCBOnumeric75 unique values
0 missing
Eig06_EA.bo.numeric411 unique values
0 missing
X2solnumeric504 unique values
0 missing
SAtotnumeric628 unique values
0 missing
Eig03_AEA.ri.numeric356 unique values
0 missing
Eta_epsinumeric519 unique values
0 missing
Eig05_AEA.bo.numeric400 unique values
0 missing
SpMin7_Bh.p.numeric287 unique values
0 missing
GGI2numeric43 unique values
0 missing
X0solnumeric322 unique values
0 missing
Eig03_EA.ri.numeric348 unique values
0 missing

62 properties

801
Number of instances (rows) of the dataset.
69
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.
68
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.
0.09
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.86
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.
-0.38
Mean skewness among attributes of the numeric type.
5.03
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
140.02
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.
-0.22
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.21
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.62
Second quartile (Median) of standard deviation of attributes of the numeric type.
10.54
Maximum kurtosis among attributes of the numeric type.
0.09
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
19403.45
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.
2.25
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.
98.55
Percentage of numeric attributes.
19.07
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.8
Minimum skewness among attributes of the numeric type.
1.45
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
1.73
Maximum skewness among attributes of the numeric type.
0.02
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.07
Third quartile of skewness among attributes of the numeric type.
9017.02
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.13
First quartile of kurtosis among attributes of the numeric type.
3.45
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.
3.17
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
1.41
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.
328.41
Mean of means among attributes of the numeric type.
-0.85
First quartile of skewness among attributes of the numeric type.
0.2
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
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