Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4601

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4601

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: CHEMBL4601 (TID: 30026), and it has 553 rows and 68 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.

70 features

pXC50 (target)numeric92 unique values
0 missing
molecule_id (row identifier)nominal553 unique values
0 missing
N.073numeric4 unique values
0 missing
CATS2D_09_AAnumeric5 unique values
0 missing
C.033numeric4 unique values
0 missing
H.048numeric4 unique values
0 missing
nArCONR2numeric2 unique values
0 missing
nNnumeric10 unique values
0 missing
SpMax4_Bh.e.numeric384 unique values
0 missing
SpMin7_Bh.v.numeric321 unique values
0 missing
nPyrazinesnumeric2 unique values
0 missing
Eig07_EA.ed.numeric452 unique values
0 missing
SM02_AEA.ri.numeric452 unique values
0 missing
SpMin8_Bh.p.numeric329 unique values
0 missing
SpMax4_Bh.i.numeric380 unique values
0 missing
CATS2D_03_DAnumeric5 unique values
0 missing
SpMin8_Bh.i.numeric289 unique values
0 missing
D.Dtr05numeric389 unique values
0 missing
SpMin8_Bh.e.numeric301 unique values
0 missing
C.006numeric10 unique values
0 missing
Rperimnumeric31 unique values
0 missing
X4numeric475 unique values
0 missing
Eig15_AEA.bo.numeric366 unique values
0 missing
Chi1_EA.dm.numeric482 unique values
0 missing
NRSnumeric6 unique values
0 missing
Chi0_EA.dm.numeric469 unique values
0 missing
Eig14_AEA.ri.numeric428 unique values
0 missing
SpMin8_Bh.v.numeric326 unique values
0 missing
SpMax1_Bh.e.numeric197 unique values
0 missing
CATS2D_07_DDnumeric4 unique values
0 missing
Eig01_EA.bo.numeric294 unique values
0 missing
SM11_AEA.ri.numeric294 unique values
0 missing
SpDiam_EA.bo.numeric295 unique values
0 missing
SpMax_EA.bo.numeric294 unique values
0 missing
Eig15_AEA.ed.numeric337 unique values
0 missing
SpMin7_Bh.e.numeric309 unique values
0 missing
ATS2inumeric418 unique values
0 missing
Eig14_EA.bo.numeric392 unique values
0 missing
SpMin7_Bh.p.numeric338 unique values
0 missing
Eig06_EA.bo.numeric391 unique values
0 missing
ZM2Madnumeric537 unique values
0 missing
SsssNnumeric167 unique values
0 missing
Xindexnumeric229 unique values
0 missing
Eig14_AEA.bo.numeric375 unique values
0 missing
SpMin8_Bh.m.numeric314 unique values
0 missing
SpMin7_Bh.i.numeric306 unique values
0 missing
IC1numeric395 unique values
0 missing
SpMax7_Bh.i.numeric325 unique values
0 missing
SpMax4_Bh.v.numeric384 unique values
0 missing
SpMax8_Bh.e.numeric328 unique values
0 missing
MDDDnumeric490 unique values
0 missing
nHetnumeric13 unique values
0 missing
SpMin4_Bh.i.numeric344 unique values
0 missing
SpAD_EAnumeric497 unique values
0 missing
SpMax8_Bh.i.numeric340 unique values
0 missing
SpMin7_Bh.m.numeric329 unique values
0 missing
SpMax4_Bh.p.numeric398 unique values
0 missing
SpAD_AEA.ri.numeric541 unique values
0 missing
ATS1enumeric390 unique values
0 missing
MPC03numeric73 unique values
0 missing
NsssNnumeric4 unique values
0 missing
Chi1_AEA.bo.numeric456 unique values
0 missing
Chi1_AEA.dm.numeric456 unique values
0 missing
Chi1_AEA.ed.numeric456 unique values
0 missing
Chi1_AEA.ri.numeric456 unique values
0 missing
Chi1_EAnumeric456 unique values
0 missing
SpAD_AEA.bo.numeric503 unique values
0 missing
LLS_02numeric5 unique values
0 missing
ATS3inumeric428 unique values
0 missing
SpMax8_Bh.v.numeric325 unique values
0 missing

62 properties

553
Number of instances (rows) of the dataset.
70
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.
69
Number of numeric attributes.
1
Number of nominal attributes.
0.51
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.13
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
3.05
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.
-0.13
Mean skewness among 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.
3.42
Mean standard deviation of attributes of the numeric type.
-0.25
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0
Percentage of binary attributes.
0.44
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.78
Minimum kurtosis among attributes of the numeric type.
-0.07
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
11.6
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
2.48
Third quartile of kurtosis among attributes of the numeric type.
203.68
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.57
Percentage of numeric attributes.
6.65
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.02
Minimum skewness among attributes of the numeric type.
1.43
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
0.06
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.4
Third quartile of skewness among attributes of the numeric type.
2.75
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.07
First quartile of kurtosis among attributes of the numeric type.
1.8
Third quartile of standard deviation of attributes of the numeric type.
65.18
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
1.03
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
1.22
Mean kurtosis among attributes of the numeric type.
-0.7
First quartile of skewness among attributes of the numeric type.
10.49
Mean of means among attributes of the numeric type.
0.26
First quartile of standard deviation of attributes of the numeric type.
0.54
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among 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.

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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