Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1980

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1980

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: CHEMBL1980 (TID: 11480), and it has 361 rows and 66 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.

68 features

pXC50 (target)numeric158 unique values
0 missing
molecule_id (row identifier)nominal361 unique values
0 missing
nDBnumeric5 unique values
0 missing
NdssCnumeric5 unique values
0 missing
P_VSA_e_5numeric34 unique values
0 missing
CATS2D_05_DLnumeric12 unique values
0 missing
NdOnumeric5 unique values
0 missing
O.058numeric5 unique values
0 missing
CATS2D_04_AAnumeric7 unique values
0 missing
JGI2numeric60 unique values
0 missing
MATS7inumeric227 unique values
0 missing
SpDiam_AEA.ri.numeric224 unique values
0 missing
SM12_EA.ed.numeric228 unique values
0 missing
SM13_EA.ed.numeric220 unique values
0 missing
SpMin1_Bh.s.numeric171 unique values
0 missing
JGI5numeric31 unique values
0 missing
PDInumeric101 unique values
0 missing
C.030numeric2 unique values
0 missing
SM14_EA.ed.numeric224 unique values
0 missing
SM15_EA.ed.numeric225 unique values
0 missing
SM10_EA.ed.numeric239 unique values
0 missing
GATS7vnumeric239 unique values
0 missing
SpMax1_Bh.i.numeric130 unique values
0 missing
nPyrrolesnumeric2 unique values
0 missing
piIDnumeric241 unique values
0 missing
SM09_EA.ed.numeric235 unique values
0 missing
MATS1inumeric169 unique values
0 missing
SpMin1_Bh.v.numeric119 unique values
0 missing
SM12_EA.dm.numeric89 unique values
0 missing
N.073numeric3 unique values
0 missing
SM08_EA.ed.numeric235 unique values
0 missing
H.050numeric7 unique values
0 missing
nHDonnumeric7 unique values
0 missing
SAdonnumeric21 unique values
0 missing
GATS7pnumeric251 unique values
0 missing
O.numeric66 unique values
0 missing
Hynumeric153 unique values
0 missing
SM02_EA.dm.numeric131 unique values
0 missing
CATS2D_02_ALnumeric14 unique values
0 missing
ARRnumeric76 unique values
0 missing
SdOnumeric266 unique values
0 missing
SM07_EA.ed.numeric232 unique values
0 missing
nABnumeric12 unique values
0 missing
nCONNnumeric2 unique values
0 missing
MATS7pnumeric230 unique values
0 missing
CATS2D_08_LLnumeric22 unique values
0 missing
SM12_AEA.ed.numeric233 unique values
0 missing
nCrqnumeric2 unique values
0 missing
SM13_AEA.ed.numeric241 unique values
0 missing
SM14_AEA.ed.numeric240 unique values
0 missing
SM15_AEA.ed.numeric239 unique values
0 missing
SM03_EA.dm.numeric53 unique values
0 missing
CATS2D_04_DLnumeric10 unique values
0 missing
N.numeric79 unique values
0 missing
SaasNnumeric49 unique values
0 missing
C.043numeric3 unique values
0 missing
NsssCHnumeric6 unique values
0 missing
C.033numeric3 unique values
0 missing
Eta_betaS_Anumeric91 unique values
0 missing
SM11_AEA.ed.numeric236 unique values
0 missing
SM10_EA.ri.numeric321 unique values
0 missing
SM06_EA.ed.numeric231 unique values
0 missing
nThiazolesnumeric2 unique values
0 missing
TRSnumeric22 unique values
0 missing
SM05_EA.ed.numeric223 unique values
0 missing
H.048numeric4 unique values
0 missing
GATS7inumeric260 unique values
0 missing
nPyrimidinesnumeric2 unique values
0 missing

62 properties

361
Number of instances (rows) of the dataset.
68
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.
67
Number of numeric attributes.
1
Number of nominal attributes.
Third quartile of entropy among attributes.
32.65
Maximum kurtosis among attributes of the numeric type.
-0.1
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
2.02
Third quartile of kurtosis among attributes of the numeric type.
45.07
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.
15.9
Third quartile of means 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.
98.53
Percentage of numeric 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.
-1.56
Minimum skewness among attributes of the numeric type.
1.47
Percentage of nominal attributes.
1.24
Third quartile of skewness among attributes of the numeric type.
3.65
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.
1.45
Third quartile of standard deviation of attributes of the numeric type.
27.16
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.27
First quartile of kurtosis 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.
Number of instances belonging to the least frequent class.
0.3
First quartile of means among attributes of the numeric type.
2.35
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.
8.88
Mean of means among attributes of the numeric type.
-0.42
First quartile of skewness among attributes of the numeric type.
0.6
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.29
First quartile of standard deviation of attributes of the numeric type.
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.
0.19
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.54
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.
0.52
Mean skewness among attributes of the numeric type.
2.06
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
1.98
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.
0.06
Second quartile (Median) of skewness among attributes of the numeric type.
0.76
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.4
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.

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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