Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2414

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2414

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: CHEMBL2414 (TID: 10579), and it has 388 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)numeric198 unique values
0 missing
molecule_id (row identifier)nominal388 unique values
0 missing
piPC09numeric272 unique values
0 missing
piPC07numeric266 unique values
0 missing
piPC06numeric262 unique values
0 missing
piPC10numeric278 unique values
0 missing
piPC08numeric268 unique values
0 missing
piPC05numeric250 unique values
0 missing
SM09_EA.bo.numeric254 unique values
0 missing
SM10_EA.bo.numeric258 unique values
0 missing
SpMax1_Bh.i.numeric154 unique values
0 missing
Eig02_EA.bo.numeric158 unique values
0 missing
SM05_EA.bo.numeric227 unique values
0 missing
SM12_AEA.ri.numeric158 unique values
0 missing
Eig02_AEA.bo.numeric188 unique values
0 missing
SpMax3_Bh.m.numeric215 unique values
0 missing
SM04_EA.bo.numeric247 unique values
0 missing
CATS2D_04_AAnumeric7 unique values
0 missing
C.035numeric3 unique values
0 missing
Cl.090numeric2 unique values
0 missing
P_VSA_LogP_6numeric42 unique values
0 missing
nPyrazolesnumeric2 unique values
0 missing
SpMax1_Bh.m.numeric139 unique values
0 missing
piPC04numeric239 unique values
0 missing
MPC10numeric169 unique values
0 missing
PCDnumeric274 unique values
0 missing
SpMax2_Bh.v.numeric169 unique values
0 missing
CATS2D_02_DAnumeric7 unique values
0 missing
C.029numeric3 unique values
0 missing
GATS4mnumeric252 unique values
0 missing
MPC09numeric164 unique values
0 missing
piIDnumeric275 unique values
0 missing
nThiophenesnumeric2 unique values
0 missing
Eig05_AEA.bo.numeric216 unique values
0 missing
CATS2D_09_DDnumeric3 unique values
0 missing
Eig05_EA.bo.numeric197 unique values
0 missing
SM15_AEA.ri.numeric197 unique values
0 missing
GATS3inumeric253 unique values
0 missing
SM03_EA.bo.numeric85 unique values
0 missing
MATS2mnumeric193 unique values
0 missing
X5Anumeric27 unique values
0 missing
SpMax3_Bh.e.numeric177 unique values
0 missing
CATS2D_03_DLnumeric8 unique values
0 missing
IC1numeric291 unique values
0 missing
MATS2pnumeric204 unique values
0 missing
MATS3inumeric244 unique values
0 missing
SpMax2_Bh.e.numeric156 unique values
0 missing
nSnumeric4 unique values
0 missing
SM13_EA.bo.numeric249 unique values
0 missing
TPSA.Tot.numeric146 unique values
0 missing
SM07_EA.bo.numeric261 unique values
0 missing
MPC08numeric151 unique values
0 missing
SM08_AEA.bo.numeric259 unique values
0 missing
SM06_EA.bo.numeric267 unique values
0 missing
SM08_EA.bo.numeric260 unique values
0 missing
X4Anumeric36 unique values
0 missing
GATS4pnumeric257 unique values
0 missing
NaaSnumeric2 unique values
0 missing
MATS8enumeric263 unique values
0 missing
N.073numeric3 unique values
0 missing
SddssSnumeric96 unique values
0 missing
nABnumeric12 unique values
0 missing
SpMax1_Bh.e.numeric131 unique values
0 missing
SaaNnumeric201 unique values
0 missing
X3Anumeric41 unique values
0 missing
SpMax3_Bh.p.numeric190 unique values
0 missing
C.005numeric5 unique values
0 missing
GATS2pnumeric228 unique values
0 missing
Uinumeric24 unique values
0 missing

62 properties

388
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.
0.18
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.83
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.
0.19
Mean skewness among attributes of the numeric type.
3.84
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
1.26
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.
-0.38
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-0.94
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.4
Second quartile (Median) of standard deviation of attributes of the numeric type.
243.55
Maximum kurtosis among attributes of the numeric type.
-1.16
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
91.55
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.
4.23
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.
6.35
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.6
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.
13.87
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.75
Third quartile of skewness among attributes of the numeric type.
33.13
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.14
First quartile of kurtosis among attributes of the numeric type.
0.67
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.
0.62
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
7.31
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.
5.73
Mean of means among attributes of the numeric type.
-0.79
First quartile of skewness among attributes of the numeric type.
0.19
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.15
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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