Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5409

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5409

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: CHEMBL5409 (TID: 100857), and it has 319 rows and 65 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.

67 features

pXC50 (target)numeric204 unique values
0 missing
molecule_id (row identifier)nominal319 unique values
0 missing
SpDiam_AEA.bo.numeric114 unique values
0 missing
SpMin1_Bh.m.numeric116 unique values
0 missing
Eta_F_Anumeric209 unique values
0 missing
X5Avnumeric33 unique values
0 missing
CATS2D_02_ALnumeric16 unique values
0 missing
SpDiam_AEA.ed.numeric148 unique values
0 missing
BLInumeric174 unique values
0 missing
X1Avnumeric102 unique values
0 missing
MATS1inumeric162 unique values
0 missing
SpMin1_Bh.s.numeric131 unique values
0 missing
MATS1vnumeric116 unique values
0 missing
X3Avnumeric66 unique values
0 missing
X4Avnumeric46 unique values
0 missing
GATS1snumeric183 unique values
0 missing
SpDiam_AEA.ri.numeric165 unique values
0 missing
Eta_betaS_Anumeric79 unique values
0 missing
SpMax1_Bh.e.numeric102 unique values
0 missing
SpMax1_Bh.v.numeric103 unique values
0 missing
SpMin1_Bh.i.numeric86 unique values
0 missing
N.numeric54 unique values
0 missing
SpMin1_Bh.e.numeric99 unique values
0 missing
X2Avnumeric89 unique values
0 missing
SpMax1_Bh.p.numeric103 unique values
0 missing
Eta_epsi_Anumeric123 unique values
0 missing
RCInumeric18 unique values
0 missing
RFDnumeric17 unique values
0 missing
MATS1pnumeric140 unique values
0 missing
SpMin1_Bh.p.numeric105 unique values
0 missing
PCRnumeric113 unique values
0 missing
CATS2D_04_AAnumeric8 unique values
0 missing
Eta_L_Anumeric109 unique values
0 missing
CATS2D_02_LLnumeric43 unique values
0 missing
X.numeric38 unique values
0 missing
SpMin6_Bh.i.numeric160 unique values
0 missing
Mvnumeric108 unique values
0 missing
SpMin8_Bh.s.numeric191 unique values
0 missing
Menumeric64 unique values
0 missing
CATS2D_03_DLnumeric13 unique values
0 missing
ATSC6mnumeric289 unique values
0 missing
CATS2D_02_DLnumeric8 unique values
0 missing
CATS2D_04_DLnumeric15 unique values
0 missing
H.numeric105 unique values
0 missing
ATSC3mnumeric271 unique values
0 missing
ATS6inumeric262 unique values
0 missing
nCrsnumeric12 unique values
0 missing
SpMAD_EA.ri.numeric162 unique values
0 missing
NaasCnumeric9 unique values
0 missing
GATS1vnumeric161 unique values
0 missing
P_VSA_MR_1numeric51 unique values
0 missing
SsOHnumeric114 unique values
0 missing
nCb.numeric7 unique values
0 missing
CATS2D_01_LLnumeric30 unique values
0 missing
CATS2D_05_DLnumeric16 unique values
0 missing
ATSC2pnumeric231 unique values
0 missing
P_VSA_MR_7numeric27 unique values
0 missing
Eig01_AEA.bo.numeric96 unique values
0 missing
SpMax_AEA.bo.numeric96 unique values
0 missing
CATS2D_03_LLnumeric45 unique values
0 missing
piPC07numeric196 unique values
0 missing
ATSC3pnumeric268 unique values
0 missing
PCDnumeric177 unique values
0 missing
SpMAD_EAnumeric112 unique values
0 missing
N.071numeric2 unique values
0 missing
nArNR2numeric2 unique values
0 missing
C.004numeric6 unique values
0 missing

62 properties

319
Number of instances (rows) of the dataset.
67
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.
66
Number of numeric attributes.
1
Number of nominal attributes.
-1.25
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.21
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
2.1
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.
0.41
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.
5.54
Mean standard deviation of attributes of the numeric type.
0.27
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.
0.26
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.86
Minimum kurtosis among attributes of the numeric type.
-0.02
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
7.49
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
-0.71
Third quartile of kurtosis among attributes of the numeric type.
304.54
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.51
Percentage of numeric attributes.
5.56
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-0.32
Minimum skewness among attributes of the numeric type.
1.49
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.
0.01
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.63
Third quartile of skewness among attributes of the numeric type.
3.07
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.59
First quartile of kurtosis among attributes of the numeric type.
3.26
Third quartile of standard deviation of attributes of the numeric type.
141.6
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0.68
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.
-0.86
Mean kurtosis among attributes of the numeric type.
0.03
First quartile of skewness among attributes of the numeric type.
10.69
Mean of means among attributes of the numeric type.
0.08
First quartile of standard deviation of attributes of the numeric type.
0.18
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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