Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3728

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3728

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: CHEMBL3728 (TID: 12879), and it has 267 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)numeric38 unique values
0 missing
molecule_id (row identifier)nominal267 unique values
0 missing
nIsoxazolesnumeric2 unique values
0 missing
GATS1snumeric184 unique values
0 missing
MATS1snumeric141 unique values
0 missing
D.Dtr09numeric40 unique values
0 missing
SpMin5_Bh.s.numeric178 unique values
0 missing
Yindexnumeric189 unique values
0 missing
GATS5inumeric209 unique values
0 missing
NssCH2numeric10 unique values
0 missing
nCrtnumeric4 unique values
0 missing
SsFnumeric44 unique values
0 missing
Vindexnumeric126 unique values
0 missing
C.003numeric4 unique values
0 missing
nCtnumeric4 unique values
0 missing
SssCH2numeric159 unique values
0 missing
Xindexnumeric156 unique values
0 missing
Eta_betaP_Anumeric128 unique values
0 missing
F.084numeric3 unique values
0 missing
nCsp3numeric14 unique values
0 missing
H.052numeric6 unique values
0 missing
ATS3inumeric219 unique values
0 missing
nCconjnumeric8 unique values
0 missing
nFnumeric4 unique values
0 missing
NsFnumeric4 unique values
0 missing
P_VSA_e_6numeric4 unique values
0 missing
SpMax1_Bh.s.numeric43 unique values
0 missing
ICRnumeric184 unique values
0 missing
SpMin4_Bh.v.numeric190 unique values
0 missing
SpMin4_Bh.s.numeric194 unique values
0 missing
nRCONR2numeric3 unique values
0 missing
SpMin4_Bh.p.numeric192 unique values
0 missing
ATS3enumeric227 unique values
0 missing
ATSC3inumeric231 unique values
0 missing
CSInumeric214 unique values
0 missing
Eta_L_Anumeric88 unique values
0 missing
ATSC1inumeric201 unique values
0 missing
SpMin3_Bh.e.numeric183 unique values
0 missing
SpMin3_Bh.i.numeric176 unique values
0 missing
Eta_Lnumeric254 unique values
0 missing
Eig01_EA.bo.numeric157 unique values
0 missing
SM11_AEA.ri.numeric157 unique values
0 missing
SpDiam_EA.bo.numeric157 unique values
0 missing
SpMax_EA.bo.numeric157 unique values
0 missing
ECCnumeric180 unique values
0 missing
P_VSA_LogP_6numeric56 unique values
0 missing
SpMin1_Bh.s.numeric163 unique values
0 missing
SpMin3_Bh.m.numeric184 unique values
0 missing
GATS6snumeric234 unique values
0 missing
AECCnumeric223 unique values
0 missing
SpDiam_EA.ri.numeric159 unique values
0 missing
ATSC3vnumeric257 unique values
0 missing
ATSC2inumeric205 unique values
0 missing
HVcpxnumeric208 unique values
0 missing
D.Dtr06numeric242 unique values
0 missing
Eta_betaS_Anumeric79 unique values
0 missing
Eig01_EA.ri.numeric158 unique values
0 missing
SpMax_EA.ri.numeric158 unique values
0 missing
ATSC5vnumeric265 unique values
0 missing
Eta_FL_Anumeric93 unique values
0 missing
ON1Vnumeric223 unique values
0 missing
SaaOnumeric59 unique values
0 missing
SpMin3_Bh.v.numeric181 unique values
0 missing
Eta_beta_Anumeric153 unique values
0 missing
ATSC4vnumeric266 unique values
0 missing
ATSC6vnumeric263 unique values
0 missing
Chi1_EA.bo.numeric242 unique values
0 missing
GATS3inumeric193 unique values
0 missing
ATS4inumeric234 unique values
0 missing

62 properties

267
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.
0.71
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.26
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
1.68
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.
0.67
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.
9.08
Mean standard deviation of attributes of the numeric type.
0.32
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.
0.32
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.83
Minimum 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.
22.24
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
4.25
Third quartile of kurtosis among attributes of the numeric type.
682.42
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.55
Percentage of numeric attributes.
4.71
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-1.89
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.
The maximum number of distinct values among attributes of the nominal type.
0.02
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.63
Third quartile of skewness among attributes of the numeric type.
3.73
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.03
First quartile of kurtosis among attributes of the numeric type.
2.09
Third quartile of standard deviation of attributes of the numeric type.
255.94
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0.65
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.
2.7
Mean kurtosis among attributes of the numeric type.
-0.31
First quartile of skewness among attributes of the numeric type.
21.23
Mean of means among attributes of the numeric type.
0.15
First quartile of standard deviation of attributes of the numeric type.
0.91
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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