Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4068

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4068

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: CHEMBL4068 (TID: 10074), and it has 377 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)numeric259 unique values
0 missing
molecule_id (row identifier)nominal377 unique values
0 missing
SpMax8_Bh.s.numeric211 unique values
0 missing
ATS3snumeric310 unique values
0 missing
Eta_alpha_Anumeric68 unique values
0 missing
DELSnumeric357 unique values
0 missing
NdssCnumeric10 unique values
0 missing
SpMax7_Bh.s.numeric229 unique values
0 missing
ATS2snumeric284 unique values
0 missing
ATSC6inumeric333 unique values
0 missing
CATS2D_03_DAnumeric9 unique values
0 missing
Psi_e_0numeric343 unique values
0 missing
Eta_Fnumeric355 unique values
0 missing
X0numeric193 unique values
0 missing
ATSC3enumeric295 unique values
0 missing
IDDEnumeric185 unique values
0 missing
SM06_AEA.bo.numeric225 unique values
0 missing
MWnumeric281 unique values
0 missing
Eig15_EA.ed.numeric196 unique values
0 missing
SM10_AEA.ri.numeric196 unique values
0 missing
Eig10_EA.bo.numeric200 unique values
0 missing
Chi1_EA.bo.numeric279 unique values
0 missing
Eig06_EA.ed.numeric247 unique values
0 missing
SM15_AEA.dm.numeric247 unique values
0 missing
MAXDNnumeric317 unique values
0 missing
nDBnumeric10 unique values
0 missing
Eig07_AEA.ri.numeric267 unique values
0 missing
ATS6vnumeric319 unique values
0 missing
ATSC5snumeric358 unique values
0 missing
Psi_i_snumeric274 unique values
0 missing
SPInumeric271 unique values
0 missing
X2numeric268 unique values
0 missing
Eig07_EA.ri.numeric256 unique values
0 missing
SpMax6_Bh.e.numeric236 unique values
0 missing
Dznumeric166 unique values
0 missing
RDSQnumeric272 unique values
0 missing
SpAD_AEA.ed.numeric274 unique values
0 missing
SpAD_EAnumeric273 unique values
0 missing
SpAD_EA.ri.numeric343 unique values
0 missing
TPSA.NO.numeric140 unique values
0 missing
SpMax5_Bh.s.numeric134 unique values
0 missing
ATS1snumeric269 unique values
0 missing
IDDMnumeric172 unique values
0 missing
SM02_EA.ri.numeric247 unique values
0 missing
SpMin5_Bh.m.numeric207 unique values
0 missing
Eig12_AEA.ri.numeric238 unique values
0 missing
Eig12_EA.ri.numeric226 unique values
0 missing
SpAD_AEA.bo.numeric285 unique values
0 missing
SpAD_AEA.ri.numeric344 unique values
0 missing
CIDnumeric191 unique values
0 missing
SMTInumeric272 unique values
0 missing
VvdwMGnumeric280 unique values
0 missing
VvdwZAZnumeric283 unique values
0 missing
Vxnumeric280 unique values
0 missing
SM04_EA.ri.numeric274 unique values
0 missing
Psi_e_1numeric338 unique values
0 missing
UNIPnumeric161 unique values
0 missing
Eig14_AEA.ed.numeric214 unique values
0 missing
ATSC5inumeric328 unique values
0 missing
SpAD_EA.ed.numeric274 unique values
0 missing
GGI9numeric183 unique values
0 missing
IDMnumeric251 unique values
0 missing
Eig14_EA.ed.numeric222 unique values
0 missing
SM09_AEA.ri.numeric222 unique values
0 missing
ECCnumeric213 unique values
0 missing
MWC02numeric82 unique values
0 missing
ZM1numeric82 unique values
0 missing
Eta_epsinumeric275 unique values
0 missing
SpMaxA_EA.bo.numeric100 unique values
0 missing

62 properties

377
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.
0.51
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.
0.55
Mean skewness among attributes of the numeric type.
5.93
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
236.55
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.
0.61
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.72
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
1.69
Second quartile (Median) of standard deviation of attributes of the numeric type.
41
Maximum kurtosis among attributes of the numeric type.
0.13
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
17635.42
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.
1.75
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.
55.32
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-1.08
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.
4.32
Maximum skewness among attributes of the numeric type.
0.02
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.92
Third quartile of skewness among attributes of the numeric type.
14736.32
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.75
First quartile of kurtosis among attributes of the numeric type.
15.01
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.
2.89
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
1.59
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.
319.22
Mean of means among attributes of the numeric type.
-0.03
First quartile of skewness among attributes of the numeric type.
-0.07
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.43
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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