Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1821

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1821

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 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: CHEMBL1821 (TID: 214), and it has 770 rows and 69 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.

71 features

pXC50 (target)numeric512 unique values
0 missing
molecule_id (row identifier)nominal770 unique values
0 missing
JGI7numeric25 unique values
0 missing
Eig08_AEA.dm.numeric442 unique values
0 missing
Eig08_EA.ed.numeric451 unique values
0 missing
SM03_AEA.ri.numeric451 unique values
0 missing
ZM1Kupnumeric568 unique values
0 missing
Eig07_AEA.dm.numeric461 unique values
0 missing
ZM2Kupnumeric623 unique values
0 missing
Eig10_EA.ed.numeric396 unique values
0 missing
SM05_AEA.ri.numeric396 unique values
0 missing
Eig05_AEA.ri.numeric458 unique values
0 missing
Psi_i_snumeric427 unique values
0 missing
JGI8numeric23 unique values
0 missing
Eig05_EAnumeric406 unique values
0 missing
SM13_AEA.bo.numeric406 unique values
0 missing
Eig06_AEA.dm.numeric454 unique values
0 missing
SM13_EA.ri.numeric515 unique values
0 missing
SM14_EA.ri.numeric527 unique values
0 missing
SM15_EA.ri.numeric518 unique values
0 missing
SM12_EA.ri.numeric526 unique values
0 missing
Psi_i_tnumeric32 unique values
0 missing
SM11_EA.ri.numeric519 unique values
0 missing
GATS8enumeric487 unique values
0 missing
CATS2D_05_LLnumeric40 unique values
0 missing
MPC10numeric248 unique values
0 missing
S0Knumeric268 unique values
0 missing
piPC09numeric521 unique values
0 missing
Wapnumeric511 unique values
0 missing
SpMin5_Bh.p.numeric346 unique values
0 missing
Eig06_AEA.bo.numeric424 unique values
0 missing
SpDiam_EA.ri.numeric308 unique values
0 missing
Eig10_AEA.ed.numeric368 unique values
0 missing
P_VSA_m_2numeric579 unique values
0 missing
GGI7numeric299 unique values
0 missing
ZM1MulPernumeric649 unique values
0 missing
ZM1Pernumeric646 unique values
0 missing
ATSC2snumeric667 unique values
0 missing
SpDiam_AEA.ed.numeric372 unique values
0 missing
Eig11_EA.dm.numeric12 unique values
0 missing
Eig04_EA.ri.numeric454 unique values
0 missing
Eig04_EA.bo.numeric427 unique values
0 missing
SM14_AEA.ri.numeric427 unique values
0 missing
nCsp2numeric28 unique values
0 missing
Eig05_AEA.bo.numeric434 unique values
0 missing
SpMax4_Bh.m.numeric412 unique values
0 missing
TIC3numeric586 unique values
0 missing
SM08_EA.ri.numeric519 unique values
0 missing
ZM1Vnumeric216 unique values
0 missing
Eig08_AEA.ed.numeric401 unique values
0 missing
Eig06_AEA.ri.numeric438 unique values
0 missing
Eig06_EAnumeric391 unique values
0 missing
Eig06_EA.ri.numeric441 unique values
0 missing
SM14_AEA.bo.numeric391 unique values
0 missing
piIDnumeric519 unique values
0 missing
Eig07_AEA.ri.numeric428 unique values
0 missing
SM12_EAnumeric477 unique values
0 missing
SM13_EAnumeric453 unique values
0 missing
SM11_EAnumeric465 unique values
0 missing
SM06_EA.ed.numeric468 unique values
0 missing
SM07_EA.ri.numeric482 unique values
0 missing
SpMax5_Bh.s.numeric435 unique values
0 missing
SM05_EA.ed.numeric450 unique values
0 missing
SpMax3_Bh.e.numeric350 unique values
0 missing
ATS2snumeric509 unique values
0 missing
SM10_AEA.ed.numeric464 unique values
0 missing
SM07_EA.ed.numeric443 unique values
0 missing
SpDiam_AEA.bo.numeric344 unique values
0 missing
Eig07_EA.ed.numeric436 unique values
0 missing
SM02_AEA.ri.numeric436 unique values
0 missing
nCrsnumeric16 unique values
0 missing

62 properties

770
Number of instances (rows) of the dataset.
71
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.
70
Number of numeric attributes.
1
Number of nominal attributes.
1068.33
Mean standard deviation of 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.
Minimal entropy among attributes.
-0.05
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-0.2
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.83
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.03
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
171.14
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
4.67
Third quartile of kurtosis among attributes of the numeric type.
30260.2
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.59
Percentage of numeric attributes.
15.23
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-4.67
Minimum skewness among attributes of the numeric type.
1.41
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
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.
11.3
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.77
First quartile of kurtosis among attributes of the numeric type.
2.1
Third quartile of standard deviation of attributes of the numeric type.
73722.73
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
2.04
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
6.91
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.
472.02
Mean of means among attributes of the numeric type.
-1.2
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.56
First quartile of standard deviation of attributes of the numeric type.
-0.11
Average class difference between consecutive instances.
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.
Entropy of the target attribute values.
Average number of distinct values among the attributes of the nominal type.
1.57
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.09
Number of attributes divided by the number of instances.
0.12
Mean skewness among attributes of the numeric type.
4.32
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.

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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