Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4093

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4093

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 by Noureddin Sadawi
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL4093 (TID: 20113), and it has 728 rows and 66 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.

68 features

pXC50 (target)numeric391 unique values
0 missing
molecule_id (row identifier)nominal728 unique values
0 missing
P_VSA_i_4numeric134 unique values
0 missing
SpMAD_EA.dm.numeric318 unique values
0 missing
X2Anumeric58 unique values
0 missing
SpMaxA_EA.dm.numeric113 unique values
0 missing
GATS4inumeric343 unique values
0 missing
ATSC8snumeric712 unique values
0 missing
nFnumeric12 unique values
0 missing
NsFnumeric12 unique values
0 missing
P_VSA_e_6numeric12 unique values
0 missing
SpMax1_Bh.s.numeric75 unique values
0 missing
SsFnumeric450 unique values
0 missing
ATSC2snumeric701 unique values
0 missing
ATSC8enumeric581 unique values
0 missing
ZM2Pernumeric694 unique values
0 missing
C.022numeric3 unique values
0 missing
nCspnumeric5 unique values
0 missing
nR.C.numeric3 unique values
0 missing
NtsCnumeric5 unique values
0 missing
StsCnumeric58 unique values
0 missing
nHetnumeric17 unique values
0 missing
ATSC3snumeric711 unique values
0 missing
ZM2Kupnumeric626 unique values
0 missing
P_VSA_MR_5numeric364 unique values
0 missing
ATSC6snumeric717 unique values
0 missing
MATS1inumeric202 unique values
0 missing
GATS6vnumeric315 unique values
0 missing
P_VSA_s_5numeric18 unique values
0 missing
Eig01_EA.dm.numeric50 unique values
0 missing
SpMax_EA.dm.numeric50 unique values
0 missing
CATS2D_08_DAnumeric5 unique values
0 missing
IC1numeric452 unique values
0 missing
ATS2snumeric491 unique values
0 missing
AACnumeric368 unique values
0 missing
IC0numeric368 unique values
0 missing
GMTIVnumeric694 unique values
0 missing
nTBnumeric4 unique values
0 missing
SM08_EA.dm.numeric162 unique values
0 missing
SM10_EA.dm.numeric147 unique values
0 missing
SM12_EA.dm.numeric134 unique values
0 missing
SM14_EA.dm.numeric121 unique values
0 missing
SpMax1_Bh.v.numeric183 unique values
0 missing
GGI6numeric360 unique values
0 missing
SpMin2_Bh.p.numeric141 unique values
0 missing
IACnumeric517 unique values
0 missing
TIC0numeric517 unique values
0 missing
S3Knumeric558 unique values
0 missing
Eig04_AEA.dm.numeric393 unique values
0 missing
SM06_EA.dm.numeric184 unique values
0 missing
Eig03_EAnumeric314 unique values
0 missing
SM11_AEA.bo.numeric314 unique values
0 missing
SpMax1_Bh.i.numeric183 unique values
0 missing
ATSC6inumeric604 unique values
0 missing
Psi_i_snumeric449 unique values
0 missing
Eig01_EA.ed.numeric185 unique values
0 missing
SM10_AEA.dm.numeric185 unique values
0 missing
SpMax_EA.ed.numeric185 unique values
0 missing
ZM2Vnumeric295 unique values
0 missing
ZM2MulPernumeric684 unique values
0 missing
SM04_EA.dm.numeric225 unique values
0 missing
Eig01_EAnumeric156 unique values
0 missing
SM09_AEA.bo.numeric156 unique values
0 missing
SpDiam_EAnumeric156 unique values
0 missing
SpMax_EAnumeric156 unique values
0 missing
MAXDNnumeric562 unique values
0 missing
ATSC1snumeric641 unique values
0 missing
MATS4inumeric339 unique values
0 missing

62 properties

728
Number of instances (rows) of the dataset.
68
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.
67
Number of numeric attributes.
1
Number of nominal attributes.
0.43
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.09
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
4.59
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.
0.43
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.
373.56
Mean standard deviation of attributes of the numeric type.
0.28
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.
1.14
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.9
Minimum kurtosis among attributes of the numeric type.
-0.03
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
20.29
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
2.09
Third quartile of kurtosis among attributes of the numeric type.
52101.79
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.53
Percentage of numeric attributes.
32.32
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.2
Minimum skewness among attributes of the numeric type.
1.47
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.
0.82
Third quartile of skewness among attributes of the numeric type.
4.19
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.24
First quartile of kurtosis among attributes of the numeric type.
15.78
Third quartile of standard deviation of attributes of the numeric type.
23933.86
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
1.66
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.
2.54
Mean kurtosis among attributes of the numeric type.
-0.58
First quartile of skewness among attributes of the numeric type.
832.21
Mean of means among attributes of the numeric type.
0.25
First quartile of standard deviation of attributes of the numeric type.
0.07
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
Define a new task