Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1293313

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1293313

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: CHEMBL1293313 (TID: 103746), and it has 806 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)numeric617 unique values
0 missing
molecule_id (row identifier)nominal806 unique values
0 missing
nRCONHRnumeric4 unique values
0 missing
SM13_EA.dm.numeric186 unique values
0 missing
SM15_EA.dm.numeric182 unique values
0 missing
SM11_EA.dm.numeric191 unique values
0 missing
SM09_EA.dm.numeric192 unique values
0 missing
SM07_EA.dm.numeric193 unique values
0 missing
SdssCnumeric638 unique values
0 missing
Eig02_EA.dm.numeric159 unique values
0 missing
Eig01_EA.dm.numeric149 unique values
0 missing
SpMax_EA.dm.numeric149 unique values
0 missing
CATS2D_02_DLnumeric9 unique values
0 missing
SpMax6_Bh.i.numeric442 unique values
0 missing
P_VSA_LogP_7numeric135 unique values
0 missing
ATSC2pnumeric740 unique values
0 missing
SM02_EA.dm.numeric421 unique values
0 missing
nCconjnumeric10 unique values
0 missing
X3vnumeric747 unique values
0 missing
ATSC1pnumeric693 unique values
0 missing
SpMax6_Bh.e.numeric458 unique values
0 missing
Eta_Lnumeric733 unique values
0 missing
SpMax5_Bh.e.numeric456 unique values
0 missing
JGI6numeric28 unique values
0 missing
SpMax6_Bh.v.numeric440 unique values
0 missing
TIC2numeric712 unique values
0 missing
Chi0_EA.dm.numeric738 unique values
0 missing
IC2numeric536 unique values
0 missing
Chi1_EA.dm.numeric747 unique values
0 missing
ATS5mnumeric602 unique values
0 missing
AACnumeric417 unique values
0 missing
AECCnumeric563 unique values
0 missing
ALOGPnumeric730 unique values
0 missing
ALOGP2numeric777 unique values
0 missing
AMRnumeric782 unique values
0 missing
AMWnumeric629 unique values
0 missing
ARRnumeric152 unique values
0 missing
ATS1enumeric496 unique values
0 missing
ATS1inumeric496 unique values
0 missing
ATS1mnumeric513 unique values
0 missing
ATS1pnumeric500 unique values
0 missing
ATS1snumeric503 unique values
0 missing
ATS1vnumeric500 unique values
0 missing
ATS2enumeric524 unique values
0 missing
ATS2inumeric522 unique values
0 missing
ATS2mnumeric538 unique values
0 missing
ATS2pnumeric525 unique values
0 missing
ATS2snumeric537 unique values
0 missing
ATS2vnumeric527 unique values
0 missing
ATS3enumeric555 unique values
0 missing
ATS3inumeric542 unique values
0 missing
ATS3mnumeric578 unique values
0 missing
ATS3pnumeric552 unique values
0 missing
ATS3snumeric557 unique values
0 missing
ATS3vnumeric556 unique values
0 missing
ATS4enumeric593 unique values
0 missing
ATS4inumeric578 unique values
0 missing
ATS4mnumeric601 unique values
0 missing
ATS4pnumeric581 unique values
0 missing
ATS4snumeric595 unique values
0 missing
ATS4vnumeric582 unique values
0 missing
ATS5enumeric618 unique values
0 missing
ATS5inumeric591 unique values
0 missing
ATS5pnumeric615 unique values
0 missing
ATS5snumeric606 unique values
0 missing
ATS5vnumeric594 unique values
0 missing
ATS6enumeric623 unique values
0 missing
ATS6inumeric621 unique values
0 missing
ATS6mnumeric617 unique values
0 missing
ATS6pnumeric631 unique values
0 missing
ATS6snumeric610 unique values
0 missing

62 properties

806
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.
Third quartile of entropy among attributes.
5.36
Maximum kurtosis among attributes of the numeric type.
-0.64
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
1.49
Third quartile of kurtosis among attributes of the numeric type.
191.56
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.
5.59
Third quartile of means 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.
98.59
Percentage of numeric 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.
-1.67
Minimum skewness among attributes of the numeric type.
1.41
Percentage of nominal attributes.
0.04
Third quartile of skewness among attributes of the numeric type.
1.57
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.26
Third quartile of standard deviation of attributes of the numeric type.
64.91
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.19
First quartile of kurtosis 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.
Number of instances belonging to the least frequent class.
3.38
First quartile of means among attributes of the numeric type.
0.93
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.
11.18
Mean of means among attributes of the numeric type.
-0.64
First quartile of skewness among attributes of the numeric type.
0.43
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.26
First quartile of standard deviation of attributes of the numeric type.
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.
0.09
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.72
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.
-0.33
Mean skewness among attributes of the numeric type.
3.93
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
3.03
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.
-0.49
Second quartile (Median) of skewness among attributes of the numeric type.
0.38
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.98
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.

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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