Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2543

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2543

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: CHEMBL2543 (TID: 11629), and it has 688 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)numeric77 unique values
0 missing
molecule_id (row identifier)nominal688 unique values
0 missing
Chi0_EA.dm.numeric591 unique values
0 missing
ATSC3mnumeric665 unique values
0 missing
SsssNnumeric148 unique values
0 missing
Eta_epsinumeric534 unique values
0 missing
ATSC8mnumeric674 unique values
0 missing
PCRnumeric282 unique values
0 missing
ATS5inumeric528 unique values
0 missing
Eig03_AEA.dm.numeric472 unique values
0 missing
ATS3mnumeric478 unique values
0 missing
P_VSA_i_3numeric387 unique values
0 missing
CATS2D_02_ALnumeric15 unique values
0 missing
Eig11_AEA.dm.numeric436 unique values
0 missing
ATS8mnumeric550 unique values
0 missing
IACnumeric589 unique values
0 missing
TIC0numeric589 unique values
0 missing
CENTnumeric542 unique values
0 missing
S1Knumeric544 unique values
0 missing
Eig12_AEA.dm.numeric452 unique values
0 missing
ATS5enumeric520 unique values
0 missing
IDMnumeric525 unique values
0 missing
ATSC5mnumeric676 unique values
0 missing
H.047numeric29 unique values
0 missing
Chi1_EA.bo.numeric607 unique values
0 missing
ATS1enumeric458 unique values
0 missing
SAtotnumeric649 unique values
0 missing
ATSC2mnumeric639 unique values
0 missing
SpMax6_Bh.i.numeric395 unique values
0 missing
SpAD_EA.ed.numeric624 unique values
0 missing
Eig07_AEA.dm.numeric489 unique values
0 missing
TIC5numeric518 unique values
0 missing
PHInumeric589 unique values
0 missing
Senumeric602 unique values
0 missing
X0vnumeric623 unique values
0 missing
Eta_betaSnumeric86 unique values
0 missing
Psi_i_0numeric635 unique values
0 missing
ATSC4inumeric546 unique values
0 missing
ATSC5vnumeric662 unique values
0 missing
Eig07_EAnumeric435 unique values
0 missing
SM15_AEA.bo.numeric435 unique values
0 missing
SRW06numeric347 unique values
0 missing
ATS7pnumeric558 unique values
0 missing
ATS8enumeric570 unique values
0 missing
SRW07numeric30 unique values
0 missing
SRW09numeric91 unique values
0 missing
X0numeric308 unique values
0 missing
ATS3enumeric488 unique values
0 missing
ATS3pnumeric473 unique values
0 missing
SRW04numeric121 unique values
0 missing
Eig13_AEA.dm.numeric477 unique values
0 missing
HDcpxnumeric221 unique values
0 missing
SpMaxA_AEA.ri.numeric143 unique values
0 missing
ATS2enumeric482 unique values
0 missing
CATS2D_04_DLnumeric14 unique values
0 missing
ON0Vnumeric496 unique values
0 missing
CATS2D_08_DPnumeric4 unique values
0 missing
Eig10_AEA.dm.numeric456 unique values
0 missing
ATS3vnumeric476 unique values
0 missing
BIDnumeric120 unique values
0 missing
TIC4numeric518 unique values
0 missing
ATS2inumeric483 unique values
0 missing
Chi0_EA.bo.numeric584 unique values
0 missing
Psi_i_1numeric642 unique values
0 missing
SpMax6_Bh.p.numeric394 unique values
0 missing
RDSQnumeric625 unique values
0 missing
Eig10_EA.ed.numeric502 unique values
0 missing
SM05_AEA.ri.numeric502 unique values
0 missing
ATSC4pnumeric661 unique values
0 missing
TIC3numeric547 unique values
0 missing
Eig08_EA.ed.numeric531 unique values
0 missing

62 properties

688
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.
0.46
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.1
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
4.96
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.
0.1
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.
21.51
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.
1.53
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.3
Minimum kurtosis among attributes of the numeric type.
0.14
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
14.78
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
1.44
Third quartile of kurtosis among attributes of the numeric type.
1294.12
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.
18.39
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.
1.41
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.
0.03
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.59
Third quartile of skewness among attributes of the numeric type.
3.53
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.16
First quartile of kurtosis among attributes of the numeric type.
5.26
Third quartile of standard deviation of attributes of the numeric type.
830.79
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
3.13
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.
1.42
Mean kurtosis among attributes of the numeric type.
-0.5
First quartile of skewness among attributes of the numeric type.
52.64
Mean of means among attributes of the numeric type.
0.38
First quartile of standard deviation of attributes of the numeric type.
0.53
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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