Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5819

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5819

deactivated ARFF Publicly available Visibility: public Uploaded 16-07-2016 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: CHEMBL5819 (TID: 101349), and it has 652 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)numeric38 unique values
0 missing
molecule_id (row identifier)nominal652 unique values
0 missing
Chi0_EA.dm.numeric564 unique values
0 missing
Chi1_EA.dm.numeric574 unique values
0 missing
ATSC3mnumeric632 unique values
0 missing
ATS2mnumeric450 unique values
0 missing
ATS7mnumeric528 unique values
0 missing
P_VSA_i_3numeric377 unique values
0 missing
ATSC2mnumeric607 unique values
0 missing
SRW04numeric120 unique values
0 missing
ATS1mnumeric434 unique values
0 missing
Eig12_AEA.dm.numeric435 unique values
0 missing
MWnumeric579 unique values
0 missing
ATS5inumeric507 unique values
0 missing
SpMin6_Bh.p.numeric383 unique values
0 missing
Eig10_AEA.dm.numeric437 unique values
0 missing
X3vnumeric606 unique values
0 missing
ATS3mnumeric462 unique values
0 missing
Chi1_EA.bo.numeric584 unique values
0 missing
ATS2inumeric467 unique values
0 missing
Eig09_AEA.dm.numeric461 unique values
0 missing
ZM2Madnumeric633 unique values
0 missing
ATSC4pnumeric628 unique values
0 missing
ATS3enumeric464 unique values
0 missing
Eig11_AEA.dm.numeric418 unique values
0 missing
IACnumeric560 unique values
0 missing
TIC0numeric560 unique values
0 missing
ATS3inumeric474 unique values
0 missing
SpMax2_Bh.p.numeric264 unique values
0 missing
X2vnumeric619 unique values
0 missing
Eig08_AEA.dm.numeric451 unique values
0 missing
ATS8pnumeric546 unique values
0 missing
ATS8mnumeric526 unique values
0 missing
XMODnumeric621 unique values
0 missing
RDSQnumeric602 unique values
0 missing
X2solnumeric565 unique values
0 missing
SpMax2_Bh.e.numeric243 unique values
0 missing
Eig06_AEA.bo.numeric435 unique values
0 missing
SpMax2_Bh.m.numeric299 unique values
0 missing
Eig15_AEA.dm.numeric490 unique values
0 missing
ATSC8mnumeric640 unique values
0 missing
SpMax8_Bh.m.numeric392 unique values
0 missing
X1MulPernumeric598 unique values
0 missing
Eig06_EA.ed.numeric548 unique values
0 missing
SM15_AEA.dm.numeric548 unique values
0 missing
ATS2enumeric465 unique values
0 missing
Eta_epsinumeric511 unique values
0 missing
SpMax6_Bh.m.numeric430 unique values
0 missing
ATS3snumeric480 unique values
0 missing
ZM1Madnumeric619 unique values
0 missing
SM05_AEA.bo.numeric423 unique values
0 missing
ATSC5pnumeric627 unique values
0 missing
SM04_AEA.bo.numeric426 unique values
0 missing
Eig08_EA.ed.numeric513 unique values
0 missing
SM03_AEA.ri.numeric513 unique values
0 missing
ATS5enumeric504 unique values
0 missing
SpMax8_Bh.v.numeric376 unique values
0 missing
Eta_Lnumeric594 unique values
0 missing
X3solnumeric576 unique values
0 missing
Eta_Cnumeric638 unique values
0 missing
Eig08_EAnumeric430 unique values
0 missing
SM02_AEA.dm.numeric430 unique values
0 missing
SpMax2_Bh.v.numeric263 unique values
0 missing
Eig11_AEA.ri.numeric451 unique values
0 missing
SpMax8_Bh.p.numeric367 unique values
0 missing
S1Knumeric519 unique values
0 missing
SM06_AEA.bo.numeric448 unique values
0 missing
Eig03_AEA.bo.numeric405 unique values
0 missing
X5vnumeric563 unique values
0 missing
SRW06numeric344 unique values
0 missing
ON1Vnumeric552 unique values
0 missing

62 properties

652
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.
0.65
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.11
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
4.82
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.
-0.19
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.
7
Mean standard deviation of attributes of the numeric type.
-0.31
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.
0.63
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.72
Minimum kurtosis among attributes of the numeric type.
0.01
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
10.91
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
1.89
Third quartile of kurtosis among attributes of the numeric type.
383.44
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.
11.53
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.23
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.
0.08
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.48
Third quartile of skewness among attributes of the numeric type.
3.02
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.13
First quartile of kurtosis among attributes of the numeric type.
3.08
Third quartile of standard deviation of attributes of the numeric type.
81.45
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
3.4
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.
1.79
Mean kurtosis among attributes of the numeric type.
-0.69
First quartile of skewness among attributes of the numeric type.
27.07
Mean of means among attributes of the numeric type.
0.28
First quartile of standard deviation of attributes of the numeric type.
0.65
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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