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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1741176

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1741176

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: CHEMBL1741176 (TID: 103972), and it has 940 rows and 70 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.

72 features

pXC50 (target)numeric311 unique values
0 missing
molecule_id (row identifier)nominal940 unique values
0 missing
CATS2D_06_DLnumeric15 unique values
0 missing
HNarnumeric265 unique values
0 missing
GNarnumeric283 unique values
0 missing
X0Anumeric99 unique values
0 missing
P_VSA_e_3numeric311 unique values
0 missing
SaasCnumeric843 unique values
0 missing
P_VSA_p_2numeric687 unique values
0 missing
P_VSA_m_2numeric902 unique values
0 missing
TPSA.NO.numeric670 unique values
0 missing
MAXDPnumeric804 unique values
0 missing
AACnumeric534 unique values
0 missing
AECCnumeric715 unique values
0 missing
ALOGPnumeric795 unique values
0 missing
ALOGP2numeric898 unique values
0 missing
AMRnumeric913 unique values
0 missing
AMWnumeric795 unique values
0 missing
ARRnumeric187 unique values
0 missing
ATS1enumeric562 unique values
0 missing
ATS1inumeric576 unique values
0 missing
ATS1mnumeric550 unique values
0 missing
ATS1pnumeric541 unique values
0 missing
ATS1snumeric538 unique values
0 missing
ATS1vnumeric539 unique values
0 missing
ATS2enumeric581 unique values
0 missing
ATS2inumeric610 unique values
0 missing
ATS2mnumeric559 unique values
0 missing
ATS2pnumeric579 unique values
0 missing
ATS2snumeric619 unique values
0 missing
ATS2vnumeric557 unique values
0 missing
ATS3enumeric627 unique values
0 missing
ATS3inumeric632 unique values
0 missing
ATS3mnumeric592 unique values
0 missing
ATS3pnumeric607 unique values
0 missing
ATS3snumeric612 unique values
0 missing
ATS3vnumeric619 unique values
0 missing
ATS4enumeric650 unique values
0 missing
ATS4inumeric680 unique values
0 missing
ATS4mnumeric628 unique values
0 missing
ATS4pnumeric653 unique values
0 missing
ATS4snumeric652 unique values
0 missing
ATS4vnumeric639 unique values
0 missing
ATS5enumeric678 unique values
0 missing
ATS5inumeric681 unique values
0 missing
ATS5mnumeric666 unique values
0 missing
ATS5pnumeric686 unique values
0 missing
ATS5snumeric680 unique values
0 missing
ATS5vnumeric674 unique values
0 missing
ATS6enumeric709 unique values
0 missing
ATS6inumeric704 unique values
0 missing
ATS6mnumeric680 unique values
0 missing
ATS6pnumeric692 unique values
0 missing
ATS6snumeric705 unique values
0 missing
ATS6vnumeric691 unique values
0 missing
ATS7enumeric712 unique values
0 missing
ATS7inumeric729 unique values
0 missing
ATS7mnumeric689 unique values
0 missing
ATS7pnumeric705 unique values
0 missing
ATS7snumeric709 unique values
0 missing
ATS7vnumeric697 unique values
0 missing
ATS8enumeric722 unique values
0 missing
ATS8inumeric742 unique values
0 missing
ATS8mnumeric715 unique values
0 missing
ATS8pnumeric726 unique values
0 missing
ATS8snumeric750 unique values
0 missing
ATS8vnumeric721 unique values
0 missing
ATSC1enumeric298 unique values
0 missing
ATSC1inumeric517 unique values
0 missing
ATSC1mnumeric887 unique values
0 missing
ATSC1pnumeric815 unique values
0 missing
ATSC1snumeric904 unique values
0 missing

62 properties

940
Number of instances (rows) of the dataset.
72
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.
71
Number of numeric attributes.
1
Number of nominal 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.
Second quartile (Median) of entropy among attributes.
0.08
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
1.15
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.
-0.08
Mean skewness among attributes of the numeric type.
4.17
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
3.2
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.
-0.12
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-0.25
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.4
Second quartile (Median) of standard deviation of attributes of the numeric type.
24.98
Maximum kurtosis among attributes of the numeric type.
0.12
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
159.37
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.
5.31
Third quartile of kurtosis 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.
98.61
Percentage of numeric attributes.
5.23
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.37
Minimum skewness among attributes of the numeric type.
1.39
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
4.06
Maximum skewness among attributes of the numeric type.
0.02
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.34
Third quartile of skewness among attributes of the numeric type.
42.21
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.79
First quartile of kurtosis among attributes of the numeric type.
0.61
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
3.71
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
3.37
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.
11.04
Mean of means among attributes of the numeric type.
-0.42
First quartile of skewness among attributes of the numeric type.
0.65
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.27
First quartile of standard deviation of attributes of the numeric type.

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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