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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL288

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL288

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: CHEMBL288 (TID: 11359), and it has 537 rows and 102 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent FCFP 1024-bit Molecular Fingerprints which were generated from SMILES strings. Feature selection was applied to this dataset. The fingerprints were obtained using the Pipeline Pilot program, Dassault Systèmes BIOVIA. Generating Fingerprints do not usually require missing value imputation as all bits are generated.

104 features

pXC50 (target)numeric355 unique values
0 missing
molecule_id (row identifier)nominal537 unique values
0 missing
FCFP4_1024b692numeric2 unique values
0 missing
FCFP4_1024b792numeric2 unique values
0 missing
FCFP4_1024b490numeric2 unique values
0 missing
FCFP4_1024b179numeric2 unique values
0 missing
FCFP4_1024b947numeric2 unique values
0 missing
FCFP4_1024b940numeric2 unique values
0 missing
FCFP4_1024b858numeric2 unique values
0 missing
FCFP4_1024b185numeric2 unique values
0 missing
FCFP4_1024b495numeric2 unique values
0 missing
FCFP4_1024b279numeric2 unique values
0 missing
FCFP4_1024b908numeric2 unique values
0 missing
FCFP4_1024b409numeric2 unique values
0 missing
FCFP4_1024b61numeric2 unique values
0 missing
FCFP4_1024b635numeric2 unique values
0 missing
FCFP4_1024b685numeric2 unique values
0 missing
FCFP4_1024b72numeric2 unique values
0 missing
FCFP4_1024b881numeric2 unique values
0 missing
FCFP4_1024b471numeric2 unique values
0 missing
FCFP4_1024b933numeric2 unique values
0 missing
FCFP4_1024b133numeric2 unique values
0 missing
FCFP4_1024b748numeric2 unique values
0 missing
FCFP4_1024b75numeric2 unique values
0 missing
FCFP4_1024b204numeric2 unique values
0 missing
FCFP4_1024b521numeric2 unique values
0 missing
FCFP4_1024b194numeric2 unique values
0 missing
FCFP4_1024b378numeric2 unique values
0 missing
FCFP4_1024b158numeric2 unique values
0 missing
FCFP4_1024b188numeric2 unique values
0 missing
FCFP4_1024b49numeric2 unique values
0 missing
FCFP4_1024b68numeric2 unique values
0 missing
FCFP4_1024b932numeric2 unique values
0 missing
FCFP4_1024b903numeric2 unique values
0 missing
FCFP4_1024b902numeric2 unique values
0 missing
FCFP4_1024b790numeric2 unique values
0 missing
FCFP4_1024b730numeric2 unique values
0 missing
FCFP4_1024b529numeric2 unique values
0 missing
FCFP4_1024b71numeric2 unique values
0 missing
FCFP4_1024b899numeric2 unique values
0 missing
FCFP4_1024b691numeric2 unique values
0 missing
FCFP4_1024b69numeric2 unique values
0 missing
FCFP4_1024b787numeric2 unique values
0 missing
FCFP4_1024b971numeric2 unique values
0 missing
FCFP4_1024b606numeric2 unique values
0 missing
FCFP4_1024b568numeric2 unique values
0 missing
FCFP4_1024b453numeric2 unique values
0 missing
FCFP4_1024b954numeric2 unique values
0 missing
FCFP4_1024b250numeric2 unique values
0 missing
FCFP4_1024b799numeric2 unique values
0 missing
FCFP4_1024b290numeric2 unique values
0 missing
FCFP4_1024b610numeric2 unique values
0 missing
FCFP4_1024b429numeric2 unique values
0 missing
FCFP4_1024b981numeric2 unique values
0 missing
FCFP4_1024b1003numeric2 unique values
0 missing
FCFP4_1024b332numeric2 unique values
0 missing
FCFP4_1024b334numeric2 unique values
0 missing
FCFP4_1024b497numeric2 unique values
0 missing
FCFP4_1024b983numeric2 unique values
0 missing
FCFP4_1024b408numeric2 unique values
0 missing
FCFP4_1024b291numeric2 unique values
0 missing
FCFP4_1024b588numeric2 unique values
0 missing
FCFP4_1024b798numeric2 unique values
0 missing
FCFP4_1024b325numeric2 unique values
0 missing
FCFP4_1024b296numeric2 unique values
0 missing
FCFP4_1024b604numeric2 unique values
0 missing
FCFP4_1024b383numeric2 unique values
0 missing
FCFP4_1024b87numeric2 unique values
0 missing
FCFP4_1024b134numeric2 unique values
0 missing
FCFP4_1024b630numeric2 unique values
0 missing
FCFP4_1024b165numeric2 unique values
0 missing
FCFP4_1024b312numeric2 unique values
0 missing
FCFP4_1024b370numeric2 unique values
0 missing
FCFP4_1024b815numeric2 unique values
0 missing
FCFP4_1024b297numeric2 unique values
0 missing
FCFP4_1024b176numeric2 unique values
0 missing
FCFP4_1024b330numeric2 unique values
0 missing
FCFP4_1024b54numeric2 unique values
0 missing
FCFP4_1024b639numeric2 unique values
0 missing
FCFP4_1024b786numeric2 unique values
0 missing
FCFP4_1024b143numeric2 unique values
0 missing
FCFP4_1024b553numeric2 unique values
0 missing
FCFP4_1024b413numeric2 unique values
0 missing
FCFP4_1024b212numeric2 unique values
0 missing
FCFP4_1024b311numeric2 unique values
0 missing
FCFP4_1024b800numeric2 unique values
0 missing
FCFP4_1024b222numeric2 unique values
0 missing
FCFP4_1024b817numeric2 unique values
0 missing
FCFP4_1024b652numeric2 unique values
0 missing
FCFP4_1024b371numeric2 unique values
0 missing
FCFP4_1024b925numeric2 unique values
0 missing
FCFP4_1024b372numeric2 unique values
0 missing
FCFP4_1024b765numeric2 unique values
0 missing
FCFP4_1024b102numeric2 unique values
0 missing
FCFP4_1024b876numeric2 unique values
0 missing
FCFP4_1024b59numeric2 unique values
0 missing
FCFP4_1024b1006numeric2 unique values
0 missing
FCFP4_1024b846numeric2 unique values
0 missing
FCFP4_1024b1016numeric2 unique values
0 missing
FCFP4_1024b350numeric2 unique values
0 missing
FCFP4_1024b741numeric2 unique values
0 missing
FCFP4_1024b929numeric2 unique values
0 missing
FCFP4_1024b598numeric2 unique values
0 missing
FCFP4_1024b617numeric2 unique values
0 missing

62 properties

537
Number of instances (rows) of the dataset.
104
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.
103
Number of numeric attributes.
1
Number of nominal attributes.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
0.05
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
10.52
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.
0.19
Mean of means among attributes of the numeric type.
2
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.23
First quartile of standard deviation of attributes of the numeric type.
-0.01
Average class difference between consecutive instances.
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.
Entropy of the target attribute values.
Average number of distinct values among the attributes of the nominal type.
6.36
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.19
Number of attributes divided by the number of instances.
3.08
Mean skewness among attributes of the numeric type.
0.09
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.
0.3
Mean standard deviation of 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.
Minimal entropy among attributes.
2.89
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-2
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.29
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
55.21
Maximum kurtosis among attributes of the numeric type.
0.02
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
6.58
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.
13.71
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.
99.04
Percentage of numeric attributes.
0.15
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-1.02
Minimum skewness among attributes of the numeric type.
0.96
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
7.55
Maximum skewness among attributes of the numeric type.
0.13
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
3.96
Third quartile of skewness among attributes of the numeric type.
1.64
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
2
First quartile of kurtosis among attributes of the numeric type.
0.35
Third quartile of standard deviation of attributes of the numeric type.

12 tasks

1 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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