Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4026

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4026

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 by Noureddin Sadawi
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL4026 (TID: 11472), and it has 720 rows and 51 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.

53 features

pXC50 (target)numeric391 unique values
0 missing
molecule_id (row identifier)nominal720 unique values
0 missing
FCFP4_1024b868numeric2 unique values
0 missing
FCFP4_1024b531numeric2 unique values
0 missing
FCFP4_1024b799numeric2 unique values
0 missing
FCFP4_1024b973numeric2 unique values
0 missing
FCFP4_1024b714numeric2 unique values
0 missing
FCFP4_1024b396numeric2 unique values
0 missing
FCFP4_1024b524numeric2 unique values
0 missing
FCFP4_1024b492numeric2 unique values
0 missing
FCFP4_1024b387numeric2 unique values
0 missing
FCFP4_1024b589numeric2 unique values
0 missing
FCFP4_1024b322numeric2 unique values
0 missing
FCFP4_1024b260numeric2 unique values
0 missing
FCFP4_1024b728numeric2 unique values
0 missing
FCFP4_1024b603numeric2 unique values
0 missing
FCFP4_1024b161numeric2 unique values
0 missing
FCFP4_1024b862numeric2 unique values
0 missing
FCFP4_1024b986numeric2 unique values
0 missing
FCFP4_1024b271numeric2 unique values
0 missing
FCFP4_1024b124numeric2 unique values
0 missing
FCFP4_1024b640numeric2 unique values
0 missing
FCFP4_1024b152numeric2 unique values
0 missing
FCFP4_1024b653numeric2 unique values
0 missing
FCFP4_1024b695numeric2 unique values
0 missing
FCFP4_1024b948numeric2 unique values
0 missing
FCFP4_1024b574numeric2 unique values
0 missing
FCFP4_1024b108numeric2 unique values
0 missing
FCFP4_1024b902numeric2 unique values
0 missing
FCFP4_1024b557numeric2 unique values
0 missing
FCFP4_1024b943numeric2 unique values
0 missing
FCFP4_1024b847numeric2 unique values
0 missing
FCFP4_1024b429numeric2 unique values
0 missing
FCFP4_1024b872numeric2 unique values
0 missing
FCFP4_1024b908numeric2 unique values
0 missing
FCFP4_1024b541numeric2 unique values
0 missing
FCFP4_1024b521numeric2 unique values
0 missing
FCFP4_1024b421numeric2 unique values
0 missing
FCFP4_1024b61numeric2 unique values
0 missing
FCFP4_1024b376numeric2 unique values
0 missing
FCFP4_1024b18numeric2 unique values
0 missing
FCFP4_1024b32numeric2 unique values
0 missing
FCFP4_1024b65numeric2 unique values
0 missing
FCFP4_1024b514numeric2 unique values
0 missing
FCFP4_1024b455numeric2 unique values
0 missing
FCFP4_1024b826numeric2 unique values
0 missing
FCFP4_1024b107numeric2 unique values
0 missing
FCFP4_1024b542numeric2 unique values
0 missing
FCFP4_1024b938numeric2 unique values
0 missing
FCFP4_1024b332numeric2 unique values
0 missing
FCFP4_1024b632numeric2 unique values
0 missing
FCFP4_1024b971numeric2 unique values
0 missing
FCFP4_1024b817numeric2 unique values
0 missing

62 properties

720
Number of instances (rows) of the dataset.
53
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.
52
Number of numeric attributes.
1
Number of nominal attributes.
5.76
Maximum skewness among attributes of the numeric type.
0.16
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.86
Third quartile of skewness among attributes of the numeric type.
0.85
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.29
First quartile of kurtosis among attributes of the numeric type.
0.47
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.
0.16
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
2.46
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.
0.34
Mean of means among attributes of the numeric type.
0.82
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.37
First quartile of standard deviation of attributes of the numeric type.
0.3
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.
-0.04
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.07
Number of attributes divided by the number of instances.
1.58
Mean skewness among attributes of the numeric type.
0.22
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.
Percentage of instances belonging to the most frequent class.
0.41
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.
1.37
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-2.01
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.41
Second quartile (Median) of standard deviation of attributes of the numeric type.
31.25
Maximum kurtosis among attributes of the numeric type.
0.03
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
5.07
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.
1.47
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.
98.11
Percentage of numeric attributes.
0.33
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-0.4
Minimum skewness among attributes of the numeric type.
1.89
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.

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
Define a new task