Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3490

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3490

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: CHEMBL3490 (TID: 100610), and it has 273 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)numeric43 unique values
0 missing
molecule_id (row identifier)nominal273 unique values
0 missing
FCFP4_1024b504numeric2 unique values
0 missing
FCFP4_1024b69numeric2 unique values
0 missing
FCFP4_1024b731numeric2 unique values
0 missing
FCFP4_1024b298numeric2 unique values
0 missing
FCFP4_1024b152numeric2 unique values
0 missing
FCFP4_1024b4numeric2 unique values
0 missing
FCFP4_1024b542numeric2 unique values
0 missing
FCFP4_1024b429numeric2 unique values
0 missing
FCFP4_1024b183numeric2 unique values
0 missing
FCFP4_1024b446numeric2 unique values
0 missing
FCFP4_1024b235numeric2 unique values
0 missing
FCFP4_1024b787numeric2 unique values
0 missing
FCFP4_1024b799numeric2 unique values
0 missing
FCFP4_1024b714numeric2 unique values
0 missing
FCFP4_1024b695numeric2 unique values
0 missing
FCFP4_1024b106numeric2 unique values
0 missing
FCFP4_1024b603numeric2 unique values
0 missing
FCFP4_1024b164numeric2 unique values
0 missing
FCFP4_1024b553numeric2 unique values
0 missing
FCFP4_1024b137numeric2 unique values
0 missing
FCFP4_1024b925numeric2 unique values
0 missing
FCFP4_1024b105numeric2 unique values
0 missing
FCFP4_1024b143numeric2 unique values
0 missing
FCFP4_1024b752numeric2 unique values
0 missing
FCFP4_1024b762numeric2 unique values
0 missing
FCFP4_1024b588numeric2 unique values
0 missing
FCFP4_1024b301numeric2 unique values
0 missing
FCFP4_1024b529numeric2 unique values
0 missing
FCFP4_1024b78numeric2 unique values
0 missing
FCFP4_1024b2numeric2 unique values
0 missing
FCFP4_1024b444numeric2 unique values
0 missing
FCFP4_1024b492numeric2 unique values
0 missing
FCFP4_1024b679numeric2 unique values
0 missing
FCFP4_1024b859numeric2 unique values
0 missing
FCFP4_1024b845numeric2 unique values
0 missing
FCFP4_1024b507numeric2 unique values
0 missing
FCFP4_1024b860numeric2 unique values
0 missing
FCFP4_1024b99numeric2 unique values
0 missing
FCFP4_1024b804numeric2 unique values
0 missing
FCFP4_1024b10numeric2 unique values
0 missing
FCFP4_1024b118numeric2 unique values
0 missing
FCFP4_1024b18numeric2 unique values
0 missing
FCFP4_1024b784numeric2 unique values
0 missing
FCFP4_1024b412numeric2 unique values
0 missing
FCFP4_1024b649numeric2 unique values
0 missing
FCFP4_1024b847numeric2 unique values
0 missing
FCFP4_1024b25numeric2 unique values
0 missing
FCFP4_1024b57numeric2 unique values
0 missing
FCFP4_1024b376numeric2 unique values
0 missing
FCFP4_1024b65numeric2 unique values
0 missing
FCFP4_1024b348numeric2 unique values
0 missing

62 properties

273
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.
Third quartile of entropy among attributes.
4.03
Maximum kurtosis among attributes of the numeric type.
0.11
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
0.23
Third quartile of kurtosis among attributes of the numeric type.
4.99
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.
0.51
Third quartile of means 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.
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.
-1.59
Minimum skewness among attributes of the numeric type.
1.89
Percentage of nominal attributes.
1.39
Third quartile of skewness among attributes of the numeric type.
2.45
Maximum skewness among attributes of the numeric type.
0.32
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.5
Third quartile of standard deviation of attributes of the numeric type.
0.67
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.9
First quartile of kurtosis 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.
Number of instances belonging to the least frequent class.
0.22
First quartile of means among attributes of the numeric type.
-0.48
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.
0.47
Mean of means among attributes of the numeric type.
-0.05
First quartile of skewness among attributes of the numeric type.
0.68
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.4
First quartile of standard deviation of attributes of the numeric type.
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.
0.19
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
-1.6
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.
0.63
Mean skewness among attributes of the numeric type.
0.4
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
0.45
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.
0.41
Second quartile (Median) of skewness among attributes of the numeric type.
0.48
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-2.01
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.

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