Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2094138

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2094138

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: CHEMBL2094138 (TID: 104720), and it has 425 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)numeric165 unique values
0 missing
molecule_id (row identifier)nominal425 unique values
0 missing
FCFP4_1024b604numeric2 unique values
0 missing
FCFP4_1024b638numeric2 unique values
0 missing
FCFP4_1024b204numeric2 unique values
0 missing
FCFP4_1024b434numeric2 unique values
0 missing
FCFP4_1024b855numeric2 unique values
0 missing
FCFP4_1024b643numeric2 unique values
0 missing
FCFP4_1024b536numeric2 unique values
0 missing
FCFP4_1024b270numeric2 unique values
0 missing
FCFP4_1024b437numeric2 unique values
0 missing
FCFP4_1024b86numeric2 unique values
0 missing
FCFP4_1024b635numeric2 unique values
0 missing
FCFP4_1024b143numeric2 unique values
0 missing
FCFP4_1024b595numeric2 unique values
0 missing
FCFP4_1024b385numeric2 unique values
0 missing
FCFP4_1024b614numeric2 unique values
0 missing
FCFP4_1024b364numeric2 unique values
0 missing
FCFP4_1024b63numeric2 unique values
0 missing
FCFP4_1024b128numeric2 unique values
0 missing
FCFP4_1024b764numeric2 unique values
0 missing
FCFP4_1024b199numeric2 unique values
0 missing
FCFP4_1024b580numeric2 unique values
0 missing
FCFP4_1024b453numeric2 unique values
0 missing
FCFP4_1024b455numeric2 unique values
0 missing
FCFP4_1024b133numeric2 unique values
0 missing
FCFP4_1024b860numeric2 unique values
0 missing
FCFP4_1024b898numeric2 unique values
0 missing
FCFP4_1024b327numeric2 unique values
0 missing
FCFP4_1024b876numeric2 unique values
0 missing
FCFP4_1024b714numeric2 unique values
0 missing
FCFP4_1024b316numeric2 unique values
0 missing
FCFP4_1024b537numeric2 unique values
0 missing
FCFP4_1024b54numeric2 unique values
0 missing
FCFP4_1024b10numeric2 unique values
0 missing
FCFP4_1024b767numeric2 unique values
0 missing
FCFP4_1024b903numeric2 unique values
0 missing
FCFP4_1024b603numeric2 unique values
0 missing
FCFP4_1024b976numeric2 unique values
0 missing
FCFP4_1024b45numeric2 unique values
0 missing
FCFP4_1024b504numeric2 unique values
0 missing
FCFP4_1024b152numeric2 unique values
0 missing
FCFP4_1024b215numeric2 unique values
0 missing
FCFP4_1024b600numeric2 unique values
0 missing
FCFP4_1024b793numeric2 unique values
0 missing
FCFP4_1024b606numeric2 unique values
0 missing
FCFP4_1024b844numeric2 unique values
0 missing
FCFP4_1024b875numeric2 unique values
0 missing
FCFP4_1024b348numeric2 unique values
0 missing
FCFP4_1024b969numeric2 unique values
0 missing
FCFP4_1024b446numeric2 unique values
0 missing
FCFP4_1024b822numeric2 unique values
0 missing
FCFP4_1024b879numeric2 unique values
0 missing
FCFP4_1024b57numeric2 unique values
0 missing
FCFP4_1024b971numeric2 unique values
0 missing
FCFP4_1024b20numeric2 unique values
0 missing
FCFP4_1024b343numeric2 unique values
0 missing
FCFP4_1024b263numeric2 unique values
0 missing
FCFP4_1024b492numeric2 unique values
0 missing
FCFP4_1024b680numeric2 unique values
0 missing
FCFP4_1024b13numeric2 unique values
0 missing
FCFP4_1024b265numeric2 unique values
0 missing
FCFP4_1024b644numeric2 unique values
0 missing
FCFP4_1024b235numeric2 unique values
0 missing
FCFP4_1024b388numeric2 unique values
0 missing
FCFP4_1024b399numeric2 unique values
0 missing
FCFP4_1024b521numeric2 unique values
0 missing
FCFP4_1024b395numeric2 unique values
0 missing
FCFP4_1024b985numeric2 unique values
0 missing
FCFP4_1024b709numeric2 unique values
0 missing
FCFP4_1024b983numeric2 unique values
0 missing
FCFP4_1024b1000numeric2 unique values
0 missing
FCFP4_1024b981numeric2 unique values
0 missing
FCFP4_1024b148numeric2 unique values
0 missing
FCFP4_1024b324numeric2 unique values
0 missing
FCFP4_1024b372numeric2 unique values
0 missing
FCFP4_1024b612numeric2 unique values
0 missing
FCFP4_1024b319numeric2 unique values
0 missing
FCFP4_1024b553numeric2 unique values
0 missing
FCFP4_1024b139numeric2 unique values
0 missing
FCFP4_1024b357numeric2 unique values
0 missing
FCFP4_1024b283numeric2 unique values
0 missing
FCFP4_1024b1015numeric2 unique values
0 missing
FCFP4_1024b429numeric2 unique values
0 missing
FCFP4_1024b4numeric2 unique values
0 missing
FCFP4_1024b107numeric2 unique values
0 missing
FCFP4_1024b37numeric2 unique values
0 missing
FCFP4_1024b376numeric2 unique values
0 missing
FCFP4_1024b616numeric2 unique values
0 missing
FCFP4_1024b461numeric2 unique values
0 missing
FCFP4_1024b160numeric2 unique values
0 missing
FCFP4_1024b710numeric2 unique values
0 missing
FCFP4_1024b33numeric2 unique values
0 missing
FCFP4_1024b963numeric2 unique values
0 missing
FCFP4_1024b925numeric2 unique values
0 missing
FCFP4_1024b942numeric2 unique values
0 missing
FCFP4_1024b669numeric2 unique values
0 missing
FCFP4_1024b390numeric2 unique values
0 missing
FCFP4_1024b818numeric2 unique values
0 missing
FCFP4_1024b490numeric2 unique values
0 missing
FCFP4_1024b79numeric2 unique values
0 missing
FCFP4_1024b115numeric2 unique values
0 missing
FCFP4_1024b528numeric2 unique values
0 missing
FCFP4_1024b464numeric2 unique values
0 missing

62 properties

425
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.
2.29
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.24
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.14
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.
2.22
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.
0.35
Mean standard deviation of attributes of the numeric type.
2.07
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.
0.35
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.
0.03
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
34.08
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
8.48
Third quartile of kurtosis among attributes of the numeric type.
5.3
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
99.04
Percentage of numeric attributes.
0.26
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-1.86
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.
The maximum number of distinct values among attributes of the nominal type.
0.16
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
3.23
Third quartile of skewness among attributes of the numeric type.
5.99
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.58
First quartile of kurtosis among attributes of the numeric type.
0.43
Third quartile of standard deviation of attributes of the numeric type.
1.06
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0.08
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.
5.79
Mean kurtosis among attributes of the numeric type.
1.13
First quartile of skewness among attributes of the numeric type.
0.25
Mean of means among attributes of the numeric type.
0.26
First quartile of standard deviation of attributes of the numeric type.
0.15
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

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