Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5122

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5122

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: CHEMBL5122 (TID: 101079), and it has 125 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)numeric58 unique values
0 missing
molecule_id (row identifier)nominal125 unique values
0 missing
FCFP4_1024b1019numeric2 unique values
0 missing
FCFP4_1024b416numeric2 unique values
0 missing
FCFP4_1024b784numeric2 unique values
0 missing
FCFP4_1024b932numeric2 unique values
0 missing
FCFP4_1024b970numeric2 unique values
0 missing
FCFP4_1024b71numeric2 unique values
0 missing
FCFP4_1024b489numeric2 unique values
0 missing
FCFP4_1024b9numeric2 unique values
0 missing
FCFP4_1024b768numeric2 unique values
0 missing
FCFP4_1024b87numeric2 unique values
0 missing
FCFP4_1024b253numeric2 unique values
0 missing
FCFP4_1024b148numeric2 unique values
0 missing
FCFP4_1024b730numeric2 unique values
0 missing
FCFP4_1024b458numeric2 unique values
0 missing
FCFP4_1024b252numeric2 unique values
0 missing
FCFP4_1024b911numeric2 unique values
0 missing
FCFP4_1024b283numeric2 unique values
0 missing
FCFP4_1024b529numeric2 unique values
0 missing
FCFP4_1024b1numeric2 unique values
0 missing
FCFP4_1024b10numeric2 unique values
0 missing
FCFP4_1024b100numeric1 unique values
0 missing
FCFP4_1024b1000numeric2 unique values
0 missing
FCFP4_1024b1001numeric2 unique values
0 missing
FCFP4_1024b1002numeric2 unique values
0 missing
FCFP4_1024b1003numeric2 unique values
0 missing
FCFP4_1024b1004numeric2 unique values
0 missing
FCFP4_1024b1005numeric1 unique values
0 missing
FCFP4_1024b1006numeric2 unique values
0 missing
FCFP4_1024b1007numeric1 unique values
0 missing
FCFP4_1024b1008numeric1 unique values
0 missing
FCFP4_1024b1009numeric1 unique values
0 missing
FCFP4_1024b101numeric1 unique values
0 missing
FCFP4_1024b1010numeric2 unique values
0 missing
FCFP4_1024b1011numeric2 unique values
0 missing
FCFP4_1024b1012numeric2 unique values
0 missing
FCFP4_1024b1013numeric2 unique values
0 missing
FCFP4_1024b1014numeric1 unique values
0 missing
FCFP4_1024b1015numeric2 unique values
0 missing
FCFP4_1024b1016numeric2 unique values
0 missing
FCFP4_1024b1017numeric1 unique values
0 missing
FCFP4_1024b1018numeric2 unique values
0 missing
FCFP4_1024b102numeric1 unique values
0 missing
FCFP4_1024b1020numeric2 unique values
0 missing
FCFP4_1024b1021numeric2 unique values
0 missing
FCFP4_1024b1022numeric1 unique values
0 missing
FCFP4_1024b1023numeric1 unique values
0 missing
FCFP4_1024b1024numeric1 unique values
0 missing
FCFP4_1024b103numeric2 unique values
0 missing
FCFP4_1024b104numeric1 unique values
0 missing
FCFP4_1024b105numeric1 unique values
0 missing
FCFP4_1024b106numeric1 unique values
0 missing

62 properties

125
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.
-1.12
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.42
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.03
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.
3.68
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.
0.24
Mean standard deviation of attributes of the numeric type.
0.95
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.
0.14
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.86
Minimum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
125
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
59.93
Third quartile of kurtosis among attributes of the numeric type.
5.95
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.11
Percentage of numeric attributes.
0.32
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-7.81
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.
The maximum number of distinct values among attributes of the nominal type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
7.81
Third quartile of skewness among attributes of the numeric type.
11.18
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.47
First quartile of kurtosis among attributes of the numeric type.
0.46
Third quartile of standard deviation of attributes of the numeric type.
1
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0
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.
32.52
Mean kurtosis among attributes of the numeric type.
0.72
First quartile of skewness among attributes of the numeric type.
0.26
Mean of means among attributes of the numeric type.
0
First quartile of standard deviation of attributes of the numeric type.
0.19
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