Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5847

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5847

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: CHEMBL5847 (TID: 101351), and it has 299 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)numeric187 unique values
0 missing
molecule_id (row identifier)nominal299 unique values
0 missing
FCFP4_1024b177numeric2 unique values
0 missing
FCFP4_1024b10numeric2 unique values
0 missing
FCFP4_1024b626numeric2 unique values
0 missing
FCFP4_1024b431numeric2 unique values
0 missing
FCFP4_1024b644numeric2 unique values
0 missing
FCFP4_1024b581numeric2 unique values
0 missing
FCFP4_1024b844numeric2 unique values
0 missing
FCFP4_1024b37numeric2 unique values
0 missing
FCFP4_1024b635numeric2 unique values
0 missing
FCFP4_1024b674numeric2 unique values
0 missing
FCFP4_1024b632numeric2 unique values
0 missing
FCFP4_1024b817numeric2 unique values
0 missing
FCFP4_1024b993numeric2 unique values
0 missing
FCFP4_1024b504numeric2 unique values
0 missing
FCFP4_1024b708numeric2 unique values
0 missing
FCFP4_1024b453numeric2 unique values
0 missing
FCFP4_1024b437numeric2 unique values
0 missing
FCFP4_1024b643numeric2 unique values
0 missing
FCFP4_1024b235numeric2 unique values
0 missing
FCFP4_1024b299numeric2 unique values
0 missing
FCFP4_1024b356numeric2 unique values
0 missing
FCFP4_1024b825numeric2 unique values
0 missing
FCFP4_1024b54numeric2 unique values
0 missing
FCFP4_1024b447numeric2 unique values
0 missing
FCFP4_1024b983numeric2 unique values
0 missing
FCFP4_1024b1010numeric2 unique values
0 missing
FCFP4_1024b858numeric2 unique values
0 missing
FCFP4_1024b78numeric2 unique values
0 missing
FCFP4_1024b18numeric2 unique values
0 missing
FCFP4_1024b1018numeric2 unique values
0 missing
FCFP4_1024b692numeric2 unique values
0 missing
FCFP4_1024b896numeric2 unique values
0 missing
FCFP4_1024b48numeric2 unique values
0 missing
FCFP4_1024b80numeric2 unique values
0 missing
FCFP4_1024b161numeric2 unique values
0 missing
FCFP4_1024b634numeric2 unique values
0 missing
FCFP4_1024b204numeric2 unique values
0 missing
FCFP4_1024b51numeric2 unique values
0 missing
FCFP4_1024b826numeric2 unique values
0 missing
FCFP4_1024b209numeric2 unique values
0 missing
FCFP4_1024b271numeric2 unique values
0 missing
FCFP4_1024b128numeric2 unique values
0 missing
FCFP4_1024b67numeric2 unique values
0 missing
FCFP4_1024b859numeric2 unique values
0 missing
FCFP4_1024b1019numeric2 unique values
0 missing
FCFP4_1024b300numeric2 unique values
0 missing
FCFP4_1024b4numeric2 unique values
0 missing
FCFP4_1024b222numeric2 unique values
0 missing
FCFP4_1024b250numeric2 unique values
0 missing
FCFP4_1024b961numeric2 unique values
0 missing
FCFP4_1024b745numeric2 unique values
0 missing
FCFP4_1024b87numeric2 unique values
0 missing
FCFP4_1024b761numeric2 unique values
0 missing
FCFP4_1024b630numeric2 unique values
0 missing
FCFP4_1024b430numeric2 unique values
0 missing
FCFP4_1024b1002numeric2 unique values
0 missing
FCFP4_1024b625numeric2 unique values
0 missing
FCFP4_1024b553numeric2 unique values
0 missing
FCFP4_1024b787numeric2 unique values
0 missing
FCFP4_1024b208numeric2 unique values
0 missing
FCFP4_1024b360numeric2 unique values
0 missing
FCFP4_1024b669numeric2 unique values
0 missing
FCFP4_1024b8numeric2 unique values
0 missing
FCFP4_1024b325numeric2 unique values
0 missing
FCFP4_1024b1numeric1 unique values
0 missing
FCFP4_1024b100numeric2 unique values
0 missing
FCFP4_1024b1000numeric1 unique values
0 missing
FCFP4_1024b1001numeric2 unique values
0 missing
FCFP4_1024b1003numeric2 unique values
0 missing
FCFP4_1024b1004numeric1 unique values
0 missing
FCFP4_1024b1005numeric1 unique values
0 missing
FCFP4_1024b1006numeric2 unique values
0 missing
FCFP4_1024b1007numeric2 unique values
0 missing
FCFP4_1024b1008numeric1 unique values
0 missing
FCFP4_1024b1009numeric1 unique values
0 missing
FCFP4_1024b101numeric1 unique values
0 missing
FCFP4_1024b1011numeric1 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_1024b1016numeric1 unique values
0 missing
FCFP4_1024b1017numeric1 unique values
0 missing
FCFP4_1024b102numeric1 unique values
0 missing
FCFP4_1024b1020numeric2 unique values
0 missing
FCFP4_1024b1021numeric1 unique values
0 missing
FCFP4_1024b1022numeric1 unique values
0 missing
FCFP4_1024b1023numeric1 unique values
0 missing
FCFP4_1024b1024numeric1 unique values
0 missing
FCFP4_1024b103numeric1 unique values
0 missing
FCFP4_1024b104numeric2 unique values
0 missing
FCFP4_1024b105numeric2 unique values
0 missing
FCFP4_1024b106numeric1 unique values
0 missing
FCFP4_1024b107numeric2 unique values
0 missing
FCFP4_1024b108numeric2 unique values
0 missing
FCFP4_1024b109numeric1 unique values
0 missing
FCFP4_1024b11numeric1 unique values
0 missing
FCFP4_1024b110numeric2 unique values
0 missing
FCFP4_1024b111numeric1 unique values
0 missing
FCFP4_1024b112numeric1 unique values
0 missing
FCFP4_1024b113numeric2 unique values
0 missing
FCFP4_1024b114numeric1 unique values
0 missing

62 properties

299
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.
Third quartile of entropy among attributes.
299
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
19.83
Third quartile of kurtosis among attributes of the numeric type.
4.92
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.
0.22
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.
99.04
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.
-1.64
Minimum skewness among attributes of the numeric type.
0.96
Percentage of nominal attributes.
4.66
Third quartile of skewness among attributes of the numeric type.
17.29
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.4
Third quartile of standard deviation of attributes of the numeric type.
0.81
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.22
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
First quartile of means among attributes of the numeric type.
32.45
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.
1.31
First quartile of skewness among attributes of the numeric type.
0.57
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.06
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.
0.35
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
2.92
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.
3.78
Mean skewness among attributes of the numeric type.
0.06
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
0.24
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.
2.08
Second quartile (Median) of skewness among attributes of the numeric type.
0.22
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.94
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