Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3891

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3891

deactivated ARFF Publicly available Visibility: public Uploaded 16-07-2016 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: CHEMBL3891 (TID: 12955), and it has 532 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)numeric289 unique values
0 missing
molecule_id (row identifier)nominal532 unique values
0 missing
FCFP4_1024b197numeric2 unique values
0 missing
FCFP4_1024b352numeric2 unique values
0 missing
FCFP4_1024b541numeric2 unique values
0 missing
FCFP4_1024b943numeric2 unique values
0 missing
FCFP4_1024b628numeric2 unique values
0 missing
FCFP4_1024b375numeric2 unique values
0 missing
FCFP4_1024b964numeric2 unique values
0 missing
FCFP4_1024b45numeric2 unique values
0 missing
FCFP4_1024b171numeric2 unique values
0 missing
FCFP4_1024b173numeric2 unique values
0 missing
FCFP4_1024b862numeric2 unique values
0 missing
FCFP4_1024b283numeric2 unique values
0 missing
FCFP4_1024b131numeric2 unique values
0 missing
FCFP4_1024b948numeric2 unique values
0 missing
FCFP4_1024b218numeric2 unique values
0 missing
FCFP4_1024b780numeric2 unique values
0 missing
FCFP4_1024b1022numeric2 unique values
0 missing
FCFP4_1024b395numeric2 unique values
0 missing
FCFP4_1024b936numeric2 unique values
0 missing
FCFP4_1024b8numeric2 unique values
0 missing
FCFP4_1024b888numeric2 unique values
0 missing
FCFP4_1024b883numeric2 unique values
0 missing
FCFP4_1024b314numeric2 unique values
0 missing
FCFP4_1024b410numeric2 unique values
0 missing
FCFP4_1024b603numeric2 unique values
0 missing
FCFP4_1024b714numeric2 unique values
0 missing
FCFP4_1024b208numeric2 unique values
0 missing
FCFP4_1024b891numeric2 unique values
0 missing
FCFP4_1024b859numeric2 unique values
0 missing
FCFP4_1024b632numeric2 unique values
0 missing
FCFP4_1024b574numeric2 unique values
0 missing
FCFP4_1024b635numeric2 unique values
0 missing
FCFP4_1024b296numeric2 unique values
0 missing
FCFP4_1024b855numeric2 unique values
0 missing
FCFP4_1024b698numeric2 unique values
0 missing
FCFP4_1024b120numeric2 unique values
0 missing
FCFP4_1024b844numeric2 unique values
0 missing
FCFP4_1024b604numeric2 unique values
0 missing
FCFP4_1024b557numeric2 unique values
0 missing
FCFP4_1024b366numeric2 unique values
0 missing
FCFP4_1024b324numeric2 unique values
0 missing
FCFP4_1024b54numeric2 unique values
0 missing
FCFP4_1024b540numeric2 unique values
0 missing
FCFP4_1024b453numeric2 unique values
0 missing
FCFP4_1024b467numeric2 unique values
0 missing
FCFP4_1024b1005numeric2 unique values
0 missing
FCFP4_1024b847numeric2 unique values
0 missing
FCFP4_1024b429numeric2 unique values
0 missing
FCFP4_1024b351numeric2 unique values
0 missing
FCFP4_1024b799numeric2 unique values
0 missing
FCFP4_1024b253numeric2 unique values
0 missing

62 properties

532
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.
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.
0.1
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
1.78
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.
1.71
Mean skewness among attributes of the numeric type.
0.16
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
0.38
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.
1.85
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.
0.36
Second quartile (Median) of standard deviation of attributes of the numeric type.
28.56
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.
6.84
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.
9.46
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.
0.41
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-3.13
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.
5.52
Maximum skewness among attributes of the numeric type.
0.17
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
3.38
Third quartile of skewness among attributes of the numeric type.
1.54
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.52
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.
0.07
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
5.1
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.
0.4
Mean of means among attributes of the numeric type.
0.38
First quartile of skewness among attributes of the numeric type.
-0.05
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.26
First quartile of standard deviation of attributes of the numeric type.

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