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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2996

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2996

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 by Noureddin Sadawi
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This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL2996 (TID: 12247), and it has 1403 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)numeric358 unique values
0 missing
molecule_id (row identifier)nominal1403 unique values
0 missing
FCFP4_1024b114numeric2 unique values
0 missing
FCFP4_1024b993numeric2 unique values
0 missing
FCFP4_1024b374numeric2 unique values
0 missing
FCFP4_1024b207numeric2 unique values
0 missing
FCFP4_1024b848numeric2 unique values
0 missing
FCFP4_1024b612numeric2 unique values
0 missing
FCFP4_1024b192numeric2 unique values
0 missing
FCFP4_1024b265numeric2 unique values
0 missing
FCFP4_1024b204numeric2 unique values
0 missing
FCFP4_1024b177numeric2 unique values
0 missing
FCFP4_1024b199numeric2 unique values
0 missing
FCFP4_1024b33numeric2 unique values
0 missing
FCFP4_1024b107numeric2 unique values
0 missing
FCFP4_1024b123numeric2 unique values
0 missing
FCFP4_1024b714numeric2 unique values
0 missing
FCFP4_1024b252numeric2 unique values
0 missing
FCFP4_1024b732numeric2 unique values
0 missing
FCFP4_1024b787numeric2 unique values
0 missing
FCFP4_1024b319numeric2 unique values
0 missing
FCFP4_1024b937numeric2 unique values
0 missing
FCFP4_1024b361numeric2 unique values
0 missing
FCFP4_1024b57numeric2 unique values
0 missing
FCFP4_1024b644numeric2 unique values
0 missing
FCFP4_1024b94numeric2 unique values
0 missing
FCFP4_1024b652numeric2 unique values
0 missing
FCFP4_1024b875numeric2 unique values
0 missing
FCFP4_1024b392numeric2 unique values
0 missing
FCFP4_1024b451numeric2 unique values
0 missing
FCFP4_1024b472numeric2 unique values
0 missing
FCFP4_1024b532numeric2 unique values
0 missing
FCFP4_1024b366numeric2 unique values
0 missing
FCFP4_1024b75numeric2 unique values
0 missing
FCFP4_1024b530numeric2 unique values
0 missing
FCFP4_1024b603numeric2 unique values
0 missing
FCFP4_1024b821numeric2 unique values
0 missing
FCFP4_1024b37numeric2 unique values
0 missing
FCFP4_1024b187numeric2 unique values
0 missing
FCFP4_1024b649numeric2 unique values
0 missing
FCFP4_1024b855numeric2 unique values
0 missing
FCFP4_1024b20numeric2 unique values
0 missing
FCFP4_1024b524numeric2 unique values
0 missing
FCFP4_1024b464numeric2 unique values
0 missing
FCFP4_1024b352numeric2 unique values
0 missing
FCFP4_1024b10numeric2 unique values
0 missing
FCFP4_1024b69numeric2 unique values
0 missing
FCFP4_1024b137numeric2 unique values
0 missing
FCFP4_1024b81numeric2 unique values
0 missing
FCFP4_1024b437numeric2 unique values
0 missing
FCFP4_1024b806numeric2 unique values
0 missing
FCFP4_1024b923numeric2 unique values
0 missing
FCFP4_1024b182numeric2 unique values
0 missing
FCFP4_1024b490numeric2 unique values
0 missing
FCFP4_1024b760numeric2 unique values
0 missing
FCFP4_1024b983numeric2 unique values
0 missing
FCFP4_1024b1010numeric2 unique values
0 missing
FCFP4_1024b64numeric2 unique values
0 missing
FCFP4_1024b668numeric2 unique values
0 missing
FCFP4_1024b283numeric2 unique values
0 missing
FCFP4_1024b884numeric2 unique values
0 missing
FCFP4_1024b25numeric2 unique values
0 missing
FCFP4_1024b876numeric2 unique values
0 missing
FCFP4_1024b1020numeric2 unique values
0 missing
FCFP4_1024b574numeric2 unique values
0 missing
FCFP4_1024b314numeric2 unique values
0 missing
FCFP4_1024b400numeric2 unique values
0 missing
FCFP4_1024b635numeric2 unique values
0 missing
FCFP4_1024b270numeric2 unique values
0 missing
FCFP4_1024b885numeric2 unique values
0 missing
FCFP4_1024b458numeric2 unique values
0 missing
FCFP4_1024b553numeric2 unique values
0 missing
FCFP4_1024b438numeric2 unique values
0 missing
FCFP4_1024b963numeric2 unique values
0 missing
FCFP4_1024b298numeric2 unique values
0 missing
FCFP4_1024b194numeric2 unique values
0 missing
FCFP4_1024b643numeric2 unique values
0 missing
FCFP4_1024b22numeric2 unique values
0 missing
FCFP4_1024b576numeric2 unique values
0 missing
FCFP4_1024b555numeric2 unique values
0 missing
FCFP4_1024b85numeric2 unique values
0 missing
FCFP4_1024b502numeric2 unique values
0 missing
FCFP4_1024b482numeric2 unique values
0 missing
FCFP4_1024b4numeric2 unique values
0 missing
FCFP4_1024b600numeric2 unique values
0 missing
FCFP4_1024b602numeric2 unique values
0 missing
FCFP4_1024b375numeric2 unique values
0 missing
FCFP4_1024b793numeric2 unique values
0 missing
FCFP4_1024b720numeric2 unique values
0 missing
FCFP4_1024b445numeric2 unique values
0 missing
FCFP4_1024b514numeric2 unique values
0 missing
FCFP4_1024b409numeric2 unique values
0 missing
FCFP4_1024b61numeric2 unique values
0 missing
FCFP4_1024b151numeric2 unique values
0 missing
FCFP4_1024b981numeric2 unique values
0 missing
FCFP4_1024b167numeric2 unique values
0 missing
FCFP4_1024b815numeric2 unique values
0 missing
FCFP4_1024b495numeric2 unique values
0 missing
FCFP4_1024b1007numeric2 unique values
0 missing
FCFP4_1024b143numeric2 unique values
0 missing
FCFP4_1024b291numeric2 unique values
0 missing
FCFP4_1024b557numeric2 unique values
0 missing
FCFP4_1024b396numeric2 unique values
0 missing
FCFP4_1024b936numeric2 unique values
0 missing

62 properties

1403
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.
9.53
Maximum skewness among attributes of the numeric type.
0.1
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
3.54
Third quartile of skewness among attributes of the numeric type.
1.11
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.03
First quartile of kurtosis among attributes of the numeric type.
0.41
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.
0.06
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
8
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.
0.21
Mean of means among attributes of the numeric type.
1.39
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.25
First quartile of standard deviation of attributes of the numeric type.
0.22
Average class difference between consecutive instances.
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.
Entropy of the target attribute values.
Average number of distinct values among the attributes of the nominal type.
4.25
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.07
Number of attributes divided by the number of instances.
2.64
Mean skewness among attributes of the numeric type.
0.11
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.
Percentage of instances belonging to the most frequent class.
0.32
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.
2.49
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.98
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.31
Second quartile (Median) of standard deviation of attributes of the numeric type.
88.86
Maximum kurtosis among attributes of the numeric type.
0.01
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
5.92
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.
10.53
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.
99.04
Percentage of numeric attributes.
0.22
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.71
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.

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
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