Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222

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: CHEMBL222 (TID: 100), and it has 2790 rows and 256 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.

258 features

pXC50 (target)numeric1182 unique values
0 missing
molecule_id (row identifier)nominal2790 unique values
0 missing
FCFP4_1024b241numeric2 unique values
0 missing
FCFP4_1024b859numeric2 unique values
0 missing
FCFP4_1024b603numeric2 unique values
0 missing
FCFP4_1024b981numeric2 unique values
0 missing
FCFP4_1024b702numeric2 unique values
0 missing
FCFP4_1024b122numeric2 unique values
0 missing
FCFP4_1024b4numeric2 unique values
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FCFP4_1024b512numeric2 unique values
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FCFP4_1024b961numeric2 unique values
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FCFP4_1024b28numeric2 unique values
0 missing
FCFP4_1024b790numeric2 unique values
0 missing
FCFP4_1024b644numeric2 unique values
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FCFP4_1024b338numeric2 unique values
0 missing
FCFP4_1024b357numeric2 unique values
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FCFP4_1024b957numeric2 unique values
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FCFP4_1024b938numeric2 unique values
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FCFP4_1024b630numeric2 unique values
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FCFP4_1024b182numeric2 unique values
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FCFP4_1024b70numeric2 unique values
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FCFP4_1024b541numeric2 unique values
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FCFP4_1024b107numeric2 unique values
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FCFP4_1024b110numeric2 unique values
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FCFP4_1024b885numeric2 unique values
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FCFP4_1024b283numeric2 unique values
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FCFP4_1024b10numeric2 unique values
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FCFP4_1024b325numeric2 unique values
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FCFP4_1024b314numeric2 unique values
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FCFP4_1024b824numeric2 unique values
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FCFP4_1024b640numeric2 unique values
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FCFP4_1024b152numeric2 unique values
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FCFP4_1024b940numeric2 unique values
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FCFP4_1024b297numeric2 unique values
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FCFP4_1024b145numeric2 unique values
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FCFP4_1024b286numeric2 unique values
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FCFP4_1024b339numeric2 unique values
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FCFP4_1024b24numeric2 unique values
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FCFP4_1024b44numeric2 unique values
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FCFP4_1024b912numeric2 unique values
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FCFP4_1024b553numeric2 unique values
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FCFP4_1024b707numeric2 unique values
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FCFP4_1024b57numeric2 unique values
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FCFP4_1024b11numeric2 unique values
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FCFP4_1024b972numeric2 unique values
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FCFP4_1024b20numeric2 unique values
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FCFP4_1024b720numeric2 unique values
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FCFP4_1024b69numeric2 unique values
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FCFP4_1024b699numeric2 unique values
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FCFP4_1024b500numeric2 unique values
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FCFP4_1024b335numeric2 unique values
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FCFP4_1024b631numeric2 unique values
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FCFP4_1024b927numeric2 unique values
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FCFP4_1024b296numeric2 unique values
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FCFP4_1024b310numeric2 unique values
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FCFP4_1024b730numeric2 unique values
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FCFP4_1024b842numeric2 unique values
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FCFP4_1024b966numeric2 unique values
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FCFP4_1024b598numeric2 unique values
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FCFP4_1024b840numeric2 unique values
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FCFP4_1024b205numeric2 unique values
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FCFP4_1024b1numeric2 unique values
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FCFP4_1024b100numeric2 unique values
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FCFP4_1024b1000numeric2 unique values
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FCFP4_1024b1001numeric2 unique values
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FCFP4_1024b1002numeric2 unique values
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FCFP4_1024b1003numeric2 unique values
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FCFP4_1024b1004numeric2 unique values
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FCFP4_1024b1005numeric2 unique values
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FCFP4_1024b1006numeric2 unique values
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FCFP4_1024b1007numeric2 unique values
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FCFP4_1024b1008numeric2 unique values
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FCFP4_1024b1009numeric2 unique values
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FCFP4_1024b101numeric2 unique values
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FCFP4_1024b1010numeric2 unique values
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FCFP4_1024b1011numeric2 unique values
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FCFP4_1024b1012numeric2 unique values
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FCFP4_1024b1013numeric2 unique values
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FCFP4_1024b1016numeric2 unique values
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FCFP4_1024b1017numeric2 unique values
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FCFP4_1024b1019numeric2 unique values
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FCFP4_1024b102numeric2 unique values
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FCFP4_1024b1020numeric2 unique values
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FCFP4_1024b1021numeric2 unique values
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FCFP4_1024b1022numeric2 unique values
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FCFP4_1024b1024numeric2 unique values
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FCFP4_1024b106numeric2 unique values
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FCFP4_1024b109numeric2 unique values
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FCFP4_1024b111numeric1 unique values
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FCFP4_1024b125numeric1 unique values
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FCFP4_1024b14numeric2 unique values
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FCFP4_1024b142numeric2 unique values
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FCFP4_1024b143numeric1 unique values
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FCFP4_1024b149numeric1 unique values
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FCFP4_1024b15numeric2 unique values
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FCFP4_1024b153numeric2 unique values
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FCFP4_1024b16numeric2 unique values
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FCFP4_1024b160numeric2 unique values
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FCFP4_1024b162numeric2 unique values
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FCFP4_1024b17numeric2 unique values
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FCFP4_1024b176numeric2 unique values
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FCFP4_1024b179numeric1 unique values
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FCFP4_1024b183numeric2 unique values
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FCFP4_1024b199numeric2 unique values
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FCFP4_1024b2numeric2 unique values
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FCFP4_1024b200numeric2 unique values
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FCFP4_1024b201numeric2 unique values
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FCFP4_1024b202numeric2 unique values
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FCFP4_1024b203numeric2 unique values
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FCFP4_1024b204numeric1 unique values
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FCFP4_1024b206numeric2 unique values
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FCFP4_1024b207numeric2 unique values
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FCFP4_1024b21numeric2 unique values
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FCFP4_1024b210numeric2 unique values
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FCFP4_1024b211numeric2 unique values
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FCFP4_1024b212numeric2 unique values
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FCFP4_1024b213numeric2 unique values
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FCFP4_1024b214numeric1 unique values
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FCFP4_1024b216numeric1 unique values
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FCFP4_1024b217numeric2 unique values
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FCFP4_1024b219numeric2 unique values
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FCFP4_1024b22numeric2 unique values
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FCFP4_1024b220numeric2 unique values
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FCFP4_1024b221numeric2 unique values
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FCFP4_1024b222numeric2 unique values
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FCFP4_1024b223numeric2 unique values
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FCFP4_1024b224numeric2 unique values
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FCFP4_1024b225numeric2 unique values
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FCFP4_1024b226numeric2 unique values
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FCFP4_1024b227numeric2 unique values
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FCFP4_1024b228numeric2 unique values
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FCFP4_1024b229numeric2 unique values
0 missing
FCFP4_1024b23numeric1 unique values
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FCFP4_1024b230numeric1 unique values
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FCFP4_1024b231numeric2 unique values
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FCFP4_1024b232numeric2 unique values
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FCFP4_1024b234numeric2 unique values
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FCFP4_1024b235numeric2 unique values
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FCFP4_1024b236numeric2 unique values
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FCFP4_1024b238numeric1 unique values
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Show first 100 features

62 properties

NumberOfInstances
2790
Number of instances (rows) of the dataset.
NumberOfFeatures
258
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
257
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
MaxSkewnessOfNumericAtts
52.82
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0
Minimum standard deviation of attributes of the numeric type.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
17.08
Third quartile of skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
1.17
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
Quartile1KurtosisOfNumericAtts
22.04
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
0.18
Third quartile of standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
Number of instances belonging to the least frequent class.
Quartile1MeansOfNumericAtts
0
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
Standard deviation of the number of distinct values among attributes of the nominal type.
MeanKurtosisOfNumericAtts
396.87
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
0
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
MeanMeansOfNumericAtts
0.08
Mean of means among attributes of the numeric type.
Quartile1SkewnessOfNumericAtts
4.79
First quartile of skewness among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
Quartile1StdDevOfNumericAtts
0.05
First quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
-0.03
Average class difference between consecutive instances.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
ClassEntropy
Entropy of the target attribute values.
MeanNominalAttDistinctValues
Average number of distinct values among the attributes of the nominal type.
Quartile2KurtosisOfNumericAtts
70.55
Second quartile (Median) of kurtosis among attributes of the numeric type.
Dimensionality
0.09
Number of attributes divided by the number of instances.
MeanSkewnessOfNumericAtts
13.66
Mean skewness among attributes of the numeric type.
Quartile2MeansOfNumericAtts
0.01
Second quartile (Median) of means among attributes of the numeric type.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
0.14
Mean standard deviation of attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
MajorityClassSize
Number of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2SkewnessOfNumericAtts
8.4
Second quartile (Median) of skewness among attributes of the numeric type.
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-2
Minimum kurtosis among attributes of the numeric type.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
0.11
Second quartile (Median) of standard deviation of attributes of the numeric type.
MaxKurtosisOfNumericAtts
2790
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0
Minimum of means among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
MaxMeansOfNumericAtts
6.66
Maximum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
305.55
Third quartile of kurtosis among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
The minimal number of distinct values among attributes of the nominal type.
PercentageOfNumericFeatures
99.61
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
0.04
Third quartile of means among attributes of the numeric type.
MaxNominalAttDistinctValues
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-17.53
Minimum skewness among attributes of the numeric type.
PercentageOfSymbolicFeatures
0.39
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Show all 62 properties

12 tasks

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
1 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
0 runs
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL222
0 runs - estimation_procedure: 50 times Clustering
Define a new task