Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720

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: CHEMBL5720 (TID: 101301), and it has 151 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)numeric131 unique values
0 missing
molecule_id (row identifier)nominal151 unique values
0 missing
FCFP4_1024b153numeric2 unique values
0 missing
FCFP4_1024b764numeric2 unique values
0 missing
FCFP4_1024b294numeric2 unique values
0 missing
FCFP4_1024b429numeric2 unique values
0 missing
FCFP4_1024b254numeric2 unique values
0 missing
FCFP4_1024b611numeric2 unique values
0 missing
FCFP4_1024b1numeric1 unique values
0 missing
FCFP4_1024b10numeric2 unique values
0 missing
FCFP4_1024b100numeric2 unique values
0 missing
FCFP4_1024b1000numeric1 unique values
0 missing
FCFP4_1024b1001numeric2 unique values
0 missing
FCFP4_1024b1002numeric1 unique values
0 missing
FCFP4_1024b1003numeric1 unique values
0 missing
FCFP4_1024b1004numeric1 unique values
0 missing
FCFP4_1024b1005numeric2 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_1024b1011numeric1 unique values
0 missing
FCFP4_1024b1012numeric1 unique values
0 missing
FCFP4_1024b1013numeric1 unique values
0 missing
FCFP4_1024b1014numeric1 unique values
0 missing
FCFP4_1024b1015numeric1 unique values
0 missing
FCFP4_1024b1016numeric1 unique values
0 missing
FCFP4_1024b1017numeric1 unique values
0 missing
FCFP4_1024b1018numeric1 unique values
0 missing
FCFP4_1024b1019numeric2 unique values
0 missing
FCFP4_1024b102numeric2 unique values
0 missing
FCFP4_1024b1020numeric2 unique values
0 missing
FCFP4_1024b1021numeric1 unique values
0 missing
FCFP4_1024b1022numeric1 unique values
0 missing
FCFP4_1024b1023numeric2 unique values
0 missing
FCFP4_1024b1024numeric2 unique values
0 missing
FCFP4_1024b103numeric1 unique values
0 missing
FCFP4_1024b104numeric1 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_1024b110numeric1 unique values
0 missing
FCFP4_1024b111numeric1 unique values
0 missing
FCFP4_1024b112numeric1 unique values
0 missing
FCFP4_1024b113numeric1 unique values
0 missing
FCFP4_1024b114numeric1 unique values
0 missing
FCFP4_1024b115numeric2 unique values
0 missing
FCFP4_1024b116numeric1 unique values
0 missing
FCFP4_1024b117numeric1 unique values
0 missing
FCFP4_1024b118numeric1 unique values
0 missing
FCFP4_1024b119numeric1 unique values
0 missing
FCFP4_1024b12numeric1 unique values
0 missing
FCFP4_1024b120numeric1 unique values
0 missing
FCFP4_1024b121numeric1 unique values
0 missing
FCFP4_1024b122numeric2 unique values
0 missing
FCFP4_1024b123numeric2 unique values
0 missing
FCFP4_1024b124numeric1 unique values
0 missing
FCFP4_1024b125numeric1 unique values
0 missing
FCFP4_1024b126numeric1 unique values
0 missing
FCFP4_1024b127numeric2 unique values
0 missing
FCFP4_1024b128numeric2 unique values
0 missing
FCFP4_1024b129numeric2 unique values
0 missing
FCFP4_1024b13numeric1 unique values
0 missing
FCFP4_1024b130numeric1 unique values
0 missing
FCFP4_1024b131numeric1 unique values
0 missing
FCFP4_1024b132numeric1 unique values
0 missing
FCFP4_1024b133numeric2 unique values
0 missing
FCFP4_1024b134numeric1 unique values
0 missing
FCFP4_1024b135numeric1 unique values
0 missing
FCFP4_1024b136numeric2 unique values
0 missing
FCFP4_1024b137numeric2 unique values
0 missing
FCFP4_1024b138numeric2 unique values
0 missing
FCFP4_1024b139numeric2 unique values
0 missing
FCFP4_1024b14numeric1 unique values
0 missing
FCFP4_1024b140numeric1 unique values
0 missing
FCFP4_1024b141numeric1 unique values
0 missing
FCFP4_1024b142numeric1 unique values
0 missing
FCFP4_1024b143numeric2 unique values
0 missing
FCFP4_1024b144numeric2 unique values
0 missing
FCFP4_1024b145numeric2 unique values
0 missing
FCFP4_1024b146numeric1 unique values
0 missing
FCFP4_1024b147numeric1 unique values
0 missing
FCFP4_1024b148numeric1 unique values
0 missing
FCFP4_1024b149numeric1 unique values
0 missing
FCFP4_1024b15numeric1 unique values
0 missing
FCFP4_1024b150numeric1 unique values
0 missing
FCFP4_1024b151numeric1 unique values
0 missing
FCFP4_1024b152numeric2 unique values
0 missing
FCFP4_1024b154numeric2 unique values
0 missing
FCFP4_1024b155numeric1 unique values
0 missing
FCFP4_1024b156numeric1 unique values
0 missing
FCFP4_1024b157numeric1 unique values
0 missing
FCFP4_1024b158numeric1 unique values
0 missing
FCFP4_1024b159numeric1 unique values
0 missing
FCFP4_1024b16numeric1 unique values
0 missing
FCFP4_1024b160numeric2 unique values
0 missing
FCFP4_1024b161numeric1 unique values
0 missing
FCFP4_1024b162numeric1 unique values
0 missing
FCFP4_1024b163numeric1 unique values
0 missing
Show first 100 features

62 properties

NumberOfInstances
151
Number of instances (rows) of the dataset.
NumberOfFeatures
104
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
103
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
MaxKurtosisOfNumericAtts
151
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.
Quartile3KurtosisOfNumericAtts
151
Third quartile of kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
5.81
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.
Quartile3MeansOfNumericAtts
0.01
Third quartile of means 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
99.04
Percentage of numeric attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-2.11
Minimum skewness among attributes of the numeric type.
PercentageOfSymbolicFeatures
0.96
Percentage of nominal attributes.
Quartile3SkewnessOfNumericAtts
12.29
Third quartile of skewness among attributes of the numeric type.
MaxSkewnessOfNumericAtts
12.29
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.
Quartile3StdDevOfNumericAtts
0.11
Third quartile of standard deviation of attributes of the numeric type.
MaxStdDevOfNumericAtts
1.24
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
Quartile1KurtosisOfNumericAtts
-0.67
First quartile of kurtosis among attributes of the numeric type.
StdvNominalAttDistinctValues
Standard deviation of the number of distinct values among attributes of the nominal 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.
MeanKurtosisOfNumericAtts
53.9
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
0.13
Mean of means among attributes of the numeric type.
Quartile1SkewnessOfNumericAtts
0.86
First quartile of skewness among attributes of the numeric type.
AutoCorrelation
-0.3
Average class difference between consecutive instances.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
Quartile1StdDevOfNumericAtts
0
First quartile of standard deviation of attributes of the numeric type.
ClassEntropy
Entropy of the target attribute values.
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.
Dimensionality
0.69
Number of attributes divided by the number of instances.
MeanNominalAttDistinctValues
Average number of distinct values among the attributes of the nominal type.
Quartile2KurtosisOfNumericAtts
20.29
Second quartile (Median) of kurtosis 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.
MeanSkewnessOfNumericAtts
5.48
Mean skewness among attributes of the numeric type.
Quartile2MeansOfNumericAtts
0
Second quartile (Median) of means among attributes of the numeric type.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
0.1
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
4.65
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
0
Second quartile (Median) of standard deviation of attributes of the numeric type.
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-2.03
Minimum kurtosis among attributes of the numeric type.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
Show all 62 properties

12 tasks

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
1 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
0 runs
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5720
0 runs - estimation_procedure: 50 times Clustering
Define a new task