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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015

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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: CHEMBL2015 (TID: 161), and it has 84 rows and 63 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent Molecular Descriptors which were generated from SMILES strings. Missing value imputation was applied to this dataset (By choosing the Median). Feature selection was also applied.

65 features

pXC50 (target)numeric65 unique values
0 missing
GGI5numeric45 unique values
0 missing
P_VSA_LogP_6numeric15 unique values
0 missing
DELSnumeric84 unique values
0 missing
ATSC7snumeric84 unique values
0 missing
ATSC7enumeric82 unique values
0 missing
ATSC4enumeric77 unique values
0 missing
Eta_sh_ynumeric65 unique values
0 missing
CIC0numeric60 unique values
0 missing
JGI3numeric36 unique values
0 missing
SM11_AEA.bo.numeric40 unique values
0 missing
GGI4numeric45 unique values
0 missing
GGI2numeric13 unique values
0 missing
Eig03_EAnumeric40 unique values
0 missing
SaaCHnumeric84 unique values
0 missing
JGTnumeric51 unique values
0 missing
NtsCnumeric3 unique values
0 missing
GGI6numeric42 unique values
0 missing
P_VSA_LogP_4numeric23 unique values
0 missing
SPInumeric56 unique values
0 missing
ZM1Madnumeric75 unique values
0 missing
ZM2Madnumeric78 unique values
0 missing
Eig02_EA.ed.numeric40 unique values
0 missing
RCInumeric13 unique values
0 missing
RFDnumeric13 unique values
0 missing
SM06_EA.ri.numeric78 unique values
0 missing
SM11_AEA.dm.numeric40 unique values
0 missing
ATSC2vnumeric76 unique values
0 missing
SpMax8_Bh.i.numeric65 unique values
0 missing
SpMin3_Bh.e.numeric51 unique values
0 missing
ATSC3enumeric76 unique values
0 missing
ATSC4snumeric84 unique values
0 missing
ATSC5enumeric77 unique values
0 missing
SpMin3_Bh.s.numeric58 unique values
0 missing
SM03_EA.ri.numeric51 unique values
0 missing
SpMin8_Bh.s.numeric52 unique values
0 missing
JGI2numeric38 unique values
0 missing
SpMAD_AEA.ed.numeric47 unique values
0 missing
Eig03_EA.ed.numeric44 unique values
0 missing
SM12_AEA.dm.numeric44 unique values
0 missing
SpDiam_AEA.ri.numeric48 unique values
0 missing
PW2numeric39 unique values
0 missing
SpMAD_EA.ed.numeric54 unique values
0 missing
StsCnumeric25 unique values
0 missing
SpMin7_Bh.m.numeric71 unique values
0 missing
Eig01_AEA.ri.numeric45 unique values
0 missing
SpMax_AEA.ri.numeric45 unique values
0 missing
P_VSA_e_2numeric70 unique values
0 missing
P_VSA_m_2numeric72 unique values
0 missing
molecule_id (row identifier)nominal84 unique values
0 missing
P_VSA_i_2numeric70 unique values
0 missing
SpMin3_Bh.m.numeric59 unique values
0 missing
SpMin7_Bh.p.numeric63 unique values
0 missing
SpMin7_Bh.v.numeric65 unique values
0 missing
IVDEnumeric43 unique values
0 missing
JGI6numeric21 unique values
0 missing
CATS2D_08_LLnumeric11 unique values
0 missing
Eig03_AEA.ed.numeric36 unique values
0 missing
SM13_EA.ri.numeric67 unique values
0 missing
SM14_EA.ri.numeric67 unique values
0 missing
SM15_EA.ri.numeric68 unique values
0 missing
X5Anumeric17 unique values
0 missing
C.022numeric2 unique values
0 missing
nCspnumeric3 unique values
0 missing
nR.C.numeric2 unique values
0 missing
Show all 65 features

62 properties

NumberOfInstances
84
Number of instances (rows) of the dataset.
NumberOfFeatures
65
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
64
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
98.46
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
1.54
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-1.09
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
0.73
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.
Quartile1SkewnessOfNumericAtts
-0.41
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.18
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
-0.64
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
2.74
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
-0.1
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
0.47
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
0.66
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
9.7
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
0.44
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
1.52
Third quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
0.04
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
20.04
Mean of means among attributes of the numeric type.
ClassEntropy
Entropy of the target attribute values.
Dimensionality
0.77
Number of attributes divided by the number of instances.
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.
MajorityClassSize
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
37.79
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
206.25
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
5.39
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
93.28
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
0.97
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
0
Number of binary attributes.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.1
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
7.32
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.51
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.02
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-1.93
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.01
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
Show all 62 properties

12 tasks

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
2 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
0 runs
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2015
0 runs - estimation_procedure: 50 times Clustering
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