Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2798

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2798

deactivated ARFF Publicly available Visibility: public Uploaded 16-07-2016 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: CHEMBL2798 (TID: 10466), and it has 78 rows and 123 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.

125 features

pXC50 (target)numeric69 unique values
0 missing
molecule_id (row identifier)nominal78 unique values
0 missing
CATS2D_04_DLnumeric11 unique values
0 missing
CATS2D_05_DLnumeric9 unique values
0 missing
CATS2D_07_DLnumeric14 unique values
0 missing
MATS3pnumeric62 unique values
0 missing
CATS2D_07_ANnumeric2 unique values
0 missing
CATS2D_09_ANnumeric3 unique values
0 missing
Eig02_EA.bo.numeric26 unique values
0 missing
Eig06_EA.bo.numeric49 unique values
0 missing
GATS4enumeric66 unique values
0 missing
Hynumeric54 unique values
0 missing
N.071numeric2 unique values
0 missing
nABnumeric10 unique values
0 missing
nArCONR2numeric2 unique values
0 missing
nArNR2numeric2 unique values
0 missing
piPC04numeric62 unique values
0 missing
piPC05numeric63 unique values
0 missing
piPC06numeric65 unique values
0 missing
piPC07numeric66 unique values
0 missing
piPC08numeric65 unique values
0 missing
piPC09numeric68 unique values
0 missing
piPC10numeric69 unique values
0 missing
PJI2numeric12 unique values
0 missing
SaaNnumeric26 unique values
0 missing
SM04_EA.bo.numeric60 unique values
0 missing
SM06_EA.bo.numeric55 unique values
0 missing
SM12_AEA.ri.numeric26 unique values
0 missing
SpMax2_Bh.p.numeric32 unique values
0 missing
SpMax2_Bh.v.numeric32 unique values
0 missing
SpMin2_Bh.e.numeric20 unique values
0 missing
SpMin2_Bh.i.numeric20 unique values
0 missing
SpMin2_Bh.p.numeric28 unique values
0 missing
CATS2D_08_DLnumeric11 unique values
0 missing
CATS2D_09_LLnumeric22 unique values
0 missing
GATS3vnumeric59 unique values
0 missing
P_VSA_s_5numeric10 unique values
0 missing
AECCnumeric70 unique values
0 missing
HVcpxnumeric64 unique values
0 missing
IDEnumeric62 unique values
0 missing
P_VSA_p_3numeric57 unique values
0 missing
P_VSA_v_3numeric57 unique values
0 missing
GATS3inumeric62 unique values
0 missing
CATS2D_02_DAnumeric7 unique values
0 missing
Eig07_EA.bo.numeric48 unique values
0 missing
GATS3snumeric68 unique values
0 missing
MATS3vnumeric55 unique values
0 missing
piPC03numeric55 unique values
0 missing
CATS2D_06_DLnumeric13 unique values
0 missing
Eig05_EA.bo.numeric36 unique values
0 missing
GATS2pnumeric66 unique values
0 missing
GATS8inumeric59 unique values
0 missing
SM08_EA.bo.numeric51 unique values
0 missing
SM15_AEA.ri.numeric36 unique values
0 missing
SpMax2_Bh.m.numeric38 unique values
0 missing
P_VSA_LogP_2numeric58 unique values
0 missing
SpMax8_Bh.m.numeric68 unique values
0 missing
SpMin1_Bh.p.numeric24 unique values
0 missing
MSDnumeric70 unique values
0 missing
P_VSA_e_2numeric57 unique values
0 missing
PHInumeric61 unique values
0 missing
S2Knumeric62 unique values
0 missing
MATS8pnumeric59 unique values
0 missing
N.072numeric6 unique values
0 missing
JGI2numeric27 unique values
0 missing
CENTnumeric70 unique values
0 missing
Chi0_EA.ed.numeric69 unique values
0 missing
Chi1_EA.ed.numeric70 unique values
0 missing
Eig04_EA.dm.numeric23 unique values
0 missing
MDDDnumeric70 unique values
0 missing
ON1numeric48 unique values
0 missing
SpAD_EA.dm.numeric49 unique values
0 missing
SpMaxA_AEA.ed.numeric40 unique values
0 missing
SpMaxA_AEA.ri.numeric35 unique values
0 missing
SpMaxA_EAnumeric32 unique values
0 missing
SpMaxA_EA.ed.numeric40 unique values
0 missing
SpMaxA_EA.ri.numeric31 unique values
0 missing
SsssCHnumeric64 unique values
0 missing
VARnumeric59 unique values
0 missing
P_VSA_LogP_5numeric24 unique values
0 missing
NssNHnumeric6 unique values
0 missing
P_VSA_i_4numeric22 unique values
0 missing
S3Knumeric61 unique values
0 missing
ARRnumeric41 unique values
0 missing
C.numeric44 unique values
0 missing
CATS2D_03_DAnumeric6 unique values
0 missing
H.050numeric9 unique values
0 missing
nBMnumeric13 unique values
0 missing
nHDonnumeric9 unique values
0 missing
P_VSA_MR_6numeric41 unique values
0 missing
SpMAD_EA.bo.numeric58 unique values
0 missing
SpMAD_EA.dm.numeric63 unique values
0 missing
Ucnumeric13 unique values
0 missing
X2Avnumeric33 unique values
0 missing
X3Avnumeric21 unique values
0 missing
X4Avnumeric15 unique values
0 missing
X5Avnumeric11 unique values
0 missing
Eig01_AEA.dm.numeric24 unique values
0 missing
P_VSA_i_2numeric57 unique values
0 missing
SpDiam_AEA.dm.numeric24 unique values
0 missing
SpMax_AEA.dm.numeric24 unique values
0 missing
C.025numeric6 unique values
0 missing
CATS2D_02_NLnumeric2 unique values
0 missing
CATS2D_03_NLnumeric2 unique values
0 missing
CATS2D_04_AAnumeric5 unique values
0 missing
CATS2D_04_NLnumeric2 unique values
0 missing
CATS2D_05_NLnumeric2 unique values
0 missing
GATS4pnumeric58 unique values
0 missing
NaasNnumeric2 unique values
0 missing
nArCOOHnumeric2 unique values
0 missing
nCarnumeric10 unique values
0 missing
nImidazolesnumeric2 unique values
0 missing
SaasNnumeric8 unique values
0 missing
P_VSA_e_3numeric20 unique values
0 missing
SpMAD_AEA.ed.numeric48 unique values
0 missing
Eig01_EA.dm.numeric21 unique values
0 missing
Eig02_EA.dm.numeric27 unique values
0 missing
MATS3inumeric59 unique values
0 missing
SM12_EA.dm.numeric41 unique values
0 missing
SM13_EA.dm.numeric41 unique values
0 missing
SM14_EA.dm.numeric38 unique values
0 missing
SM15_EA.dm.numeric37 unique values
0 missing
SpDiam_EA.dm.numeric23 unique values
0 missing
SpMax_EA.dm.numeric21 unique values
0 missing
JGI4numeric16 unique values
0 missing

62 properties

78
Number of instances (rows) of the dataset.
125
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.
124
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.
1.6
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.74
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.
0
Mean skewness among attributes of the numeric type.
3.81
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
30
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.
-0.32
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.35
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.37
Second quartile (Median) of standard deviation of attributes of the numeric type.
24.59
Maximum kurtosis among attributes of the numeric type.
-1.54
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
6803.56
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.
6.37
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.
99.2
Percentage of numeric attributes.
9.91
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-3.72
Minimum skewness among attributes of the numeric type.
0.8
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
3.12
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.94
Third quartile of skewness among attributes of the numeric type.
3038.04
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.14
First quartile of kurtosis among attributes of the numeric type.
2.53
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.
0.55
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
3.34
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.
74.5
Mean of means among attributes of the numeric type.
-0.88
First quartile of skewness among attributes of the numeric type.
0.1
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.08
First quartile of standard deviation of attributes of the numeric type.

12 tasks

2 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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