Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3771

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3771

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 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: CHEMBL3771 (TID: 10450), and it has 214 rows and 64 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.

66 features

pXC50 (target)numeric128 unique values
0 missing
molecule_id (row identifier)nominal214 unique values
0 missing
PCRnumeric131 unique values
0 missing
P_VSA_LogP_3numeric62 unique values
0 missing
CATS2D_02_LLnumeric30 unique values
0 missing
nBnznumeric5 unique values
0 missing
SpMin1_Bh.m.numeric86 unique values
0 missing
nCb.numeric10 unique values
0 missing
nCarnumeric17 unique values
0 missing
C.024numeric16 unique values
0 missing
NaaCHnumeric17 unique values
0 missing
CATS2D_08_LLnumeric24 unique values
0 missing
nR06numeric7 unique values
0 missing
CATS2D_03_LLnumeric27 unique values
0 missing
C.016numeric3 unique values
0 missing
NdsCHnumeric3 unique values
0 missing
SdsCHnumeric59 unique values
0 missing
SpMAD_AEA.dm.numeric117 unique values
0 missing
nABnumeric13 unique values
0 missing
SIC5numeric93 unique values
0 missing
piPC03numeric141 unique values
0 missing
SaaCHnumeric194 unique values
0 missing
SM05_EA.bo.numeric153 unique values
0 missing
P_VSA_LogP_5numeric110 unique values
0 missing
CATS2D_01_LLnumeric24 unique values
0 missing
SM03_EA.bo.numeric85 unique values
0 missing
piPC02numeric115 unique values
0 missing
SM02_EA.bo.numeric115 unique values
0 missing
CATS2D_05_DLnumeric7 unique values
0 missing
Eig05_EA.bo.numeric159 unique values
0 missing
SM15_AEA.ri.numeric159 unique values
0 missing
ARRnumeric88 unique values
0 missing
BIC4numeric85 unique values
0 missing
C.025numeric9 unique values
0 missing
SM04_EA.bo.numeric149 unique values
0 missing
H.051numeric9 unique values
0 missing
CIC4numeric147 unique values
0 missing
X.numeric28 unique values
0 missing
Eig04_EA.bo.numeric150 unique values
0 missing
SM14_AEA.ri.numeric150 unique values
0 missing
ZM2MulPernumeric198 unique values
0 missing
ZM2Pernumeric199 unique values
0 missing
ZM2Vnumeric144 unique values
0 missing
Eig03_AEA.bo.numeric140 unique values
0 missing
piPC04numeric154 unique values
0 missing
SM04_AEA.bo.numeric154 unique values
0 missing
BLTA96numeric131 unique values
0 missing
BLTD48numeric131 unique values
0 missing
BLTF96numeric129 unique values
0 missing
MLOGPnumeric162 unique values
0 missing
MLOGP2numeric165 unique values
0 missing
nBMnumeric26 unique values
0 missing
Ucnumeric26 unique values
0 missing
CIC5numeric146 unique values
0 missing
P_VSA_MR_6numeric133 unique values
0 missing
P_VSA_s_4numeric110 unique values
0 missing
SM07_AEA.bo.numeric164 unique values
0 missing
SM03_AEA.bo.numeric139 unique values
0 missing
Eta_betanumeric93 unique values
0 missing
MATS1snumeric103 unique values
0 missing
SM06_AEA.bo.numeric153 unique values
0 missing
SM08_AEA.bo.numeric159 unique values
0 missing
P_VSA_i_2numeric165 unique values
0 missing
Mvnumeric94 unique values
0 missing
JGI5numeric26 unique values
0 missing
SpAD_EA.bo.numeric175 unique values
0 missing

62 properties

214
Number of instances (rows) of the dataset.
66
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.
65
Number of numeric attributes.
1
Number of nominal attributes.
10.83
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.13
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-0.98
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
1.01
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-4.09
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
145.76
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
33.89
Third quartile of kurtosis among attributes of the numeric type.
712.39
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.48
Percentage of numeric attributes.
11.71
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-11
Minimum skewness among attributes of the numeric type.
1.52
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
0.01
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.64
Third quartile of skewness among attributes of the numeric type.
2.78
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.3
First quartile of kurtosis among attributes of the numeric type.
5.98
Third quartile of standard deviation of attributes of the numeric type.
186.82
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
1.27
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
23.56
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.
37.19
Mean of means among attributes of the numeric type.
-4.16
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.47
First quartile of standard deviation of attributes of the numeric type.
-0.08
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.
1.5
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.31
Number of attributes divided by the number of instances.
-1.73
Mean skewness among attributes of the numeric type.
4.81
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.

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
Define a new task