Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2203

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2203

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: CHEMBL2203 (TID: 11061), and it has 291 rows and 129 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.

131 features

pXC50 (target)numeric121 unique values
0 missing
molecule_id (row identifier)nominal291 unique values
0 missing
SpMax4_Bh.v.numeric134 unique values
0 missing
GATS4inumeric196 unique values
0 missing
X.numeric25 unique values
0 missing
Eig06_EA.ed.numeric167 unique values
0 missing
SM15_AEA.dm.numeric167 unique values
0 missing
nXnumeric6 unique values
0 missing
Eig06_AEA.ed.numeric154 unique values
0 missing
SsFnumeric100 unique values
0 missing
Qindexnumeric23 unique values
0 missing
SpMax1_Bh.s.numeric27 unique values
0 missing
nFnumeric5 unique values
0 missing
NsFnumeric5 unique values
0 missing
P_VSA_e_6numeric5 unique values
0 missing
MSDnumeric193 unique values
0 missing
HVcpxnumeric177 unique values
0 missing
Eig06_AEA.ri.numeric186 unique values
0 missing
SpMAD_AEA.ri.numeric82 unique values
0 missing
Eig06_EAnumeric157 unique values
0 missing
SM14_AEA.bo.numeric157 unique values
0 missing
SpMax4_Bh.e.numeric125 unique values
0 missing
IDEnumeric161 unique values
0 missing
SpMAD_EAnumeric74 unique values
0 missing
GATS6mnumeric197 unique values
0 missing
SpMin4_Bh.i.numeric124 unique values
0 missing
NRSnumeric5 unique values
0 missing
GATS1snumeric138 unique values
0 missing
P_VSA_LogP_5numeric141 unique values
0 missing
PW2numeric48 unique values
0 missing
SpMax4_Bh.m.numeric140 unique values
0 missing
Eig06_EA.ri.numeric191 unique values
0 missing
MDDDnumeric199 unique values
0 missing
nArXnumeric4 unique values
0 missing
Eig07_EA.ed.numeric173 unique values
0 missing
SM02_AEA.ri.numeric173 unique values
0 missing
GATS6enumeric232 unique values
0 missing
LOCnumeric122 unique values
0 missing
AECCnumeric185 unique values
0 missing
MATS6mnumeric170 unique values
0 missing
CATS2D_08_LLnumeric34 unique values
0 missing
GATS1enumeric165 unique values
0 missing
GATS1mnumeric160 unique values
0 missing
C.002numeric12 unique values
0 missing
SsssCHnumeric202 unique values
0 missing
SpMin4_Bh.e.numeric121 unique values
0 missing
MATS7inumeric160 unique values
0 missing
BLTA96numeric157 unique values
0 missing
BLTD48numeric155 unique values
0 missing
BLTF96numeric149 unique values
0 missing
MLOGP2numeric199 unique values
0 missing
SpMax4_Bh.i.numeric130 unique values
0 missing
SpMax4_Bh.p.numeric140 unique values
0 missing
DECCnumeric178 unique values
0 missing
GATS6snumeric242 unique values
0 missing
F.084numeric3 unique values
0 missing
MATS6enumeric182 unique values
0 missing
SpMin2_Bh.p.numeric71 unique values
0 missing
SpMax2_Bh.m.numeric99 unique values
0 missing
MATS3mnumeric147 unique values
0 missing
Eig06_AEA.bo.numeric162 unique values
0 missing
GATS4snumeric221 unique values
0 missing
GATS5enumeric239 unique values
0 missing
GATS5snumeric231 unique values
0 missing
P_VSA_e_5numeric30 unique values
0 missing
CATS2D_04_DLnumeric15 unique values
0 missing
Eta_betaS_Anumeric74 unique values
0 missing
nCICnumeric7 unique values
0 missing
PJI2numeric15 unique values
0 missing
D.Dtr06numeric199 unique values
0 missing
ATSC1enumeric106 unique values
0 missing
ATS8enumeric250 unique values
0 missing
ATS8inumeric249 unique values
0 missing
MLOGPnumeric194 unique values
0 missing
P_VSA_LogP_6numeric29 unique values
0 missing
Yindexnumeric143 unique values
0 missing
SpMax6_Bh.p.numeric119 unique values
0 missing
piIDnumeric191 unique values
0 missing
SpMAD_AEA.bo.numeric90 unique values
0 missing
P_VSA_LogP_2numeric108 unique values
0 missing
X1Anumeric39 unique values
0 missing
CATS2D_01_LLnumeric25 unique values
0 missing
NNRSnumeric9 unique values
0 missing
RCInumeric18 unique values
0 missing
RFDnumeric18 unique values
0 missing
N.068numeric3 unique values
0 missing
nRNR2numeric3 unique values
0 missing
C.016numeric2 unique values
0 missing
NdsCHnumeric2 unique values
0 missing
nR.Csnumeric3 unique values
0 missing
SdsCHnumeric29 unique values
0 missing
X5Avnumeric26 unique values
0 missing
MATS2pnumeric159 unique values
0 missing
Chi1_EA.dm.numeric228 unique values
0 missing
NssCH2numeric14 unique values
0 missing
SpMin3_Bh.s.numeric130 unique values
0 missing
nR06numeric5 unique values
0 missing
SpMaxA_EA.dm.numeric61 unique values
0 missing
MATS3vnumeric136 unique values
0 missing
JGI3numeric33 unique values
0 missing
GATS6inumeric171 unique values
0 missing
ATS7enumeric240 unique values
0 missing
CATS2D_07_LLnumeric30 unique values
0 missing
O.057numeric4 unique values
0 missing
X3Avnumeric54 unique values
0 missing
SpMin2_Bh.s.numeric116 unique values
0 missing
SpMAD_EA.ed.numeric185 unique values
0 missing
SpMax2_Bh.i.numeric79 unique values
0 missing
Vindexnumeric89 unique values
0 missing
SpMin2_Bh.v.numeric72 unique values
0 missing
CATS2D_07_DDnumeric5 unique values
0 missing
X4Avnumeric37 unique values
0 missing
piPC09numeric199 unique values
0 missing
N.numeric67 unique values
0 missing
JGI1numeric79 unique values
0 missing
GATS4mnumeric170 unique values
0 missing
MATS1enumeric142 unique values
0 missing
GATS2mnumeric158 unique values
0 missing
X2Avnumeric67 unique values
0 missing
ALOGP2numeric237 unique values
0 missing
SpMax6_Bh.v.numeric123 unique values
0 missing
piPC03numeric117 unique values
0 missing
MATS6snumeric169 unique values
0 missing
Xindexnumeric101 unique values
0 missing
ARRnumeric64 unique values
0 missing
nArOHnumeric2 unique values
0 missing
CATS2D_09_LLnumeric37 unique values
0 missing
CATS2D_05_DLnumeric18 unique values
0 missing
MATS7pnumeric157 unique values
0 missing
ATSC2enumeric172 unique values
0 missing
SaaNnumeric98 unique values
0 missing

62 properties

291
Number of instances (rows) of the dataset.
131
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.
130
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.
0.45
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
1.63
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.
1.21
Mean skewness among attributes of the numeric type.
1.47
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
5.43
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.
0.48
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.23
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.25
Second quartile (Median) of standard deviation of attributes of the numeric type.
135.33
Maximum kurtosis among attributes of the numeric type.
-4.12
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
410.33
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.
4.3
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.
99.24
Percentage of numeric attributes.
4.92
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-7.78
Minimum skewness among attributes of the numeric type.
0.76
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
11.52
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.82
Third quartile of skewness among attributes of the numeric type.
285.85
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.2
First quartile of kurtosis among attributes of the numeric type.
1.04
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.
0.4
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
11.16
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.
7.68
Mean of means among attributes of the numeric type.
-0.09
First quartile of skewness among attributes of the numeric type.
-0.03
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.07
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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