Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1741217

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1741217

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: CHEMBL1741217 (TID: 104013), and it has 1001 rows and 70 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.

72 features

pXC50 (target)numeric621 unique values
0 missing
molecule_id (row identifier)nominal1001 unique values
0 missing
nN.numeric2 unique values
0 missing
SpMax2_Bh.s.numeric432 unique values
0 missing
SsSHnumeric183 unique values
0 missing
P_VSA_s_3numeric910 unique values
0 missing
Psi_e_Anumeric596 unique values
0 missing
Psi_i_Anumeric596 unique values
0 missing
MATS1pnumeric313 unique values
0 missing
NsSHnumeric3 unique values
0 missing
S.106numeric3 unique values
0 missing
AMWnumeric813 unique values
0 missing
MATS1mnumeric290 unique values
0 missing
TPSA.Tot.numeric635 unique values
0 missing
DELSnumeric987 unique values
0 missing
SAaccnumeric581 unique values
0 missing
GATS1mnumeric428 unique values
0 missing
Eig04_AEA.dm.numeric709 unique values
0 missing
CATS2D_02_PLnumeric6 unique values
0 missing
O.058numeric6 unique values
0 missing
P_VSA_v_2numeric622 unique values
0 missing
SpMax4_Bh.s.numeric626 unique values
0 missing
P_VSA_p_2numeric582 unique values
0 missing
N.079numeric2 unique values
0 missing
N.072numeric5 unique values
0 missing
SpMax3_Bh.s.numeric528 unique values
0 missing
H.numeric237 unique values
0 missing
Eta_epsi_Anumeric245 unique values
0 missing
SaasNnumeric294 unique values
0 missing
Mvnumeric218 unique values
0 missing
SdOnumeric632 unique values
0 missing
P_VSA_e_5numeric144 unique values
0 missing
GATS2snumeric475 unique values
0 missing
AACnumeric541 unique values
0 missing
IC0numeric541 unique values
0 missing
MAXDNnumeric813 unique values
0 missing
ATSC3snumeric996 unique values
0 missing
P_VSA_m_3numeric184 unique values
0 missing
NaasNnumeric3 unique values
0 missing
Eig05_EA.ed.numeric840 unique values
0 missing
SM14_AEA.dm.numeric840 unique values
0 missing
SpMax1_Bh.s.numeric256 unique values
0 missing
P_VSA_s_6numeric538 unique values
0 missing
SpDiam_AEA.dm.numeric489 unique values
0 missing
C.040numeric6 unique values
0 missing
SpMax1_Bh.m.numeric418 unique values
0 missing
GATS1snumeric453 unique values
0 missing
nNqnumeric2 unique values
0 missing
NssssN.numeric2 unique values
0 missing
SssssN.numeric57 unique values
0 missing
Eig01_AEA.dm.numeric477 unique values
0 missing
SpMax_AEA.dm.numeric477 unique values
0 missing
SdssCnumeric572 unique values
0 missing
Eig05_AEA.dm.numeric721 unique values
0 missing
NdOnumeric8 unique values
0 missing
ZM2Madnumeric978 unique values
0 missing
Mpnumeric210 unique values
0 missing
Eig02_EA.dm.numeric191 unique values
0 missing
SIC0numeric240 unique values
0 missing
O.numeric127 unique values
0 missing
Menumeric97 unique values
0 missing
Eig07_AEA.dm.numeric718 unique values
0 missing
Eig05_AEA.ed.numeric714 unique values
0 missing
nHAccnumeric14 unique values
0 missing
GATS1vnumeric444 unique values
0 missing
Eig06_AEA.dm.numeric747 unique values
0 missing
MATS1vnumeric197 unique values
0 missing
CATS2D_02_DAnumeric7 unique values
0 missing
ATS2mnumeric629 unique values
0 missing
ZM1Madnumeric950 unique values
0 missing
BIC0numeric218 unique values
0 missing
ATSC4snumeric998 unique values
0 missing

62 properties

1001
Number of instances (rows) of the dataset.
72
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.
71
Number of numeric attributes.
1
Number of nominal attributes.
Third quartile of entropy among attributes.
14.14
Maximum kurtosis among attributes of the numeric type.
-0.09
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
1.8
Third quartile of kurtosis among attributes of the numeric type.
174.45
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.
6.89
Third quartile of means 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.
98.61
Percentage of numeric 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.
-0.75
Minimum skewness among attributes of the numeric type.
1.39
Percentage of nominal attributes.
1.25
Third quartile of skewness among attributes of the numeric type.
3.94
Maximum skewness among attributes of the numeric type.
0.02
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.85
Third quartile of standard deviation of attributes of the numeric type.
50.88
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.19
First quartile of kurtosis among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
0.65
First quartile of means among attributes of the numeric type.
2.14
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.
17.01
Mean of means among attributes of the numeric type.
0.28
First quartile of skewness among attributes of the numeric type.
0.5
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.25
First quartile of standard deviation of attributes of the numeric type.
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.
0.07
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.99
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.
0.83
Mean skewness among attributes of the numeric type.
2.19
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
7.76
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.
0.59
Second quartile (Median) of skewness among attributes of the numeric type.
0.66
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.76
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.

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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