Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5306

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5306

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 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: CHEMBL5306 (TID: 101152), and it has 101 rows and 119 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.

121 features

pXC50 (target)numeric85 unique values
0 missing
molecule_id (row identifier)nominal101 unique values
0 missing
H.numeric45 unique values
0 missing
BIC1numeric60 unique values
0 missing
SIC1numeric64 unique values
0 missing
CATS2D_04_DDnumeric2 unique values
0 missing
GATS1mnumeric60 unique values
0 missing
AMWnumeric65 unique values
0 missing
P_VSA_e_2numeric75 unique values
0 missing
P_VSA_i_2numeric75 unique values
0 missing
P_VSA_p_3numeric75 unique values
0 missing
P_VSA_v_3numeric75 unique values
0 missing
MATS6inumeric61 unique values
0 missing
GATS1vnumeric62 unique values
0 missing
nOHsnumeric5 unique values
0 missing
GATS1pnumeric66 unique values
0 missing
MATS7snumeric66 unique values
0 missing
Eta_betaP_Anumeric40 unique values
0 missing
PDInumeric57 unique values
0 missing
piPC07numeric66 unique values
0 missing
BLTA96numeric60 unique values
0 missing
BLTD48numeric62 unique values
0 missing
BLTF96numeric59 unique values
0 missing
MLOGPnumeric62 unique values
0 missing
MLOGP2numeric62 unique values
0 missing
SpMax1_Bh.m.numeric41 unique values
0 missing
ALOGPnumeric86 unique values
0 missing
ALOGP2numeric87 unique values
0 missing
N.numeric26 unique values
0 missing
SpMax1_Bh.v.numeric44 unique values
0 missing
Eta_alpha_Anumeric26 unique values
0 missing
P_VSA_m_2numeric75 unique values
0 missing
piPC04numeric56 unique values
0 missing
GATS2pnumeric68 unique values
0 missing
SaasCnumeric38 unique values
0 missing
CATS2D_04_DAnumeric4 unique values
0 missing
MATS2snumeric66 unique values
0 missing
CATS2D_09_DLnumeric17 unique values
0 missing
CATS2D_03_DLnumeric13 unique values
0 missing
CATS2D_07_DAnumeric8 unique values
0 missing
TPSA.NO.numeric35 unique values
0 missing
TPSA.Tot.numeric35 unique values
0 missing
piPC09numeric66 unique values
0 missing
JGI4numeric16 unique values
0 missing
O.numeric41 unique values
0 missing
Psi_e_Anumeric76 unique values
0 missing
Psi_i_Anumeric76 unique values
0 missing
PCDnumeric48 unique values
0 missing
PCRnumeric37 unique values
0 missing
ATSC3snumeric89 unique values
0 missing
MATS6mnumeric59 unique values
0 missing
SM06_EA.bo.numeric72 unique values
0 missing
piPC08numeric69 unique values
0 missing
CATS2D_05_DLnumeric13 unique values
0 missing
JGI1numeric58 unique values
0 missing
BIC4numeric50 unique values
0 missing
ATSC8snumeric89 unique values
0 missing
SpMax4_Bh.s.numeric24 unique values
0 missing
P_VSA_p_2numeric36 unique values
0 missing
P_VSA_v_2numeric39 unique values
0 missing
SAaccnumeric39 unique values
0 missing
SpMax5_Bh.s.numeric25 unique values
0 missing
SpMin2_Bh.i.numeric27 unique values
0 missing
P_VSA_s_3numeric55 unique values
0 missing
Eig04_AEA.dm.numeric42 unique values
0 missing
ATSC6snumeric89 unique values
0 missing
CATS2D_06_DLnumeric13 unique values
0 missing
CATS2D_08_DLnumeric13 unique values
0 missing
SpMax3_Bh.p.numeric35 unique values
0 missing
SpMax3_Bh.v.numeric41 unique values
0 missing
CATS2D_05_DAnumeric8 unique values
0 missing
Minumeric17 unique values
0 missing
AACnumeric58 unique values
0 missing
AECCnumeric65 unique values
0 missing
AMRnumeric87 unique values
0 missing
ARRnumeric23 unique values
0 missing
ATS1enumeric69 unique values
0 missing
ATS1inumeric67 unique values
0 missing
ATS1mnumeric70 unique values
0 missing
ATS1pnumeric66 unique values
0 missing
ATS1snumeric72 unique values
0 missing
ATS1vnumeric69 unique values
0 missing
ATS2enumeric70 unique values
0 missing
ATS2inumeric72 unique values
0 missing
ATS2mnumeric75 unique values
0 missing
ATS2pnumeric79 unique values
0 missing
ATS2snumeric80 unique values
0 missing
ATS2vnumeric78 unique values
0 missing
ATS3enumeric78 unique values
0 missing
ATS3inumeric75 unique values
0 missing
ATS3mnumeric83 unique values
0 missing
ATS3pnumeric79 unique values
0 missing
ATS3snumeric79 unique values
0 missing
ATS3vnumeric78 unique values
0 missing
ATS4enumeric82 unique values
0 missing
ATS4inumeric73 unique values
0 missing
ATS4mnumeric82 unique values
0 missing
ATS4pnumeric82 unique values
0 missing
ATS4snumeric75 unique values
0 missing
ATS4vnumeric82 unique values
0 missing
ATS5enumeric81 unique values
0 missing
ATS5inumeric83 unique values
0 missing
ATS5mnumeric80 unique values
0 missing
ATS5pnumeric79 unique values
0 missing
ATS5snumeric77 unique values
0 missing
ATS5vnumeric77 unique values
0 missing
ATS6enumeric83 unique values
0 missing
ATS6inumeric77 unique values
0 missing
ATS6mnumeric84 unique values
0 missing
ATS6pnumeric76 unique values
0 missing
ATS6snumeric80 unique values
0 missing
ATS6vnumeric79 unique values
0 missing
ATS7enumeric77 unique values
0 missing
ATS7inumeric73 unique values
0 missing
ATS7mnumeric82 unique values
0 missing
ATS7pnumeric78 unique values
0 missing
ATS7snumeric83 unique values
0 missing
ATS7vnumeric80 unique values
0 missing
ATS8enumeric81 unique values
0 missing
ATS8inumeric78 unique values
0 missing
ATS8mnumeric77 unique values
0 missing

62 properties

101
Number of instances (rows) of the dataset.
121
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.
120
Number of numeric attributes.
1
Number of nominal attributes.
9.6
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.
-0.61
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-1.97
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.36
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-2.5
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
7.39
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
0.28
Third quartile of kurtosis among attributes of the numeric type.
372.68
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
99.17
Percentage of numeric attributes.
6.93
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.17
Minimum skewness among attributes of the numeric type.
0.83
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
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.55
Third quartile of skewness among attributes of the numeric type.
2.98
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.28
First quartile of kurtosis among attributes of the numeric type.
1.8
Third quartile of standard deviation of attributes of the numeric type.
170.54
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
2.25
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
-0.31
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.
30.87
Mean of means among attributes of the numeric type.
-0.84
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.19
First quartile of standard deviation of attributes of the numeric type.
0.22
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.
-0.71
Second quartile (Median) of kurtosis among attributes of the numeric type.
1.2
Number of attributes divided by the number of instances.
-0.24
Mean skewness among attributes of the numeric type.
5.07
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
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