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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL208

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL208

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: CHEMBL208 (TID: 36), and it has 1731 rows and 102 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent FCFP 1024-bit Molecular Fingerprints which were generated from SMILES strings. Feature selection was applied to this dataset. The fingerprints were obtained using the Pipeline Pilot program, Dassault Systèmes BIOVIA. Generating Fingerprints do not usually require missing value imputation as all bits are generated.

104 features

pXC50 (target)numeric858 unique values
0 missing
molecule_id (row identifier)nominal1731 unique values
0 missing
FCFP4_1024b767numeric2 unique values
0 missing
FCFP4_1024b285numeric2 unique values
0 missing
FCFP4_1024b22numeric2 unique values
0 missing
FCFP4_1024b814numeric2 unique values
0 missing
FCFP4_1024b297numeric2 unique values
0 missing
FCFP4_1024b774numeric2 unique values
0 missing
FCFP4_1024b891numeric2 unique values
0 missing
FCFP4_1024b134numeric2 unique values
0 missing
FCFP4_1024b408numeric2 unique values
0 missing
FCFP4_1024b607numeric2 unique values
0 missing
FCFP4_1024b716numeric2 unique values
0 missing
FCFP4_1024b110numeric2 unique values
0 missing
FCFP4_1024b273numeric2 unique values
0 missing
FCFP4_1024b128numeric2 unique values
0 missing
FCFP4_1024b399numeric2 unique values
0 missing
FCFP4_1024b360numeric2 unique values
0 missing
FCFP4_1024b240numeric2 unique values
0 missing
FCFP4_1024b894numeric2 unique values
0 missing
FCFP4_1024b815numeric2 unique values
0 missing
FCFP4_1024b78numeric2 unique values
0 missing
FCFP4_1024b113numeric2 unique values
0 missing
FCFP4_1024b904numeric2 unique values
0 missing
FCFP4_1024b372numeric2 unique values
0 missing
FCFP4_1024b14numeric2 unique values
0 missing
FCFP4_1024b957numeric2 unique values
0 missing
FCFP4_1024b614numeric2 unique values
0 missing
FCFP4_1024b56numeric2 unique values
0 missing
FCFP4_1024b543numeric2 unique values
0 missing
FCFP4_1024b809numeric2 unique values
0 missing
FCFP4_1024b468numeric2 unique values
0 missing
FCFP4_1024b38numeric2 unique values
0 missing
FCFP4_1024b540numeric2 unique values
0 missing
FCFP4_1024b953numeric2 unique values
0 missing
FCFP4_1024b942numeric2 unique values
0 missing
FCFP4_1024b87numeric2 unique values
0 missing
FCFP4_1024b235numeric2 unique values
0 missing
FCFP4_1024b940numeric2 unique values
0 missing
FCFP4_1024b209numeric2 unique values
0 missing
FCFP4_1024b437numeric2 unique values
0 missing
FCFP4_1024b369numeric2 unique values
0 missing
FCFP4_1024b220numeric2 unique values
0 missing
FCFP4_1024b508numeric2 unique values
0 missing
FCFP4_1024b12numeric2 unique values
0 missing
FCFP4_1024b446numeric2 unique values
0 missing
FCFP4_1024b461numeric2 unique values
0 missing
FCFP4_1024b298numeric2 unique values
0 missing
FCFP4_1024b823numeric2 unique values
0 missing
FCFP4_1024b117numeric2 unique values
0 missing
FCFP4_1024b453numeric2 unique values
0 missing
FCFP4_1024b558numeric2 unique values
0 missing
FCFP4_1024b556numeric2 unique values
0 missing
FCFP4_1024b148numeric2 unique values
0 missing
FCFP4_1024b147numeric2 unique values
0 missing
FCFP4_1024b784numeric2 unique values
0 missing
FCFP4_1024b827numeric2 unique values
0 missing
FCFP4_1024b675numeric2 unique values
0 missing
FCFP4_1024b983numeric2 unique values
0 missing
FCFP4_1024b862numeric2 unique values
0 missing
FCFP4_1024b49numeric2 unique values
0 missing
FCFP4_1024b423numeric2 unique values
0 missing
FCFP4_1024b281numeric2 unique values
0 missing
FCFP4_1024b693numeric2 unique values
0 missing
FCFP4_1024b159numeric2 unique values
0 missing
FCFP4_1024b429numeric2 unique values
0 missing
FCFP4_1024b421numeric2 unique values
0 missing
FCFP4_1024b487numeric2 unique values
0 missing
FCFP4_1024b839numeric2 unique values
0 missing
FCFP4_1024b152numeric2 unique values
0 missing
FCFP4_1024b212numeric2 unique values
0 missing
FCFP4_1024b394numeric2 unique values
0 missing
FCFP4_1024b46numeric2 unique values
0 missing
FCFP4_1024b924numeric2 unique values
0 missing
FCFP4_1024b702numeric2 unique values
0 missing
FCFP4_1024b633numeric2 unique values
0 missing
FCFP4_1024b320numeric2 unique values
0 missing
FCFP4_1024b11numeric2 unique values
0 missing
FCFP4_1024b937numeric2 unique values
0 missing
FCFP4_1024b557numeric2 unique values
0 missing
FCFP4_1024b20numeric2 unique values
0 missing
FCFP4_1024b1022numeric2 unique values
0 missing
FCFP4_1024b533numeric2 unique values
0 missing
FCFP4_1024b768numeric2 unique values
0 missing
FCFP4_1024b109numeric2 unique values
0 missing
FCFP4_1024b39numeric2 unique values
0 missing
FCFP4_1024b1000numeric2 unique values
0 missing
FCFP4_1024b351numeric2 unique values
0 missing
FCFP4_1024b310numeric2 unique values
0 missing
FCFP4_1024b238numeric2 unique values
0 missing
FCFP4_1024b348numeric2 unique values
0 missing
FCFP4_1024b345numeric2 unique values
0 missing
FCFP4_1024b331numeric2 unique values
0 missing
FCFP4_1024b504numeric2 unique values
0 missing
FCFP4_1024b403numeric2 unique values
0 missing
FCFP4_1024b363numeric2 unique values
0 missing
FCFP4_1024b952numeric2 unique values
0 missing
FCFP4_1024b366numeric2 unique values
0 missing
FCFP4_1024b836numeric2 unique values
0 missing
FCFP4_1024b612numeric2 unique values
0 missing
FCFP4_1024b750numeric2 unique values
0 missing
FCFP4_1024b987numeric2 unique values
0 missing
FCFP4_1024b528numeric2 unique values
0 missing
FCFP4_1024b129numeric2 unique values
0 missing

62 properties

1731
Number of instances (rows) of the dataset.
104
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.
103
Number of numeric attributes.
1
Number of nominal attributes.
6.79
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.
39.53
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.
99.04
Percentage of numeric attributes.
0.12
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
0.03
Minimum skewness among attributes of the numeric type.
0.96
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
14.62
Maximum skewness among attributes of the numeric type.
0.07
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
6.44
Third quartile of skewness among attributes of the numeric type.
1.2
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
3.67
First quartile of kurtosis among attributes of the numeric type.
0.32
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.
0.02
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
26.08
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.
0.15
Mean of means among attributes of the numeric type.
2.38
First quartile of skewness among attributes of the numeric type.
-0.05
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.15
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.
0.06
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
11.43
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.
4.5
Mean skewness among attributes of the numeric type.
0.06
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
0.25
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.
3.66
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-2
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.24
Second quartile (Median) of standard deviation of attributes of the numeric type.
211.99
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.

12 tasks

1 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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