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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1907603

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1907603

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: CHEMBL1907603 (TID: 104297), and it has 202 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)numeric170 unique values
0 missing
molecule_id (row identifier)nominal202 unique values
0 missing
FCFP4_1024b680numeric2 unique values
0 missing
FCFP4_1024b981numeric2 unique values
0 missing
FCFP4_1024b122numeric2 unique values
0 missing
FCFP4_1024b859numeric2 unique values
0 missing
FCFP4_1024b178numeric2 unique values
0 missing
FCFP4_1024b896numeric2 unique values
0 missing
FCFP4_1024b128numeric2 unique values
0 missing
FCFP4_1024b9numeric2 unique values
0 missing
FCFP4_1024b930numeric2 unique values
0 missing
FCFP4_1024b735numeric2 unique values
0 missing
FCFP4_1024b312numeric2 unique values
0 missing
FCFP4_1024b394numeric2 unique values
0 missing
FCFP4_1024b342numeric2 unique values
0 missing
FCFP4_1024b536numeric2 unique values
0 missing
FCFP4_1024b638numeric2 unique values
0 missing
FCFP4_1024b696numeric2 unique values
0 missing
FCFP4_1024b842numeric2 unique values
0 missing
FCFP4_1024b785numeric2 unique values
0 missing
FCFP4_1024b1numeric1 unique values
0 missing
FCFP4_1024b10numeric2 unique values
0 missing
FCFP4_1024b100numeric2 unique values
0 missing
FCFP4_1024b1000numeric1 unique values
0 missing
FCFP4_1024b1001numeric1 unique values
0 missing
FCFP4_1024b1002numeric2 unique values
0 missing
FCFP4_1024b1003numeric1 unique values
0 missing
FCFP4_1024b1004numeric2 unique values
0 missing
FCFP4_1024b1005numeric1 unique values
0 missing
FCFP4_1024b1006numeric2 unique values
0 missing
FCFP4_1024b1007numeric2 unique values
0 missing
FCFP4_1024b1008numeric1 unique values
0 missing
FCFP4_1024b1009numeric2 unique values
0 missing
FCFP4_1024b101numeric1 unique values
0 missing
FCFP4_1024b1010numeric2 unique values
0 missing
FCFP4_1024b1011numeric1 unique values
0 missing
FCFP4_1024b1012numeric1 unique values
0 missing
FCFP4_1024b1013numeric1 unique values
0 missing
FCFP4_1024b1014numeric1 unique values
0 missing
FCFP4_1024b1015numeric1 unique values
0 missing
FCFP4_1024b1016numeric1 unique values
0 missing
FCFP4_1024b1017numeric1 unique values
0 missing
FCFP4_1024b1018numeric1 unique values
0 missing
FCFP4_1024b1019numeric2 unique values
0 missing
FCFP4_1024b102numeric2 unique values
0 missing
FCFP4_1024b1020numeric2 unique values
0 missing
FCFP4_1024b1021numeric1 unique values
0 missing
FCFP4_1024b1022numeric2 unique values
0 missing
FCFP4_1024b1023numeric1 unique values
0 missing
FCFP4_1024b1024numeric1 unique values
0 missing
FCFP4_1024b103numeric2 unique values
0 missing
FCFP4_1024b104numeric1 unique values
0 missing
FCFP4_1024b105numeric2 unique values
0 missing
FCFP4_1024b106numeric1 unique values
0 missing
FCFP4_1024b107numeric2 unique values
0 missing
FCFP4_1024b108numeric2 unique values
0 missing
FCFP4_1024b109numeric1 unique values
0 missing
FCFP4_1024b11numeric2 unique values
0 missing
FCFP4_1024b110numeric2 unique values
0 missing
FCFP4_1024b111numeric2 unique values
0 missing
FCFP4_1024b112numeric1 unique values
0 missing
FCFP4_1024b113numeric2 unique values
0 missing
FCFP4_1024b114numeric2 unique values
0 missing
FCFP4_1024b115numeric1 unique values
0 missing
FCFP4_1024b116numeric2 unique values
0 missing
FCFP4_1024b117numeric1 unique values
0 missing
FCFP4_1024b118numeric2 unique values
0 missing
FCFP4_1024b119numeric1 unique values
0 missing
FCFP4_1024b12numeric2 unique values
0 missing
FCFP4_1024b120numeric2 unique values
0 missing
FCFP4_1024b121numeric2 unique values
0 missing
FCFP4_1024b123numeric2 unique values
0 missing
FCFP4_1024b124numeric1 unique values
0 missing
FCFP4_1024b125numeric1 unique values
0 missing
FCFP4_1024b126numeric1 unique values
0 missing
FCFP4_1024b127numeric1 unique values
0 missing
FCFP4_1024b129numeric2 unique values
0 missing
FCFP4_1024b13numeric1 unique values
0 missing
FCFP4_1024b130numeric1 unique values
0 missing
FCFP4_1024b131numeric1 unique values
0 missing
FCFP4_1024b132numeric1 unique values
0 missing
FCFP4_1024b133numeric2 unique values
0 missing
FCFP4_1024b134numeric1 unique values
0 missing
FCFP4_1024b135numeric2 unique values
0 missing
FCFP4_1024b136numeric1 unique values
0 missing
FCFP4_1024b137numeric2 unique values
0 missing
FCFP4_1024b138numeric2 unique values
0 missing
FCFP4_1024b139numeric2 unique values
0 missing
FCFP4_1024b14numeric1 unique values
0 missing
FCFP4_1024b140numeric1 unique values
0 missing
FCFP4_1024b141numeric1 unique values
0 missing
FCFP4_1024b142numeric2 unique values
0 missing
FCFP4_1024b143numeric1 unique values
0 missing
FCFP4_1024b144numeric1 unique values
0 missing
FCFP4_1024b145numeric1 unique values
0 missing
FCFP4_1024b146numeric1 unique values
0 missing
FCFP4_1024b147numeric1 unique values
0 missing
FCFP4_1024b148numeric1 unique values
0 missing
FCFP4_1024b149numeric1 unique values
0 missing
FCFP4_1024b15numeric1 unique values
0 missing
FCFP4_1024b150numeric1 unique values
0 missing
FCFP4_1024b151numeric1 unique values
0 missing
FCFP4_1024b152numeric2 unique values
0 missing
FCFP4_1024b153numeric1 unique values
0 missing

62 properties

202
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.
99.04
Percentage of numeric attributes.
0.05
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.
0.96
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.
-0.03
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
8.55
Third quartile of skewness among attributes of the numeric type.
14.21
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
5.78
First quartile of kurtosis among attributes of the numeric type.
0.22
Third quartile of standard deviation of attributes of the numeric type.
1.27
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
First quartile of means 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.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
52.57
Mean kurtosis among attributes of the numeric type.
2.78
First quartile of skewness among attributes of the numeric type.
0.11
Mean of means among attributes of the numeric type.
0
First quartile of standard deviation of attributes of the numeric type.
-0.01
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among 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.
17.96
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.51
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0
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.
5.98
Mean skewness among 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.
0.12
Mean standard deviation of attributes of the numeric type.
4.45
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0
Percentage of binary attributes.
0.07
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.56
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
202
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
72.58
Third quartile of kurtosis among attributes of the numeric type.
6.68
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.

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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