Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2111437

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2111437

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: CHEMBL2111437 (TID: 104952), and it has 50 rows and 154 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.

156 features

pXC50 (target)numeric38 unique values
0 missing
molecule_id (row identifier)nominal50 unique values
0 missing
FCFP4_1024b1numeric1 unique values
0 missing
FCFP4_1024b10numeric2 unique values
0 missing
FCFP4_1024b100numeric1 unique values
0 missing
FCFP4_1024b1000numeric1 unique values
0 missing
FCFP4_1024b1001numeric2 unique values
0 missing
FCFP4_1024b1002numeric1 unique values
0 missing
FCFP4_1024b1003numeric2 unique values
0 missing
FCFP4_1024b1004numeric1 unique values
0 missing
FCFP4_1024b1005numeric1 unique values
0 missing
FCFP4_1024b1006numeric1 unique values
0 missing
FCFP4_1024b1007numeric1 unique values
0 missing
FCFP4_1024b1008numeric1 unique values
0 missing
FCFP4_1024b1009numeric1 unique values
0 missing
FCFP4_1024b101numeric1 unique values
0 missing
FCFP4_1024b1010numeric1 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_1024b1018numeric2 unique values
0 missing
FCFP4_1024b1019numeric1 unique values
0 missing
FCFP4_1024b102numeric1 unique values
0 missing
FCFP4_1024b1020numeric2 unique values
0 missing
FCFP4_1024b1021numeric1 unique values
0 missing
FCFP4_1024b1022numeric1 unique values
0 missing
FCFP4_1024b1023numeric1 unique values
0 missing
FCFP4_1024b1024numeric1 unique values
0 missing
FCFP4_1024b103numeric2 unique values
0 missing
FCFP4_1024b104numeric2 unique values
0 missing
FCFP4_1024b105numeric1 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_1024b11numeric1 unique values
0 missing
FCFP4_1024b110numeric1 unique values
0 missing
FCFP4_1024b111numeric1 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_1024b116numeric1 unique values
0 missing
FCFP4_1024b117numeric1 unique values
0 missing
FCFP4_1024b118numeric2 unique values
0 missing
FCFP4_1024b119numeric1 unique values
0 missing
FCFP4_1024b12numeric1 unique values
0 missing
FCFP4_1024b120numeric1 unique values
0 missing
FCFP4_1024b121numeric2 unique values
0 missing
FCFP4_1024b122numeric2 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_1024b128numeric1 unique values
0 missing
FCFP4_1024b129numeric1 unique values
0 missing
FCFP4_1024b13numeric1 unique values
0 missing
FCFP4_1024b130numeric1 unique values
0 missing
FCFP4_1024b131numeric2 unique values
0 missing
FCFP4_1024b132numeric1 unique values
0 missing
FCFP4_1024b133numeric2 unique values
0 missing
FCFP4_1024b134numeric1 unique values
0 missing
FCFP4_1024b135numeric1 unique values
0 missing
FCFP4_1024b136numeric1 unique values
0 missing
FCFP4_1024b137numeric1 unique values
0 missing
FCFP4_1024b138numeric1 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_1024b142numeric1 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_1024b150numeric2 unique values
0 missing
FCFP4_1024b151numeric1 unique values
0 missing
FCFP4_1024b152numeric2 unique values
0 missing
FCFP4_1024b153numeric1 unique values
0 missing
FCFP4_1024b154numeric1 unique values
0 missing
FCFP4_1024b155numeric2 unique values
0 missing
FCFP4_1024b156numeric1 unique values
0 missing
FCFP4_1024b157numeric1 unique values
0 missing
FCFP4_1024b158numeric1 unique values
0 missing
FCFP4_1024b159numeric1 unique values
0 missing
FCFP4_1024b16numeric1 unique values
0 missing
FCFP4_1024b160numeric1 unique values
0 missing
FCFP4_1024b161numeric2 unique values
0 missing
FCFP4_1024b162numeric1 unique values
0 missing
FCFP4_1024b163numeric1 unique values
0 missing
FCFP4_1024b164numeric1 unique values
0 missing
FCFP4_1024b165numeric1 unique values
0 missing
FCFP4_1024b166numeric2 unique values
0 missing
FCFP4_1024b167numeric1 unique values
0 missing
FCFP4_1024b168numeric1 unique values
0 missing
FCFP4_1024b169numeric1 unique values
0 missing
FCFP4_1024b17numeric1 unique values
0 missing
FCFP4_1024b170numeric1 unique values
0 missing
FCFP4_1024b171numeric2 unique values
0 missing
FCFP4_1024b172numeric1 unique values
0 missing
FCFP4_1024b173numeric2 unique values
0 missing
FCFP4_1024b174numeric1 unique values
0 missing
FCFP4_1024b175numeric1 unique values
0 missing
FCFP4_1024b176numeric1 unique values
0 missing
FCFP4_1024b177numeric1 unique values
0 missing
FCFP4_1024b178numeric1 unique values
0 missing
FCFP4_1024b179numeric1 unique values
0 missing
FCFP4_1024b18numeric2 unique values
0 missing
FCFP4_1024b180numeric1 unique values
0 missing
FCFP4_1024b181numeric1 unique values
0 missing
FCFP4_1024b182numeric1 unique values
0 missing
FCFP4_1024b183numeric1 unique values
0 missing
FCFP4_1024b184numeric2 unique values
0 missing
FCFP4_1024b185numeric2 unique values
0 missing
FCFP4_1024b186numeric1 unique values
0 missing
FCFP4_1024b187numeric1 unique values
0 missing
FCFP4_1024b188numeric1 unique values
0 missing
FCFP4_1024b189numeric1 unique values
0 missing
FCFP4_1024b19numeric1 unique values
0 missing
FCFP4_1024b190numeric1 unique values
0 missing
FCFP4_1024b191numeric1 unique values
0 missing
FCFP4_1024b192numeric2 unique values
0 missing
FCFP4_1024b193numeric1 unique values
0 missing
FCFP4_1024b194numeric1 unique values
0 missing
FCFP4_1024b195numeric1 unique values
0 missing
FCFP4_1024b196numeric1 unique values
0 missing
FCFP4_1024b197numeric1 unique values
0 missing
FCFP4_1024b198numeric1 unique values
0 missing
FCFP4_1024b199numeric2 unique values
0 missing
FCFP4_1024b2numeric1 unique values
0 missing
FCFP4_1024b20numeric2 unique values
0 missing
FCFP4_1024b200numeric2 unique values
0 missing
FCFP4_1024b201numeric1 unique values
0 missing
FCFP4_1024b202numeric2 unique values
0 missing
FCFP4_1024b203numeric1 unique values
0 missing
FCFP4_1024b204numeric1 unique values
0 missing
FCFP4_1024b205numeric1 unique values
0 missing
FCFP4_1024b206numeric1 unique values
0 missing
FCFP4_1024b207numeric1 unique values
0 missing
FCFP4_1024b208numeric1 unique values
0 missing
FCFP4_1024b209numeric1 unique values
0 missing
FCFP4_1024b21numeric1 unique values
0 missing
FCFP4_1024b210numeric1 unique values
0 missing
FCFP4_1024b211numeric1 unique values
0 missing
FCFP4_1024b212numeric1 unique values
0 missing
FCFP4_1024b213numeric1 unique values
0 missing
FCFP4_1024b214numeric1 unique values
0 missing

62 properties

50
Number of instances (rows) of the dataset.
156
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.
155
Number of numeric attributes.
1
Number of nominal attributes.
17.73
Second quartile (Median) of kurtosis among attributes of the numeric type.
3.12
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.
3.78
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.
0.06
Mean standard deviation of attributes of the numeric type.
4.33
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
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-2.09
Minimum 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.
50
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
50
Third quartile of kurtosis among attributes of the numeric type.
6.17
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
99.36
Percentage of numeric attributes.
0
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-3.19
Minimum skewness among attributes of the numeric type.
0.64
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.
7.07
Third quartile of skewness among attributes of the numeric type.
7.07
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
3.97
First quartile of kurtosis among attributes of the numeric type.
0
Third quartile of standard deviation of attributes of the numeric type.
0.94
Maximum standard deviation of attributes of the numeric type.
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.
21.49
Mean kurtosis among attributes of the numeric type.
1.83
First quartile of skewness among attributes of the numeric type.
0.1
Mean of means among attributes of the numeric type.
0
First quartile of standard deviation of attributes of the numeric type.
-0.03
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.

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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