Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1821

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1821

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: CHEMBL1821 (TID: 214), and it has 770 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)numeric512 unique values
0 missing
molecule_id (row identifier)nominal770 unique values
0 missing
FCFP4_1024b913numeric2 unique values
0 missing
FCFP4_1024b707numeric2 unique values
0 missing
FCFP4_1024b116numeric2 unique values
0 missing
FCFP4_1024b851numeric2 unique values
0 missing
FCFP4_1024b621numeric2 unique values
0 missing
FCFP4_1024b367numeric2 unique values
0 missing
FCFP4_1024b429numeric2 unique values
0 missing
FCFP4_1024b764numeric2 unique values
0 missing
FCFP4_1024b79numeric2 unique values
0 missing
FCFP4_1024b283numeric2 unique values
0 missing
FCFP4_1024b107numeric2 unique values
0 missing
FCFP4_1024b869numeric2 unique values
0 missing
FCFP4_1024b375numeric2 unique values
0 missing
FCFP4_1024b524numeric2 unique values
0 missing
FCFP4_1024b352numeric2 unique values
0 missing
FCFP4_1024b587numeric2 unique values
0 missing
FCFP4_1024b349numeric2 unique values
0 missing
FCFP4_1024b208numeric2 unique values
0 missing
FCFP4_1024b911numeric2 unique values
0 missing
FCFP4_1024b25numeric2 unique values
0 missing
FCFP4_1024b17numeric2 unique values
0 missing
FCFP4_1024b622numeric2 unique values
0 missing
FCFP4_1024b671numeric2 unique values
0 missing
FCFP4_1024b891numeric2 unique values
0 missing
FCFP4_1024b424numeric2 unique values
0 missing
FCFP4_1024b972numeric2 unique values
0 missing
FCFP4_1024b202numeric2 unique values
0 missing
FCFP4_1024b610numeric2 unique values
0 missing
FCFP4_1024b619numeric2 unique values
0 missing
FCFP4_1024b616numeric2 unique values
0 missing
FCFP4_1024b694numeric2 unique values
0 missing
FCFP4_1024b738numeric2 unique values
0 missing
FCFP4_1024b563numeric2 unique values
0 missing
FCFP4_1024b825numeric2 unique values
0 missing
FCFP4_1024b219numeric2 unique values
0 missing
FCFP4_1024b176numeric2 unique values
0 missing
FCFP4_1024b553numeric2 unique values
0 missing
FCFP4_1024b124numeric2 unique values
0 missing
FCFP4_1024b151numeric2 unique values
0 missing
FCFP4_1024b569numeric2 unique values
0 missing
FCFP4_1024b734numeric2 unique values
0 missing
FCFP4_1024b736numeric2 unique values
0 missing
FCFP4_1024b787numeric2 unique values
0 missing
FCFP4_1024b705numeric2 unique values
0 missing
FCFP4_1024b381numeric2 unique values
0 missing
FCFP4_1024b396numeric2 unique values
0 missing
FCFP4_1024b313numeric2 unique values
0 missing
FCFP4_1024b715numeric2 unique values
0 missing
FCFP4_1024b842numeric2 unique values
0 missing
FCFP4_1024b150numeric2 unique values
0 missing
FCFP4_1024b1numeric1 unique values
0 missing
FCFP4_1024b10numeric2 unique values
0 missing
FCFP4_1024b100numeric2 unique values
0 missing
FCFP4_1024b1000numeric2 unique values
0 missing
FCFP4_1024b1001numeric2 unique values
0 missing
FCFP4_1024b1002numeric2 unique values
0 missing
FCFP4_1024b1003numeric2 unique values
0 missing
FCFP4_1024b1004numeric2 unique values
0 missing
FCFP4_1024b1005numeric2 unique values
0 missing
FCFP4_1024b1006numeric2 unique values
0 missing
FCFP4_1024b1007numeric2 unique values
0 missing
FCFP4_1024b1008numeric2 unique values
0 missing
FCFP4_1024b1009numeric2 unique values
0 missing
FCFP4_1024b101numeric2 unique values
0 missing
FCFP4_1024b1010numeric1 unique values
0 missing
FCFP4_1024b1011numeric2 unique values
0 missing
FCFP4_1024b1012numeric2 unique values
0 missing
FCFP4_1024b1013numeric2 unique values
0 missing
FCFP4_1024b1014numeric2 unique values
0 missing
FCFP4_1024b1015numeric1 unique values
0 missing
FCFP4_1024b1016numeric2 unique values
0 missing
FCFP4_1024b1017numeric2 unique values
0 missing
FCFP4_1024b1018numeric2 unique values
0 missing
FCFP4_1024b1019numeric2 unique values
0 missing
FCFP4_1024b102numeric2 unique values
0 missing
FCFP4_1024b1020numeric2 unique values
0 missing
FCFP4_1024b1021numeric2 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_1024b104numeric1 unique values
0 missing
FCFP4_1024b105numeric2 unique values
0 missing
FCFP4_1024b106numeric2 unique values
0 missing
FCFP4_1024b108numeric2 unique values
0 missing
FCFP4_1024b109numeric2 unique values
0 missing
FCFP4_1024b11numeric2 unique values
0 missing
FCFP4_1024b110numeric2 unique values
0 missing
FCFP4_1024b111numeric2 unique values
0 missing
FCFP4_1024b112numeric2 unique values
0 missing
FCFP4_1024b113numeric2 unique values
0 missing
FCFP4_1024b114numeric2 unique values
0 missing
FCFP4_1024b115numeric1 unique values
0 missing
FCFP4_1024b117numeric2 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_1024b122numeric2 unique values
0 missing
FCFP4_1024b123numeric2 unique values
0 missing
FCFP4_1024b125numeric1 unique values
0 missing
FCFP4_1024b126numeric1 unique values
0 missing
FCFP4_1024b127numeric2 unique values
0 missing
FCFP4_1024b128numeric2 unique values
0 missing
FCFP4_1024b129numeric2 unique values
0 missing
FCFP4_1024b13numeric2 unique values
0 missing
FCFP4_1024b130numeric2 unique values
0 missing
FCFP4_1024b131numeric2 unique values
0 missing
FCFP4_1024b132numeric1 unique values
0 missing
FCFP4_1024b133numeric2 unique values
0 missing
FCFP4_1024b134numeric2 unique values
0 missing
FCFP4_1024b135numeric2 unique values
0 missing
FCFP4_1024b136numeric2 unique values
0 missing
FCFP4_1024b137numeric2 unique values
0 missing
FCFP4_1024b138numeric2 unique values
0 missing
FCFP4_1024b139numeric2 unique values
0 missing
FCFP4_1024b14numeric2 unique values
0 missing
FCFP4_1024b140numeric2 unique values
0 missing
FCFP4_1024b141numeric2 unique values
0 missing
FCFP4_1024b142numeric2 unique values
0 missing
FCFP4_1024b143numeric1 unique values
0 missing
FCFP4_1024b144numeric2 unique values
0 missing
FCFP4_1024b145numeric2 unique values
0 missing
FCFP4_1024b146numeric2 unique values
0 missing
FCFP4_1024b147numeric2 unique values
0 missing
FCFP4_1024b148numeric2 unique values
0 missing
FCFP4_1024b149numeric1 unique values
0 missing
FCFP4_1024b15numeric2 unique values
0 missing
FCFP4_1024b152numeric2 unique values
0 missing
FCFP4_1024b153numeric2 unique values
0 missing
FCFP4_1024b154numeric2 unique values
0 missing
FCFP4_1024b155numeric2 unique values
0 missing
FCFP4_1024b156numeric1 unique values
0 missing
FCFP4_1024b157numeric2 unique values
0 missing
FCFP4_1024b158numeric1 unique values
0 missing
FCFP4_1024b159numeric2 unique values
0 missing
FCFP4_1024b16numeric2 unique values
0 missing
FCFP4_1024b160numeric2 unique values
0 missing
FCFP4_1024b161numeric1 unique values
0 missing
FCFP4_1024b162numeric2 unique values
0 missing
FCFP4_1024b163numeric1 unique values
0 missing
FCFP4_1024b164numeric2 unique values
0 missing
FCFP4_1024b165numeric2 unique values
0 missing
FCFP4_1024b166numeric1 unique values
0 missing
FCFP4_1024b167numeric2 unique values
0 missing
FCFP4_1024b168numeric1 unique values
0 missing
FCFP4_1024b169numeric2 unique values
0 missing
FCFP4_1024b170numeric2 unique values
0 missing
FCFP4_1024b171numeric2 unique values
0 missing
FCFP4_1024b172numeric1 unique values
0 missing
FCFP4_1024b173numeric2 unique values
0 missing
FCFP4_1024b174numeric2 unique values
0 missing
FCFP4_1024b175numeric2 unique values
0 missing

62 properties

770
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.
Maximum entropy among attributes.
-2
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.13
Second quartile (Median) of standard deviation of attributes of the numeric type.
770
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.
6.02
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.
105.7
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.
99.36
Percentage of numeric attributes.
0.04
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.67
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.
27.75
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
10.36
Third quartile of skewness among attributes of the numeric type.
1.3
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
17.01
First quartile of kurtosis among attributes of the numeric type.
0.19
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
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
150.14
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.
0.1
Mean of means among attributes of the numeric type.
4.36
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.05
First quartile of standard deviation of attributes of the numeric type.
-0.11
Average class difference between consecutive instances.
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.
0.2
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
45.05
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.
9.47
Mean skewness among attributes of the numeric type.
0.02
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
0.14
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.
6.85
Second quartile (Median) of skewness among attributes of the numeric type.

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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