Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5701

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL5701

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 by Noureddin Sadawi
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL5701 (TID: 101506), and it has 79 rows and 65 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.

67 features

pXC50 (target)numeric35 unique values
0 missing
molecule_id (row identifier)nominal79 unique values
0 missing
BLTA96numeric72 unique values
0 missing
BLTD48numeric69 unique values
0 missing
BLTF96numeric69 unique values
0 missing
MLOGPnumeric76 unique values
0 missing
MLOGP2numeric78 unique values
0 missing
AACnumeric74 unique values
0 missing
AECCnumeric78 unique values
0 missing
ALOGPnumeric79 unique values
0 missing
ALOGP2numeric79 unique values
0 missing
AMRnumeric79 unique values
0 missing
AMWnumeric75 unique values
0 missing
ARRnumeric64 unique values
0 missing
ATS1enumeric75 unique values
0 missing
ATS1inumeric75 unique values
0 missing
ATS1mnumeric76 unique values
0 missing
ATS1pnumeric74 unique values
0 missing
ATS1snumeric74 unique values
0 missing
ATS1vnumeric73 unique values
0 missing
ATS2enumeric75 unique values
0 missing
ATS2inumeric77 unique values
0 missing
ATS2mnumeric77 unique values
0 missing
ATS2pnumeric76 unique values
0 missing
ATS2snumeric79 unique values
0 missing
ATS2vnumeric78 unique values
0 missing
ATS3enumeric77 unique values
0 missing
ATS3inumeric75 unique values
0 missing
ATS3mnumeric76 unique values
0 missing
ATS3pnumeric76 unique values
0 missing
ATS3snumeric72 unique values
0 missing
ATS3vnumeric76 unique values
0 missing
ATS4enumeric77 unique values
0 missing
ATS4inumeric79 unique values
0 missing
ATS4mnumeric76 unique values
0 missing
ATS4pnumeric75 unique values
0 missing
ATS4snumeric77 unique values
0 missing
ATS4vnumeric78 unique values
0 missing
ATS5enumeric77 unique values
0 missing
ATS5inumeric78 unique values
0 missing
ATS5mnumeric77 unique values
0 missing
ATS5pnumeric78 unique values
0 missing
ATS5snumeric77 unique values
0 missing
ATS5vnumeric78 unique values
0 missing
ATS6enumeric74 unique values
0 missing
ATS6inumeric77 unique values
0 missing
ATS6mnumeric74 unique values
0 missing
ATS6pnumeric78 unique values
0 missing
ATS6snumeric78 unique values
0 missing
ATS6vnumeric75 unique values
0 missing
ATS7enumeric78 unique values
0 missing
ATS7inumeric78 unique values
0 missing
ATS7mnumeric78 unique values
0 missing
ATS7pnumeric78 unique values
0 missing
ATS7snumeric77 unique values
0 missing
ATS7vnumeric76 unique values
0 missing
ATS8enumeric76 unique values
0 missing
ATS8inumeric78 unique values
0 missing
ATS8mnumeric78 unique values
0 missing
ATS8pnumeric78 unique values
0 missing
ATS8snumeric79 unique values
0 missing
ATS8vnumeric77 unique values
0 missing
ATSC1enumeric69 unique values
0 missing
ATSC1inumeric75 unique values
0 missing
ATSC1mnumeric77 unique values
0 missing
ATSC1pnumeric78 unique values
0 missing
ATSC1snumeric79 unique values
0 missing

62 properties

79
Number of instances (rows) of the dataset.
67
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.
66
Number of numeric attributes.
1
Number of nominal 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.
Second quartile (Median) of entropy among attributes.
0.85
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.35
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.
-0.06
Mean skewness among attributes of the numeric type.
4.2
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
1.2
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.
-0.13
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-0.81
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.
8.81
Maximum kurtosis among attributes of the numeric type.
-4.03
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
122.19
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.
1.17
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.
98.51
Percentage of numeric attributes.
5.18
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-1.64
Minimum skewness among attributes of the numeric type.
1.49
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2.5
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.
0.13
Third quartile of skewness among attributes of the numeric type.
24.11
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.14
First quartile of kurtosis among attributes of the numeric type.
0.45
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.
4
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
0.79
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.
6.39
Mean of means among attributes of the numeric type.
-0.35
First quartile of skewness among attributes of the numeric type.
0.1
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.26
First quartile of standard deviation of attributes of the numeric type.

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
Define a new task