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Table 2 Summary of different features of kinases used in our study

From: Predicting a small molecule-kinase interaction map: A machine learning approach

Short-hand Full Name # Features Feature Type
STTK Serine/Threonine, Tyrosine Kinases 1 nominal
Summary Partitioning into Serine, Threonine and Tyrosine kinases   
PC Phylogenetic Clustering 2 nominal
Summary Partitioning into kinase groups and kinase families   
PRO PROSITE patterns 12 numeric
Summary Find PROSITE patterns in the kinases   
Apri Apriori patterns 14 numeric
Summary Find frequently occurring amino acid sequence patterns   
glAli global alignment scores 113 numeric
Summary Calculate global alignment scores for all pairs of kinases   
locAli local alignment scores 113 numeric
Summary Calculate local alignment scores for all pairs of kinases   
PSF Position Specific Features 98 nominal
Summary Use amino acids at the active center directly as features   
abPSF abstract Postition Specific Features 98 nominal
Summary Use amino acid classes at the active center directly as features