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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