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Using genetic algorithms to select most predictive protein features.

Kernytsky A, Rost B,
Proteins (2009) 75:75-88 PublishedPSI:Phase 2  
Northeast Structural Genomics Consortium

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Many important characteristics of proteins such as biochemical activity and subcellular localization present a challenge to machine-learning methods: it is often difficult to encode the appropriate input features at the residue level for the purpose of making a prediction for the entire protein. ...
metabolism chemistry methods 
Computational Biology Models, Molecular Computer Simulation Serine Endopeptidases Databases, Protein Structure-Activity Relationship Protein Conformation Neural Networks (Computer) Proteins Algorithms 
18798568  
10.1002/prot.22211  
16 (Last update: 04/01/2017 12:15:57pm)  
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