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ABSTRACT: Background
The prediction of calmodulin-binding (CaM-binding) proteins plays a very important role in the fields of biology and biochemistry, because the calmodulin protein binds and regulates a multitude of protein targets affecting different cellular processes. Computational methods that can accurately identify CaM-binding proteins and CaM-binding domains would accelerate research in calcium signaling and calmodulin function. Short-linear motifs (SLiMs), on the other hand, have been effectively used as features for analyzing protein-protein interactions, though their properties have not been utilized in the prediction of CaM-binding proteins.Results
We propose a new method for the prediction of CaM-binding proteins based on both the total and average scores of known and n
SUBMITTER: Li Y
PROVIDER: S-EPMC6245490 | biostudies-literature | 2018 Nov
REPOSITORIES: biostudies-literature