Improved multi-level protein-protein interaction prediction with semantic-based regularization

HIGHLIGHTS

• who: Saccà et_al BMC Bioinformatics and collaborators from the (UNIVERSITY) have published the paper: Improved multi-level protein-protein interaction prediction with semantic-based regularization, in the Journal: (JOURNAL)
• what: The authors propose solving the multi-level prediction problem adapting a state-of-the-art statistical-relational learning framework, namely Semantic Based Regularization (SBR) . In what follows the authors describe how to design inter-level FOL constraints to properly enforce consistency between predictions at different levels. The authors focus on modeling the constraints tying proteins and domains; it is easy to see that the ones . . .
  

   

  

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