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Prediction of Protein-Protein Interaction Sites with Conditional Random Fields

Protein-protein interactions appear in
almost every biological process. Proteins are mainly folded into
three dimensional structures, which requires that a meaningful
prediction should take consideration of the important spatial
relationships of the amino acid residues. In this regard, many
research groups use the spatial neighborhood information to
evaluate the residues in their predictions, but the model itself do
not consider the dependencies between the spatial neighboring
residues. Our contribution is modeling the spatial neighborhood
information of a protein directly into a graphical model based on
the approach of conditional random fields.