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A Novel Method to Predict Protein-Protein Interactions Based on the Information of Protein-Protein Interaction Networks and Protein Sequence

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Abstract:

Protein-protein interactions (PPIs) are crucial to most biochemical processes in human beings. Although many human PPIs have been identified by experiments, the number is still limited compared to the available protein sequences of human organisms. Recently, many computational methods have been proposed to facilitate the recognition of novel human PPIs. However the existing methods only concentrated on the information of individual PPI, while the systematic characteristic of protein-protein interaction networks (PINs) was ignored. In this study, a new method was proposed by combining the global information of PINs and protein sequence information. Random forest (RF) algorithm was implemented to develop the prediction model, and a high accuracy of 91.88% was obtained. Furthermore, the RF model was tested by using three independent datasets with good performances, suggesting that our method is a useful tool for identification of PPIs and investigation into PINs as well.





Keywords: Auto covariance; HIV-1 reverse transcriptase; PINs; RF algorithm; WoLFPSORT package; cellular automaton image; hierarchical random graph; human PINs; human PPIs; independent dataset; link prediction; net charge index; non-interacting protein pairs; paralogous verification methods; polarizability; protein-protein interaction networks; protein-protein interactions; protein-protein sequence; proteomics studies; random forest; solvent accessible surface area

Document Type: Research Article

DOI: http://dx.doi.org/10.2174/092986611796011482

Publication date: September 1, 2011

More about this publication?
  • Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.

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