Faster and more accurate global protein function assignment from protein interaction networks using the MFGO algorithm

On four proteins interaction datasets, including Vazquez dataset, YP dataset, DIP‐core dataset, and SPK dataset, MFGO was tested and compared with the popular MR (majority rule) and GOM methods. Experimental results confirm MFGO's improvement on both speed and accuracy. Especially, MFGO method has a distinctive advantage in accurately predicting functions for proteins with few neighbors. Moreover, the robustness of the approach was validated both in a dataset containing a high percentage of unknown proteins and a disturbed dataset through random insertion and deletion. The analysis shows that a moderate amount of misplaced interactions do not preclude a reliable function assignment.

[1]  P. Bork,et al.  Functional organization of the yeast proteome by systematic analysis of protein complexes , 2002, Nature.

[2]  B. Schwikowski,et al.  A network of protein–protein interactions in yeast , 2000, Nature Biotechnology.

[3]  David Martin,et al.  Functional classification of proteins for the prediction of cellular function from a protein-protein interaction network , 2003, Genome Biology.

[4]  PagelPhilipp,et al.  The MIPS mammalian protein--protein interaction database , 2005 .

[5]  B. Snel,et al.  Comparative assessment of large-scale data sets of protein–protein interactions , 2002, Nature.

[6]  Ian M. Donaldson,et al.  BIND: the Biomolecular Interaction Network Database , 2001, Nucleic Acids Res..

[7]  Alessandro Vespignani,et al.  Global protein function prediction from protein-protein interaction networks , 2003, Nature Biotechnology.

[8]  Kui Zhang,et al.  Prediction of protein function using protein-protein interaction data , 2002, Proceedings. IEEE Computer Society Bioinformatics Conference.

[9]  D. Eisenberg,et al.  Assigning protein functions by comparative genome analysis: protein phylogenetic profiles. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[10]  T. Takagi,et al.  Assessment of prediction accuracy of protein function from protein–protein interaction data , 2001, Yeast.

[11]  Kiyoshi Asai,et al.  Accurate extraction of functional associations between proteins based on common interaction partners and common domains , 2005, Bioinform..

[12]  Gary D Bader,et al.  Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry , 2002, Nature.

[13]  Baldomero Oliva,et al.  Detecting remotely related proteins by their interactions and sequence similarity. , 2005, Proceedings of the National Academy of Sciences of the United States of America.