Inferring protein-protein interaction networks from protein complex data.
Present day approaches for the determination of protein-protein interaction networks are usually based on two hybrid experimental measurements. Here we consider a computational method that uses another type of experimental data: instead of direct information about protein-protein interactions, we consider data in the form of protein complexes. We propose a method for using these complexes to provide predictions of protein-protein interactions. When applied to a dataset obtained from a cat melanoma cell line we find that we are able to predict when a protein pair belongs to a complex with approximately 96% accuracy. Further, we are able to extrapolate the experimentally identified interaction pairs to the entire cat proteome.
Department of Computational Biology, Sandia National Laboratories, Albuquerque, NM 87185-1316, USA. smartin@sandia.gov
Shawn
S
Martin
Zisu
Z
Mao
Linda S
LS
Chan
Suraiya
S
Rasheed
D000818:Animals; D002415:Cats; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D015180:Electrophoresis, Gel, Two-Dimensional; D015233:Models, Statistical; D025941:Protein Interaction Mapping; D011506:Proteins / Q000737:chemistry*; D020543:Proteome; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D020539:Sequence Analysis, Protein; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; D020798:Two-Hybrid System Techniques
D011506:Proteins; D020543:Proteome