Assessment of prediction accuracy of protein function from protein–protein interaction data

By Haretsugu Hishigaki, Kenta Nakai, Toshihide Ono, Akira Tanigami, Toshihisa Takagi. Yeast, 2001

360 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/379cbb12fbf5d2bf50a0594ac06737223aa2be4f

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In Molecular Biology

Citations in the corpus

Topological structure analysis of the protein-protein interaction network in budding yeast. (2003, background): “(19) predicted uncharacterized proteins based on interacting partners; Maslov and Sneppen (20) analyzed the stable topological properties of interaction networks; Ge et al.”
Whole-proteome prediction of protein function via graph-theoretic analysis of interaction maps (2005, methodology): “For each protein, we consider all other proteins within a radius r as described in Hishigaki et al. (2001), and then for each function, we use a χ 2 -test to determine if it is over-represented.”
Analyzing and modeling real-world phenomena with complex networks: a survey of applications (2007, methodology): “Other methods are based on interaction partners, because proteins with the same funct ions end to share connections [328].”
Prediction of Protein Function Using Protein–Protein Interaction Data (2002, methodology): “The above approaches have been extended to l-neighbors, where two proteins are lneighbors of each other if they are separated by at most l − 1 proteins through interactions (Schwikowski et al. 2000; Hishigaki et al. 2001).”
Uncovering Biological Network Function via Graphlet Degree Signatures (2008, background): “…protein function from it is one of the major challenges in ∗to whom correspondence should be addressed the post-genomic era (Nabieva et al., 2005; Vazquez et al., 2003; Schwikowski and Fields, 2000; Hishigaki et al., 2001; Letovsky and Kasif, 2003; Deng et al., 2003, 2004; Brun et al., 2004).”
Predicting protein functions with message passing algorithms (2004, methodology): “…unclassiﬁed proteins whose interactions with the rest of the graph are at least partially known, there are the so called Neighboring Counting Method 16 , the χ 2 Method 17 , the Bayesian approaches 5,6 , the Redundancy Method 18 and a more recent Monte Carlo Simulated Annealing (SA) approach 7 .”
Network-based prediction of protein function (2007, methodology): “Hishigaki et al (2001) try to tackle the ﬁrst problem by computing w 2 -like scores for function assignment.”
Global protein function prediction in protein-protein interaction networks (2003, background): “Assigning to an unclassiﬁed protein the most common function(s) present among the classiﬁed interacting proteins, as in [7,8] (majority rule assignment) is rather straightforward.”
Relating whole-genome expression data with protein-protein interactions. (2002, background): “Our work follows up on many recent analyses of protein-protein interactions (Fellenberg et al. 2000; Hishigaki et al. 2001; Teichmann et al. 2001; Walhout and Vidal 2001).”