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Stoecker/etal/2019a: Protein Complex Similarity Based on Weisfeiler-Lehman Labeling

Bibtype Inproceedings
Bibkey Stoecker/etal/2019a
Author Bianca K. St{\"{o}}cker and Till Sch{\"{a}}fer and Petra Mutzel and Johannes K{\"{o}}ster and Nils M. Kriege and Sven Rahmann
Editor Giuseppe Amato and Claudio Gennaro and Vincent Oria and Milos Radovanovic
Title Protein Complex Similarity Based on {W}eisfeiler-{L}ehman Labeling
Booktitle Similarity Search and Applications
Pages 308--322
Address Cham
Publisher Springer International Publishing
Abstract Proteins in living cells rarely act alone, but instead perform their functions together with other proteins in so-called protein complexes. Being able to quantify the similarity between two protein complexes is essential for numerous applications, e.g. for database searches of complexes that are similar to a given input complex. While the similarity problem has been extensively studied on single proteins and protein families, there is very little existing work on modeling and computing the similarity between protein complexes. Because protein complexes can be naturally modeled as graphs, in principle general graph similarity measures may be used, but these are often computationally hard to obtain and do not take typical properties of protein complexes into account. Here we propose a parametric family of similarity measures based on Weisfeiler-Lehman labeling. We evaluate it on simulated complexes of the extended human integrin adhesome network. We show that the defined family of similarity measures is in good agreement with edit similarity, a similarity measure derived from graph edit distance, but can be computed more efficiently. It can therefore be used in large-scale studies and serve as a basis for further refinements of modeling protein complex similarity.
Year 2019
Projekt SFB876-A6,SFB876-C1
Isbn 978-3-030-32047-8
Bibtex Here you can get this literature entry as BibTeX format.