Paper Info
Title
Extension And Robustness Of Transitivity Clustering For Protein-Protein Interaction Network Analysis
Abstract
Partitioning biological data objects into groups such that the objects within the groups share common traits is a longstanding challenge in computational biology. Recently, we developed and established transitivity clustering, a partitioning approach based on weighted transitive graph projection that utilizes a single similarity threshold as density parameter. In previous publications, we concentrated on the graphical user interface and on concrete biomedical application protocols. Here, we contribute the following theoretical considerations: (1) We provide proofs that the average similarity between objects from the same cluster is above the user- given threshold and that the average similarity between objects from different clusters is below the threshold. (2) We extend transitivity clustering to an overlapping clustering tool by integrating two new approaches. (3) We demonstrate the power of transitivity clustering for protein-complex detection. We evaluate our approaches against others by utilizing gold-standard data that was previously used by Broh'ee et al. for reviewing existing bioinformatics clustering tools.The extended version of this article is available online at http://transclust. mpi-inf. mpg.de.
Year
DOI
Venue
2011
10.1080/15427951.2011.604559
INTERNET MATHEMATICS
Keywords
Field
DocType
protein complex,gold standard,biological data,computational biology,graphic user interface
Biological data,Fuzzy clustering,Combinatorics,Correlation clustering,Robustness (computer science),Theoretical computer science,Graphical user interface,Mathematical proof,Cluster analysis,Mathematics,Transitive relation
Journal
Volume
Issue
ISSN
7
4
1542-7951
Citations 
PageRank 
References 
5
0.58
7
Authors
5
Name
Order
Citations
PageRank
Tobias Wittkop1956.10
Sven Rahmann263359.13
Richard Röttger3234.97
Sebastian Böcker433239.19
Jan Baumbach514822.11