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Abstract Mirco Gerke1,2, Erich Bornberg-Bauer1, Xiaoyi Jiang2 and Georg Fuellen1,3
1Division of Bioinformatics, Biology Department, Schlossplatz 4, D-48149 Münster, Germany; 2Institut für Informatik, Fachbereich Mathematik und Informatik, Einsteinstr. 62, D- 48149 Münster, Germany; 3Department of Medicine, AG Bioinformatics, Domagkstr. 3, D-48149 Münster, Germany
Abstract: Protein interactions are an important resource to obtain an understanding of cell function. Recently, researchers have compared networks of interactions in order to understand network evolution. While current methods first infer homologs and then compare topologies, we here present a method which first searches for interesting topologies and then looks for homologs. PINA (protein interaction network analysis) takes the protein interaction networks of two organisms, scans both networks for subnetworks deemed interesting, and then tries to find orthologs among the interesting subnetworks. The application is very fast because orthology investigations are restricted to subnetworks like hubs and clusters that fulfill certain criteria regarding neighborhood and connectivity. Finally, the hubs or clusters found to be related can be visualized and analyzed according to protein annotation.
The process of submitting the paper was smooth with little time required on the author's behalf. Reviews were prompt and the process of addressing reviewer comments was very streamlined. All correspondence with the editorial office was extremely professional with immediate responses. This is one of the few journals asking for feedback on their submission process.Dr Greg Trottier, MD, PhD, FRCSC (University of Toronto, Toronto, Ontario, Canada) What our authors say
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