Accessible Protein Interaction Data for Network Modeling. Structure of the Information and Available Repositories

ABSTRACTSoftware tools that allow visualization and analysis of protein interaction networks are essential for studies in systems biology. One of the most popular network visualization tools in biology is Cytoscape, which offers a large selection of plugins for interpretation of protein interaction data. Chemical cross-linking coupled to mass spectrometry (XL-MS) is an increasingly important source for such interaction data, but there are currently no Cytoscape tools to analyze XL-MS results. In light of the suitability of Cytoscape platform but also to expand its toolbox, here we introduce XlinkCyNET, an open-source Cytoscape Java plugin for exploring large-scale XL-MS-based protein interaction networks. XlinkCyNET offers rapid and easy visualization of intra and intermolecular cross-links and the locations of protein domains in a rectangular bar style, allowing subdomain-level interrogation of the interaction network. XlinkCyNET is freely available from the Cytoscape app store: http://apps.cytoscape.org/apps/xlinkcynet and at https://www.theliulab.com/software/xlinkcynet.

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Approach of the functional evolution of duplicated genes in Saccharomyces cerevisiae using a new classification method based on protein-protein interaction data

Genome Evolution ◽

10.1007/978-94-010-0263-9_21 ◽

2003 ◽

pp. 213-224

Author(s):

Christine Brun ◽

Alain Guénoche ◽

Bernard Jacq

Keyword(s):

Saccharomyces Cerevisiae ◽

Protein Interaction ◽

Classification Method ◽

Protein Interaction Data ◽

Interaction Data ◽

Duplicated Genes ◽

Functional Evolution ◽

New Classification ◽

Protein Protein Interaction

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Functional classification of proteins based on protein interaction data

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics ◽

10.1002/047001153x.g303314 ◽

2005 ◽

Author(s):

Christine Brun ◽

Ana��s Baudot ◽

Bernard Jacq

Keyword(s):

Protein Interaction ◽

Protein Interaction Data ◽

Interaction Data ◽

Functional Classification

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Discovering Interaction Motifs from Protein Interaction Networks

Biological Data Mining in Protein Interaction Networks ◽

10.4018/978-1-60566-398-2.ch007 ◽

2009 ◽

pp. 99-116 ◽

Cited By ~ 1

Author(s):

Hugo Willy

Keyword(s):

Protein Interaction ◽

Protein Interactions ◽

Protein Interaction Networks ◽

Interaction Networks ◽

Protein Interaction Data ◽

Interaction Data ◽

Protein Patterns ◽

Protein Protein Interaction ◽

Family Based ◽

High Throughput Experiments

Recent breakthroughs in high throughput experiments to determine protein-protein interaction have generated a vast amount of protein interaction data. However, most of the experiments could only answer the question of whether two proteins interact but not the question on the mechanisms by which proteins interact. Such understanding is crucial for understanding the protein interaction of an organism as a whole (the interactome) and even predicting novel protein interactions. Protein interaction usually occurs at some specific sites on the proteins and, given their importance, they are usually well conserved throughout the evolution of the proteins of the same family. Based on this observation, a number of works on finding protein patterns/motifs conserved in interacting proteins have emerged in the last few years. Such motifs are collectively termed as the interaction motifs. This chapter provides a review on the different approaches on finding interaction motifs with a discussion on their implications, potentials and possible areas of improvements in the future.

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