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BIND: the Biomolecular Interaction Network Database

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TLDR
The BIND anticipates the coming large influx of interaction information from high-throughput proteomics efforts including detailed information about post-translational modifications from mass spectrometry.
Abstract
The Biomolecular Interaction Network Database (BIND: http://bind.ca) archives biomolecular interaction, complex and pathway information. A web-based system is available to query, view and submit records. BIND continues to grow with the addition of individual submissions as well as interaction data from the PDB and a number of large-scale interaction and complex mapping experiments using yeast two hybrid, mass spectrometry, genetic interactions and phage display. We have developed a new graphical analysis tool that provides users with a view of the domain composition of proteins in interaction and complex records to help relate functional domains to protein interactions. An interaction network clustering tool has also been developed to help focus on regions of interest. Continued input from users has helped further mature the BIND data specification, which now includes the ability to store detailed information about genetic interactions. The BIND data specification is available as ASN.1 and XML DTD.

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Citations
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Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks

TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
Journal ArticleDOI

An automated method for finding molecular complexes in large protein interaction networks.

TL;DR: A novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes is described.
Journal ArticleDOI

ToppGene Suite for gene list enrichment analysis and candidate gene prioritization

TL;DR: The utility of ToppGene Suite is demonstrated using 20 recently reported GWAS-based gene–disease associations (including novel disease genes) representing five diseases.
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Journal ArticleDOI

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Error and attack tolerance of complex networks

TL;DR: It is found that scale-free networks, which include the World-Wide Web, the Internet, social networks and cells, display an unexpected degree of robustness, the ability of their nodes to communicate being unaffected even by unrealistically high failure rates.
Journal ArticleDOI

A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae

TL;DR: Examination of large-scale yeast two-hybrid screens reveals interactions that place functionally unclassified proteins in a biological context, interactions between proteins involved in the same biological function, and interactions that link biological functions together into larger cellular processes.
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