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.read more
Citations
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Journal ArticleDOI
Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks
Paul Shannon,Andrew Markiel,Owen Ozier,Nitin S. Baliga,Jonathan T. Wang,Daniel Ramage,Nada Amin,Benno Schwikowski,Trey Ideker +8 more
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
Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry
Yuen Ho,Albrecht Gruhler,Adrian Heilbut,Gary D. Bader,Gary D. Bader,Lynda Moore,Sally-Lin Adams,Anna Millar,Paul J. Taylor,Keiryn L. Bennett,Kelly Boutilier,Lingyun Yang,Cheryl Wolting,Ian Donaldson,Søren Schandorff,Juanita Shewnarane,Mai Vo,Joanne Taggart,Marilyn Goudreault,Brenda Muskat,Cris Alfarano,Danielle Dewar,Zhen Lin,Katerina Michalickova,Katerina Michalickova,Andrew Willems,Andrew Willems,Holly Sassi,Peter A Nielsen,Karina Juhl Rasmussen,Jens R. Andersen,Lene E. Johansen,Lykke Haastrup Hansen,Hans Jespersen,Alexandre V. Podtelejnikov,Eva Nielsen,Janne S. Crawford,Vibeke Poulsen,Birgitte D Sørensen,Jesper Matthiesen,Ronald C. Hendrickson,Frank Gleeson,Tony Pawson,Tony Pawson,Michael Moran,Daniel Durocher,Daniel Durocher,Matthias Mann,Christopher W. V. Hogue,Christopher W. V. Hogue,Daniel Figeys,Mike Tyers,Mike Tyers +52 more
TL;DR: Comparison of the HMS-PCI data set with interactions reported in the literature revealed an average threefold higher success rate in detection of known complexes compared with large-scale two-hybrid studies.
Journal ArticleDOI
Towards a proteome-scale map of the human protein–protein interaction network
Jean François Rual,Kavitha Venkatesan,Tong Hao,Tomoko Hirozane-Kishikawa,Amélie Dricot,Ning Li,Gabriel F. Berriz,Francis D. Gibbons,Matija Dreze,Nono Ayivi-Guedehoussou,Niels Klitgord,Christophe Simon,Mike Boxem,Stuart Milstein,Jennifer Rosenberg,Debra S. Goldberg,Lan V. Zhang,Sharyl L. Wong,Giovanni Franklin,Siming Li,Joanna S. Albala,Joanna S. Albala,Janghoo Lim,Carlene Fraughton,Estelle Llamosas,Sebiha Cevik,Camille Bex,Philippe Lamesch,Robert S. Sikorski,Jean Vandenhaute,Huda Y. Zoghbi,Alex Smolyar,Stephanie Bosak,Reynaldo Sequerra,Lynn Doucette-Stamm,Michael E. Cusick,David E. Hill,Frederick P. Roth,Marc Vidal +38 more
TL;DR: An initial version of a proteome-scale map of human binary protein–protein interactions is described, which increases by ∼70% the set of available binary interactions within the tested space and reveals more than 300 new connections to over 100 disease-associated proteins.
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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A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae
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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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