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169
BioGRID: a General Repository for Interaction Datasets
, 2006
"... Access to unified datasets of protein and genetic interactions is critical for interrogation of gene/ protein function and analysis of global network properties. BioGRID is a freely accessible database of physical and genetic interactions available at ..."
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Cited by 424 (1 self)
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Access to unified datasets of protein and genetic interactions is critical for interrogation of gene/ protein function and analysis of global network properties. BioGRID is a freely accessible database of physical and genetic interactions available at
Bind: the biomolecular interaction network database
- Nucleic Acids Res
, 2003
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R.: IntAct: an open source molecular interaction database. Nucleic Acids Res., (2004) 32 Database issue D452-D455
"... IntAct provides an open source database and toolkit for the storage, presentation and analysis of protein interactions. The web interface provides both textual and graphical representations of protein interactions, and allows exploring interaction net-works in the context of the GO annotations of th ..."
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Cited by 213 (13 self)
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IntAct provides an open source database and toolkit for the storage, presentation and analysis of protein interactions. The web interface provides both textual and graphical representations of protein interactions, and allows exploring interaction net-works in the context of the GO annotations of the interacting proteins. A web service allows direct computational access to retrieve interaction net-works in XML format. IntAct currently contains ~2200 binary and complex interactions imported from the literature and curated in collaboration with the Swiss-Prot team, making intensive use of con-trolled vocabularies to ensure data consistency. All IntAct software, data and controlled vocabularies are available at
IntAct–open source resource for molecular interaction data
- Nucleic Acids Res
, 2007
"... interaction data ..."
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STRING: known and predicted protein-protein associations, integrated and transferred across organisms
- Database Issue
, 2005
"... associations, integrated and transferred across organisms ..."
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Cited by 143 (16 self)
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associations, integrated and transferred across organisms
ELM server: a new resource for investigating short functional sites in modular eukaryotic proteins. Nucleic Acids Res
, 2003
"... Multidomain proteins predominate in eukaryotic proteomes. Individual functions assigned to different sequence segments combine to create a complex function for the whole protein. While on-line resources are available for revealing globular domains in sequences, there has hitherto been no comprehensi ..."
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Cited by 133 (6 self)
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Multidomain proteins predominate in eukaryotic proteomes. Individual functions assigned to different sequence segments combine to create a complex function for the whole protein. While on-line resources are available for revealing globular domains in sequences, there has hitherto been no comprehensive collection of small functional sites/ motifs comparable to the globular domain resources, yet these are as important for the function of multidomain proteins. Short linear peptide motifs are used for cell compartment targeting, protein–protein interaction, regulation by phosphorylation, acetylation, glycosylation and a host of other post-translational modifications. ELM, the Eukaryotic Linear Motif server at
STRING 7–recent developments in the integration and prediction of protein interactions
- Nucleic Acids Res
, 2007
"... Information on protein–protein interactions is still mostly limited to a small number of model organisms, and originates from a wide variety of experimental and computational techniques. The database and online resource STRING generalizes access to protein interaction data, by integrating known and ..."
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Cited by 125 (13 self)
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Information on protein–protein interactions is still mostly limited to a small number of model organisms, and originates from a wide variety of experimental and computational techniques. The database and online resource STRING generalizes access to protein interaction data, by integrating known and predicted interactions from a variety of sources. The underlying infrastructure includes a consistent body of completely sequenced genomes and exhaustive orthology classifications, based on which interaction evidence is transferred between organisms. Although primarily developed for protein interaction analysis, the resource has also been successfully applied to comparative genomics, phylogenetics and network studies, which are all facilitated by programmatic access to the database backend and the availability of compact download files. As of release 7, STRING has almost doubled to 373 distinct organisms, and contains more than 1.5 million proteins for which associations have been pre-computed. Novel features include AJAX-based web-navigation, inclusion of additional resources such as BioGRID, and detailed protein domain annotation. STRING is available at
MINT: the Molecular INTeraction database
- Nucleic Acids Res
, 2007
"... The Molecular INTeraction database (MINT, ..."
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The European Bioinformatics Institute’s data resources. Nucleic Acids Res 2010;38:D17–25
"... ABSTRACT The wide uptake of next-generation sequencing and other ultra-high throughput technologies by life scientists with a diverse range of interests, ..."
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Cited by 91 (7 self)
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ABSTRACT The wide uptake of next-generation sequencing and other ultra-high throughput technologies by life scientists with a diverse range of interests,
Protein complex prediction via cost-based clustering
, 2004
"... Motivation: Understanding principles of cellular organization and function can be enhanced if we detect known and predict still undiscovered protein complexes within the cell’s protein–protein interaction (PPI) network. Such predictions may be used as an inexpensive tool to direct biological experim ..."
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Cited by 80 (1 self)
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Motivation: Understanding principles of cellular organization and function can be enhanced if we detect known and predict still undiscovered protein complexes within the cell’s protein–protein interaction (PPI) network. Such predictions may be used as an inexpensive tool to direct biological experiments. The increasing amount of available PPI data necessitates an accurate and scalable approach to protein complex identification. Results: We have developed the Restricted Neighborhood Search Clustering Algorithm (RNSC) to efficiently partition networks into clusters using a cost function. We applied this cost-based clustering algorithm to PPI networks of Saccharomyces cerevisiae, Drosophila melanogaster and Caenorhabditis elegans to identify and predict protein complexes. We have determined functional and graph-theoretic properties of true protein complexes from the MIPS data-base. Based on these properties, we defined filters to distinguish between identified network clusters and true protein complexes. Conclusions: Our application of the cost-based clustering algorithm provides an accurate and scalable method of detecting and predicting protein complexes within a PPI network. Availability: The RNSC algorithm and data processing code are available upon request from the authors.
