IntAct—open source resource for molecular interaction data

IntAct is an open source database and software suite for modeling, storing and analyzing molecular interaction data. The data available in the database originates entirely from published literature and is manually annotated by expert biologists to a high level of detail, including experimental methods, conditions and interacting domains. The database features over 126 000 binary interactions extracted from over 2100 scientific publications and makes extensive use of controlled vocabularies. The web site provides tools allowing users to search, visualize and download data from the repository. IntAct supports and encourages local installations as well as direct data submission and curation collaborations. IntAct source code and data are freely available from

The Relationship between the UniProt Knowledgebase (UniProtKB) and the IntAct Molecular Interaction Databases

IntAct provides a freely available, open source database system and analysis tools for protein interaction data. All interactions are derived from literature curation or direct user submission and all experimental information relating to binary protein-protein
interactions is entered into the IntAct database by curators, via a web-based editor. Interaction information is added to the SUBUNIT comment and the RP line of the relevant publication within the UniProtKB entry. There may be a single INTERACTION comment present within a UniProtKB entry, which conveys information relevant to binary protein-protein interactions. This is automatically derived from the IntAct database and is updated on a triweekly basis. Interactions can be derived by any appropriate experimental method but must be confirmed by a second interaction if resulting from a single yeast2hybrid experiment. For large-scale experiments, interactions are considered if a high confidence score is assigned by the authors. The INTERACTION line contains a direct link to IntAct that provides detailed information for the experimental support. These lines are not changed manually and any discrepancy is reported to IntAct for updates. There is also a database crossreference line within the UniProtKB entry i.e.: DR IntAct _UniProtKB AC, which directs the user to additional interaction data for that molecule. 
UniProt is supported by grants from the National Institutes of Health, European Commission, Swiss Federal Government and PATRIC BRC.
IntAct is funded by the European Commission under FELICS, contract number 021902 (RII3) within the Research Infrastructure Action of the FP6 "Structuring the European Research Area" Programme

The Relationship between the UniProt Knowledgebase (UniProtKB) and the IntAct Molecular Interaction Databases

IntAct provides a freely available, open source database system and analysis tools for protein interaction data. All interactions are derived from literature curation or direct user submission and all experimental information relating to binary protein-protein
interactions is entered into the IntAct database by curators, via a web-based editor. Interaction information is added to the SUBUNIT comment and the RP line of the relevant publication within the UniProtKB entry. There may be a single INTERACTION comment present within a UniProtKB entry, which conveys information relevant to binary protein-protein interactions. This is automatically derived from the IntAct database and is updated on a triweekly basis. Interactions can be derived by any appropriate experimental method but must be confirmed by a second interaction if resulting from a single yeast2hybrid experiment. For large-scale experiments, interactions are considered if a high confidence score is assigned by the authors. The INTERACTION line contains a direct link to IntAct that provides detailed information for the experimental support. These lines are not changed manually and any discrepancy is reported to IntAct for updates. There is also a database crossreference line within the UniProtKB entry i.e.: DR IntAct _UniProtKB AC, which directs the user to additional interaction data for that molecule. 
UniProt is supported by grants from the National Institutes of Health, European Commission, Swiss Federal Government and PATRIC BRC.
IntAct is funded by the European Commission under FELICS, contract number 021902 (RII3) within the Research Infrastructure Action of the FP6 "Structuring the European Research Area" Programme

Gene3D: comprehensive structural and functional annotation of genomes

Gene3D provides comprehensive structural and functional annotation of most available protein sequences, including the UniProt, RefSeq and Integr8 resources. The main structural annotation is generated through scanning these sequences against the CATH structural domain database profile-HMM library. CATH is a database of manually derived PDB-based structural domains, placed within a hierarchy reflecting topology, homology and conservation and is able to infer more ancient and divergent homology relationships than sequence-based approaches. This data is supplemented with Pfam-A, other non-domain structural predictions (i.e. coiled coils) and experimental data from UniProt. In order to enhance the investigations possible with this data, we have also incorporated a variety of protein annotation resources, including protein–protein interaction data, GO functional assignments, KEGG pathways, FUNCAT functional descriptions and links to microarray expression data. All of this data can be accessed through a newly re-designed website that has a focus on flexibility and clarity, with searches that can be restricted to a single genome or across the entire sequence database. Currently Gene3D contains over 3.5 million domain assignments for nearly 5 million proteins including 527 completed genomes. This is available at: http://gene3d.biochem.ucl.ac.uk

Unbiased protein association study on the public human proteome reveals biological connections between co-occurring protein pairs

Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal wayS to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targets for follow-up analysis

InnateDB: systems biology of innate immunity and beyond—recent updates and continuing curation

peer-reviewedInnateDB (http://www.innatedb.com) is an integrated analysis platform that has been specifically designed to facilitate systems-level analyses of mammalian innate immunity networks, pathways and genes. In this article, we provide details of recent updates and improvements to the database. InnateDB now contains >196 000 human, mouse and bovine experimentally validated molecular interactions and 3000 pathway annotations of relevance to all mammalian cellular systems (i.e. not just immune relevant pathways and interactions). In addition, the InnateDB team has, to date, manually curated in excess of 18 000 molecular interactions of relevance to innate immunity, providing unprecedented insight into innate immunity networks, pathways and their component molecules. More recently, InnateDB has also initiated the curation of allergy- and asthma-related interactions. Furthermore, we report a range of improvements to our integrated bioinformatics solutions including web service access to InnateDB interaction data using Proteomics Standards Initiative Common Query Interface, enhanced Gene Ontology analysis for innate immunity, and the availability of new network visualizations tools. Finally, the recent integration of bovine data makes InnateDB the first integrated network analysis platform for this agriculturally important model organism.This work was supported by Genome BC through the Pathogenomics of Innate Immunity (PI2) project and by the Foundation for the National Institutes of Health and the Canadian Institutes of Health Research under the Grand Challenges in Global Health Research Initiative [Grand Challenges ID: 419]. Further funding was also provided by AllerGen grants 12ASI1 and 12B&B2. D.J.L. was funded in part during this project by a postdoctoral trainee award from the Michael Smith Foundation for Health Research (MSFHR). F.S.L.B. is a MSFHR Senior Scholar and R.E.W.H. holds a Canada Research Chair (CRC). Funding to enable bovine systems biology in InnateDB is provided by Teagasc [RMIS6018] and the Teagasc Walsh Fellowship scheme. IMEx is funded by the European Commission under the PSIMEx project [contract number FP7-HEALTH-2007-223411]. Funding for open access charge: Teagasc [RMIS6018]

SPRINT: Ultrafast protein-protein interaction prediction of the entire human interactome

Proteins perform their functions usually by interacting with other proteins. Predicting which proteins interact is a fundamental problem. Experimental methods are slow, expensive, and have a high rate of error. Many computational methods have been proposed among which sequence-based ones are very promising. However, so far no such method is able to predict effectively the entire human interactome: they require too much time or memory. We present SPRINT (Scoring PRotein INTeractions), a new sequence-based algorithm and tool for predicting protein-protein interactions. We comprehensively compare SPRINT with state-of-the-art programs on seven most reliable human PPI datasets and show that it is more accurate while running orders of magnitude faster and using very little memory. SPRINT is the only program that can predict the entire human interactome. Our goal is to transform the very challenging problem of predicting the entire human interactome into a routine task. The source code of SPRINT is freely available from github.com/lucian-ilie/SPRINT/ and the datasets and predicted PPIs from www.csd.uwo.ca/faculty/ilie/SPRINT/