modMine: flexible access to modENCODE data

Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, UK.
Nucleic Acids Research (Impact Factor: 9.11). 11/2011; 40(Database issue):D1082-8. DOI: 10.1093/nar/gkr921
Source: PubMed


In an effort to comprehensively characterize the functional elements within the genomes of the important model organisms Drosophila melanogaster and Caenorhabditis elegans, the NHGRI model organism Encyclopaedia of DNA Elements (modENCODE) consortium has generated an enormous library of genomic data along with detailed, structured information on all aspects of the experiments. The modMine database ( described here has been built by the modENCODE Data Coordination Center to allow the broader research community to (i) search for and download data sets of interest among the thousands generated by modENCODE; (ii) access the data in an integrated form together with non-modENCODE data sets; and (iii) facilitate fine-grained analysis of the above data. The sophisticated search features are possible because of the collection of extensive experimental metadata by the consortium. Interfaces are provided to allow both biologists and bioinformaticians to exploit these rich modENCODE data sets now available via modMine.

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Available from: Rachel Lyne, Oct 03, 2015
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    • "esyN is primarily written in the javascript language, using the following libraries: cytoscape.js [12], intermine [13], jQuery [42], angularJS [43], underscore.js [44]. "
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    ABSTRACT: The construction and analysis of networks is increasingly widespread in biological research. We have developed esyN ("easy networks") as a free and open source tool to facilitate the exchange of biological network models between researchers. esyN acts as a searchable database of user-created networks from any field. We have developed a simple companion web tool that enables users to view and edit networks using data from publicly available databases. Both normal interaction networks (graphs) and Petri nets can be created. In addition to its basic tools, esyN contains a number of logical templates that can be used to create models more easily. The ability to use previously published models as building blocks makes esyN a powerful tool for the construction of models and network graphs. Users are able to save their own projects online and share them either publicly or with a list of collaborators. The latter can be given the ability to edit the network themselves, allowing online collaboration on network construction. esyN is designed to facilitate unrestricted exchange of this increasingly important type of biological information. Ultimately, the aim of esyN is to bring the advantages of Open Source software development to the construction of biological networks.
    PLoS ONE 09/2014; 9(9):e106035. DOI:10.1371/journal.pone.0106035 · 3.23 Impact Factor
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    • "However , the loca - tions and extents of UTRs , promoters , and enhancers are more difficult to annotate . For mammalian genes , the TRANSFAC database ( Wingender et al . 1996 ) reports exper - imentally validated transcription factor binding sites , consen - sus binding sequences , etc . The availability of various relevant data from modENCODE ( Contrino et al . 2012 ) should have a positive impact on annotation of regulatory regions in the future . Moreover , new databases relevant to fly transcriptom - ics are already emerging , e . g . , OnTheFly ( Shazman et al . 2013 ) and REDfly ( Gallo et al . 2011 ) . Additionally , although there is a wealth of information about signaling and biochem - ical"
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    ABSTRACT: Drosophila melanogaster has become a system-of-choice for functional genomic studies. Many resources, including online databases and software tools, are now available to support design or identification of relevant fly stocks and reagents, or analysis and mining of existing functional genomic, transcriptomic, proteomic, etc. datasets. These include large community collections of fly stocks and plasmid clones, 'meta' information sites like FlyBase and FlyMine, and an increasing number of more specialized reagents, databases and online tools. Here, we introduce key resources useful to plan large-scale functional genomics studies in Drosophila and to analyze, integrate and mine the results of those studies in ways that facilitate identification of highest-confidence results and generation of new hypotheses. We also discuss ways in which existing resources can be used and might be improved, and suggest a few areas of future development that would further support large- and small-scale studies in Drosophila and facilitate use of Drosophila information by the research community more generally.
    Genetics 03/2014; 197(1). DOI:10.1534/genetics.113.154344 · 5.96 Impact Factor
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    • "It includes a web application providing a simple user interface with a set of analysis tools suitable for first time users, as well as a powerful, scriptable web-service API to allow programmatic access to data for more advanced users (for a review of the InterMine platform, see reference6). It was originally built for the FlyMine project7, and has since been used by a number of projects ranging from large-scale functional annotation of the C. elegans and D. melanogaster genomes (modENCODE8) drug discovery (TargetMine9), fruit fly transcription factors (FlyTF10) and mitochondrial proteomics (MitoMiner11). "
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    ABSTRACT: Model organisms are widely used for understanding basic biology, and have significantly contributed to the study of human disease. In recent years, genomic analysis has provided extensive evidence of widespread conservation of gene sequence and function amongst eukaryotes, allowing insights from model organisms to help decipher gene function in a wider range of species. The InterMOD consortium is developing an infrastructure based around the InterMine data warehouse system to integrate genomic and functional data from a number of key model organisms, leading the way to improved cross-species research. So far including budding yeast, nematode worm, fruit fly, zebrafish, rat and mouse, the project has set up data warehouses, synchronized data models, and created analysis tools and links between data from different species. The project unites a number of major model organism databases, improving both the consistency and accessibility of comparative research, to the benefit of the wider scientific community.
    Scientific Reports 05/2013; 3:1802. DOI:10.1038/srep01802 · 5.58 Impact Factor
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