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1.  EBI metagenomics—a new resource for the analysis and archiving of metagenomic data 
Nucleic Acids Research  2013;42(D1):D600-D606.
Metagenomics is a relatively recently established but rapidly expanding field that uses high-throughput next-generation sequencing technologies to characterize the microbial communities inhabiting different ecosystems (including oceans, lakes, soil, tundra, plants and body sites). Metagenomics brings with it a number of challenges, including the management, analysis, storage and sharing of data. In response to these challenges, we have developed a new metagenomics resource (http://www.ebi.ac.uk/metagenomics/) that allows users to easily submit raw nucleotide reads for functional and taxonomic analysis by a state-of-the-art pipeline, and have them automatically stored (together with descriptive, standards-compliant metadata) in the European Nucleotide Archive.
doi:10.1093/nar/gkt961
PMCID: PMC3965009  PMID: 24165880
2.  The MetaboLights repository: curation challenges in metabolomics 
MetaboLights is the first general-purpose open-access curated repository for metabolomic studies, their raw experimental data and associated metadata, maintained by one of the major open-access data providers in molecular biology. Increases in the number of depositions, number of samples per study and the file size of data submitted to MetaboLights present a challenge for the objective of ensuring high-quality and standardized data in the context of diverse metabolomic workflows and data representations. Here, we describe the MetaboLights curation pipeline, its challenges and its practical application in quality control of complex data depositions.
Database URL: http://www.ebi.ac.uk/metabolights
doi:10.1093/database/bat029
PMCID: PMC3638156  PMID: 23630246
3.  The Stem Cell Commons: an exemplar for data integration in the biomedical domain driven by the ISA framework 
Comparisons of stem cell experiments at both molecular and semantic levels remain challenging due to inconsistencies in results, data formats, and descriptions among biomedical research discoveries. The Harvard Stem Cell Institute (HSCI) has created the Stem Cell Commons (stemcellcommons.org), an open, community-based approach to data sharing. Experimental information is integrated using the Investigation-Study-Assay tabular format (ISA-Tab) used by over 30 organizations (ISA Commons, isacommons.org). The early adoption of this format permitted the novel integration of three independent systems to facilitate stem cell data storage, exchange and analysis: the Blood Genomics Repository, the Stem Cell Discovery Engine, and the new Refinery platform that links the Galaxy analytical engine to data repositories.
PMCID: PMC3814497  PMID: 24303302
4.  OntoMaton: a Bioportal powered ontology widget for Google Spreadsheets 
Bioinformatics  2012;29(4):525-527.
Motivation: Data collection in spreadsheets is ubiquitous, but current solutions lack support for collaborative semantic annotation that would promote shared and interdisciplinary annotation practices, supporting geographically distributed players.
Results: OntoMaton is an open source solution that brings ontology lookup and tagging capabilities into a cloud-based collaborative editing environment, harnessing Google Spreadsheets and the NCBO Web services. It is a general purpose, format-agnostic tool that may serve as a component of the ISA software suite. OntoMaton can also be used to assist the ontology development process.
Availability: OntoMaton is freely available from Google widgets under the CPAL open source license; documentation and examples at: https://github.com/ISA-tools/OntoMaton.
Contact: isatools@googlegroups.com
doi:10.1093/bioinformatics/bts718
PMCID: PMC3570217  PMID: 23267176
5.  MetaboLights—an open-access general-purpose repository for metabolomics studies and associated meta-data 
Nucleic Acids Research  2012;41(D1):D781-D786.
MetaboLights (http://www.ebi.ac.uk/metabolights) is the first general-purpose, open-access repository for metabolomics studies, their raw experimental data and associated metadata, maintained by one of the major open-access data providers in molecular biology. Metabolomic profiling is an important tool for research into biological functioning and into the systemic perturbations caused by diseases, diet and the environment. The effectiveness of such methods depends on the availability of public open data across a broad range of experimental methods and conditions. The MetaboLights repository, powered by the open source ISA framework, is cross-species and cross-technique. It will cover metabolite structures and their reference spectra as well as their biological roles, locations, concentrations and raw data from metabolic experiments. Studies automatically receive a stable unique accession number that can be used as a publication reference (e.g. MTBLS1). At present, the repository includes 15 submitted studies, encompassing 93 protocols for 714 assays, and span over 8 different species including human, Caenorhabditis elegans, Mus musculus and Arabidopsis thaliana. Eight hundred twenty-seven of the metabolites identified in these studies have been mapped to ChEBI. These studies cover a variety of techniques, including NMR spectroscopy and mass spectrometry.
doi:10.1093/nar/gks1004
PMCID: PMC3531110  PMID: 23109552
6.  MetaboLights: towards a new COSMOS of metabolomics data management 
Metabolomics  2012;8(5):757-760.
Exciting funding initiatives are emerging in Europe and the US for metabolomics data production, storage, dissemination and analysis. This is based on a rich ecosystem of resources around the world, which has been build during the past ten years, including but not limited to resources such as MassBank in Japan and the Human Metabolome Database in Canada. Now, the European Bioinformatics Institute has launched MetaboLights, a database for metabolomics experiments and the associated metadata (http://www.ebi.ac.uk/metabolights). It is the first comprehensive, cross-species, cross-platform metabolomics database maintained by one of the major open access data providers in molecular biology. In October, the European COSMOS consortium will start its work on Metabolomics data standardization, publication and dissemination workflows. The NIH in the US is establishing 6–8 metabolomics services cores as well as a national metabolomics repository. This communication reports about MetaboLights as a new resource for Metabolomics research, summarises the related developments and outlines how they may consolidate the knowledge management in this third large omics field next to proteomics and genomics.
doi:10.1007/s11306-012-0462-0
PMCID: PMC3465651  PMID: 23060735
Metabolomics; Databases; ISA-Tab; ISA commons
7.  Toward interoperable bioscience data 
Nature genetics  2012;44(2):121-126.
To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open ‘data commoning’ culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared ‘Investigation-Study-Assay’ framework to support that vision.
doi:10.1038/ng.1054
PMCID: PMC3428019  PMID: 22281772
8.  The Metadata Coverage Index (MCI): A standardized metric for quantifying database metadata richness 
Standards in Genomic Sciences  2012;6(3):438-447.
Variability in the extent of the descriptions of data (‘metadata’) held in public repositories forces users to assess the quality of records individually, which rapidly becomes impractical. The scoring of records on the richness of their description provides a simple, objective proxy measure for quality that enables filtering that supports downstream analysis. Pivotally, such descriptions should spur on improvements. Here, we introduce such a measure - the ‘Metadata Coverage Index’ (MCI): the percentage of available fields actually filled in a record or description. MCI scores can be calculated across a database, for individual records or for their component parts (e.g., fields of interest). There are many potential uses for this simple metric: for example; to filter, rank or search for records; to assess the metadata availability of an ad hoc collection; to determine the frequency with which fields in a particular record type are filled, especially with respect to standards compliance; to assess the utility of specific tools and resources, and of data capture practice more generally; to prioritize records for further curation; to serve as performance metrics of funded projects; or to quantify the value added by curation. Here we demonstrate the utility of MCI scores using metadata from the Genomes Online Database (GOLD), including records compliant with the ‘Minimum Information about a Genome Sequence’ (MIGS) standard developed by the Genomic Standards Consortium. We discuss challenges and address the further application of MCI scores; to show improvements in annotation quality over time, to inform the work of standards bodies and repository providers on the usability and popularity of their products, and to assess and credit the work of curators. Such an index provides a step towards putting metadata capture practices and in the future, standards compliance, into a quantitative and objective framework.
doi:10.4056/sigs.2675953
PMCID: PMC3558968  PMID: 23409217
9.  A call for an international network of genomic observatories (GOs) 
GigaScience  2012;1:5.
We are entering a new era in genomics–that of large-scale, place-based, highly contextualized genomic research. Here we review this emerging paradigm shift and suggest that sites of utmost scientific importance be expanded into ‘Genomic Observatories’ (GOs). Investment in GOs should focus on the digital characterization of whole ecosystems, from all-taxa biotic inventories to time-series ’omics studies. The foundational layer of biodiversity–genetic variation–would thus be mainstreamed into Earth Observation systems enabling predictive modelling of biodiversity dynamics and resultant impacts on ecosystem services.
doi:10.1186/2047-217X-1-5
PMCID: PMC3617453  PMID: 23587188
Ecogenomics; Earth observation; Biodiversity; Ecosystems; Biocode; Genomic observatory; DNA
10.  On the evolving portfolio of community-standards and data sharing policies: turning challenges into new opportunities 
GigaScience  2012;1:10.
There are thousands of biology databases with hundreds of terminologies, reporting guidelines, representations models, and exchange formats to help annotate, report, and share bioscience investigations. It is evident, however, that researchers and bioinformaticians struggle to navigate the various standards and to find the appropriate database to collect, manage, and share data. Further, policy makers, funders, and publishers lack sufficient information to formulate their guidelines. In this paper, we highlight a number of key issues that can be used to turn these challenges into new opportunities. It is time for all stakeholders to work together to reconcile cause and effect and make the data-sharing culture functional and efficient.
doi:10.1186/2047-217X-1-10
PMCID: PMC3626509  PMID: 23587326
Standard; Ontology; Data sharing; Curation; Data policy; ISA commons; ISA-Tab; BioSharing
11.  Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications 
Yilmaz, Pelin | Kottmann, Renzo | Field, Dawn | Knight, Rob | Cole, James R | Amaral-Zettler, Linda | Gilbert, Jack A | Karsch-Mizrachi, Ilene | Johnston, Anjanette | Cochrane, Guy | Vaughan, Robert | Hunter, Christopher | Park, Joonhong | Morrison, Norman | Rocca-Serra, Philippe | Sterk, Peter | Arumugam, Manimozhiyan | Bailey, Mark | Baumgartner, Laura | Birren, Bruce W | Blaser, Martin J | Bonazzi, Vivien | Booth, Tim | Bork, Peer | Bushman, Frederic D | Buttigieg, Pier Luigi | Chain, Patrick S G | Charlson, Emily | Costello, Elizabeth K | Huot-Creasy, Heather | Dawyndt, Peter | DeSantis, Todd | Fierer, Noah | Fuhrman, Jed A | Gallery, Rachel E | Gevers, Dirk | Gibbs, Richard A | Gil, Inigo San | Gonzalez, Antonio | Gordon, Jeffrey I | Guralnick, Robert | Hankeln, Wolfgang | Highlander, Sarah | Hugenholtz, Philip | Jansson, Janet | Kau, Andrew L | Kelley, Scott T | Kennedy, Jerry | Knights, Dan | Koren, Omry | Kuczynski, Justin | Kyrpides, Nikos | Larsen, Robert | Lauber, Christian L | Legg, Teresa | Ley, Ruth E | Lozupone, Catherine A | Ludwig, Wolfgang | Lyons, Donna | Maguire, Eamonn | Methé, Barbara A | Meyer, Folker | Muegge, Brian | Nakielny, Sara | Nelson, Karen E | Nemergut, Diana | Neufeld, Josh D | Newbold, Lindsay K | Oliver, Anna E | Pace, Norman R | Palanisamy, Giriprakash | Peplies, Jörg | Petrosino, Joseph | Proctor, Lita | Pruesse, Elmar | Quast, Christian | Raes, Jeroen | Ratnasingham, Sujeevan | Ravel, Jacques | Relman, David A | Assunta-Sansone, Susanna | Schloss, Patrick D | Schriml, Lynn | Sinha, Rohini | Smith, Michelle I | Sodergren, Erica | Spor, Aymé | Stombaugh, Jesse | Tiedje, James M | Ward, Doyle V | Weinstock, George M | Wendel, Doug | White, Owen | Whiteley, Andrew | Wilke, Andreas | Wortman, Jennifer R | Yatsunenko, Tanya | Glöckner, Frank Oliver
Nature Biotechnology  2011;29(5):415-420.
Here we present a standard developed by the Genomic Standards Consortium (GSC) for reporting marker gene sequences—the minimum information about a marker gene sequence (MIMARKS). We also introduce a system for describing the environment from which a biological sample originates. The ‘environmental packages’ apply to any genome sequence of known origin and can be used in combination with MIMARKS and other GSC checklists. Finally, to establish a unified standard for describing sequence data and to provide a single point of entry for the scientific community to access and learn about GSC checklists, we present the minimum information about any (x) sequence (MIxS). Adoption of MIxS will enhance our ability to analyze natural genetic diversity documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biosphere.
doi:10.1038/nbt.1823
PMCID: PMC3367316  PMID: 21552244
12.  graph2tab, a library to convert experimental workflow graphs into tabular formats 
Bioinformatics  2012;28(12):1665-1667.
Motivations: Spreadsheet-like tabular formats are ever more popular in the biomedical field as a mean for experimental reporting. The problem of converting the graph of an experimental workflow into a table-based representation occurs in many such formats and is not easy to solve.
Results: We describe graph2tab, a library that implements methods to realise such a conversion in a size-optimised way. Our solution is generic and can be adapted to specific cases of data exporters or data converters that need to be implemented.
Availability and Implementation: The library source code and documentation are available at http://github.com/ISA-tools/graph2tab.
Contact: brandizi@ebi.ac.uk.
Supplementary Information: A supplementary document describes the theoretical and technical details about the library implementation.
doi:10.1093/bioinformatics/bts258
PMCID: PMC3371871  PMID: 22556367
13.  Towards BioDBcore: a community-defined information specification for biological databases 
The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources; and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.
doi:10.1093/database/baq027
PMCID: PMC3017395  PMID: 21205783
14.  Meeting Report from the Second “Minimum Information for Biological and Biomedical Investigations” (MIBBI) workshop 
Standards in Genomic Sciences  2010;3(3):259-266.
This report summarizes the proceedings of the second workshop of the ‘Minimum Information for Biological and Biomedical Investigations’ (MIBBI) consortium held on Dec 1-2, 2010 in Rüdesheim, Germany through the sponsorship of the Beilstein-Institute. MIBBI is an umbrella organization uniting communities developing Minimum Information (MI) checklists to standardize the description of data sets, the workflows by which they were generated and the scientific context for the work. This workshop brought together representatives of more than twenty communities to present the status of their MI checklists and plans for future development. Shared challenges and solutions were identified and the role of MIBBI in MI checklist development was discussed. The meeting featured some thirty presentations, wide-ranging discussions and breakout groups. The top outcomes of the two-day workshop as defined by the participants were: 1) the chance to share best practices and to identify areas of synergy; 2) defining a series of tasks for updating the MIBBI Portal; 3) reemphasizing the need to maintain independent MI checklists for various communities while leveraging common terms and workflow elements contained in multiple checklists; and 4) revision of the concept of the MIBBI Foundry to focus on the creation of a core set of MIBBI modules intended for reuse by individual MI checklist projects while maintaining the integrity of each MI project. Further information about MIBBI and its range of activities can be found at http://mibbi.org/.
doi:10.4056/sigs.147362
PMCID: PMC3035314  PMID: 21304730
15.  Meeting Report: BioSharing at ISMB 2010 
Standards in Genomic Sciences  2010;3(3):254-258.
This report summarizes the proceedings of the one day BioSharing meeting held at the Intelligent Systems for Molecular Biology (ISMB) 2010 conference in Boston, MA, USA This inaugural BioSharing event was hosted by the Genomic Standards Consortium as part of its M3 & BioSharing special interest group (SIG) workshop. The BioSharing event included invited talks from a range of community leaders and a panel discussion at the end of the day. The panel session led to the formal agreement among community leaders to join together to promote cross-community knowledge exchange and collaborations. A key focus of the newly formed Biosharing community will be linking up resources to promote real-world data sharing (virtuous cycle of data) and supporting compliance with data policies through the creation of a one-stop-portal of information. Further information about the newly established BioSharing effort can be found at http://biosharing.org.
doi:10.4056/sigs/1403501
PMCID: PMC3035313  PMID: 21304729
16.  Towards BioDBcore: a community-defined information specification for biological databases 
Nucleic Acids Research  2010;39(Database issue):D7-D10.
The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.
doi:10.1093/nar/gkq1173
PMCID: PMC3013734  PMID: 21097465
17.  ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level 
Bioinformatics  2010;26(18):2354-2356.
Summary: The first open source software suite for experimentalists and curators that (i) assists in the annotation and local management of experimental metadata from high-throughput studies employing one or a combination of omics and other technologies; (ii) empowers users to uptake community-defined checklists and ontologies; and (iii) facilitates submission to international public repositories.
Availability and Implementation: Software, documentation, case studies and implementations at http://www.isa-tools.org
Contact: isatools@googlegroups.com
doi:10.1093/bioinformatics/btq415
PMCID: PMC2935443  PMID: 20679334
18.  Modeling biomedical experimental processes with OBI 
Journal of Biomedical Semantics  2010;1(Suppl 1):S7.
Background
Experimental descriptions are typically stored as free text without using standardized terminology, creating challenges in comparison, reproduction and analysis. These difficulties impose limitations on data exchange and information retrieval.
Results
The Ontology for Biomedical Investigations (OBI), developed as a global, cross-community effort, provides a resource that represents biomedical investigations in an explicit and integrative framework. Here we detail three real-world applications of OBI, provide detailed modeling information and explain how to use OBI.
Conclusion
We demonstrate how OBI can be applied to different biomedical investigations to both facilitate interpretation of the experimental process and increase the computational processing and integration within the Semantic Web. The logical definitions of the entities involved allow computers to unambiguously understand and integrate different biological experimental processes and their relevant components.
Availability
OBI is available at http://purl.obolibrary.org/obo/obi/2009-11-02/obi.owl
doi:10.1186/2041-1480-1-S1-S7
PMCID: PMC2903726  PMID: 20626927
19.  Challenges of molecular nutrition research 6: the nutritional phenotype database to store, share and evaluate nutritional systems biology studies 
Genes & Nutrition  2010;5(3):189-203.
The challenge of modern nutrition and health research is to identify food-based strategies promoting life-long optimal health and well-being. This research is complex because it exploits a multitude of bioactive compounds acting on an extensive network of interacting processes. Whereas nutrition research can profit enormously from the revolution in ‘omics’ technologies, it has discipline-specific requirements for analytical and bioinformatic procedures. In addition to measurements of the parameters of interest (measures of health), extensive description of the subjects of study and foods or diets consumed is central for describing the nutritional phenotype. We propose and pursue an infrastructural activity of constructing the “Nutritional Phenotype database” (dbNP). When fully developed, dbNP will be a research and collaboration tool and a publicly available data and knowledge repository. Creation and implementation of the dbNP will maximize benefits to the research community by enabling integration and interrogation of data from multiple studies, from different research groups, different countries and different—omics levels. The dbNP is designed to facilitate storage of biologically relevant, pre-processed—omics data, as well as study descriptive and study participant phenotype data. It is also important to enable the combination of this information at different levels (e.g. to facilitate linkage of data describing participant phenotype, genotype and food intake with information on study design and—omics measurements, and to combine all of this with existing knowledge). The biological information stored in the database (i.e. genetics, transcriptomics, proteomics, biomarkers, metabolomics, functional assays, food intake and food composition) is tailored to nutrition research and embedded in an environment of standard procedures and protocols, annotations, modular data-basing, networking and integrated bioinformatics. The dbNP is an evolving enterprise, which is only sustainable if it is accepted and adopted by the wider nutrition and health research community as an open source, pre-competitive and publicly available resource where many partners both can contribute and profit from its developments. We introduce the Nutrigenomics Organisation (NuGO, http://www.nugo.org) as a membership association responsible for establishing and curating the dbNP. Within NuGO, all efforts related to dbNP (i.e. usage, coordination, integration, facilitation and maintenance) will be directed towards a sustainable and federated infrastructure.
doi:10.1007/s12263-010-0167-9
PMCID: PMC2935528  PMID: 21052526
Nutritional phenotype; Nutrigenomics; Database
20.  Challenges of molecular nutrition research 6: the nutritional phenotype database to store, share and evaluate nutritional systems biology studies 
Genes & Nutrition  2010;5(3):189-203.
The challenge of modern nutrition and health research is to identify food-based strategies promoting life-long optimal health and well-being. This research is complex because it exploits a multitude of bioactive compounds acting on an extensive network of interacting processes. Whereas nutrition research can profit enormously from the revolution in ‘omics’ technologies, it has discipline-specific requirements for analytical and bioinformatic procedures. In addition to measurements of the parameters of interest (measures of health), extensive description of the subjects of study and foods or diets consumed is central for describing the nutritional phenotype. We propose and pursue an infrastructural activity of constructing the “Nutritional Phenotype database” (dbNP). When fully developed, dbNP will be a research and collaboration tool and a publicly available data and knowledge repository. Creation and implementation of the dbNP will maximize benefits to the research community by enabling integration and interrogation of data from multiple studies, from different research groups, different countries and different—omics levels. The dbNP is designed to facilitate storage of biologically relevant, pre-processed—omics data, as well as study descriptive and study participant phenotype data. It is also important to enable the combination of this information at different levels (e.g. to facilitate linkage of data describing participant phenotype, genotype and food intake with information on study design and—omics measurements, and to combine all of this with existing knowledge). The biological information stored in the database (i.e. genetics, transcriptomics, proteomics, biomarkers, metabolomics, functional assays, food intake and food composition) is tailored to nutrition research and embedded in an environment of standard procedures and protocols, annotations, modular data-basing, networking and integrated bioinformatics. The dbNP is an evolving enterprise, which is only sustainable if it is accepted and adopted by the wider nutrition and health research community as an open source, pre-competitive and publicly available resource where many partners both can contribute and profit from its developments. We introduce the Nutrigenomics Organisation (NuGO, http://www.nugo.org) as a membership association responsible for establishing and curating the dbNP. Within NuGO, all efforts related to dbNP (i.e. usage, coordination, integration, facilitation and maintenance) will be directed towards a sustainable and federated infrastructure.
doi:10.1007/s12263-010-0167-9
PMCID: PMC2935528  PMID: 21052526
Nutritional phenotype; Nutrigenomics; Database
21.  The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration 
Nature biotechnology  2007;25(11):1251.
The value of any kind of data is greatly enhanced when it exists in a form that allows it to be integrated with other data. One approach to integration is through the annotation of multiple bodies of data using common controlled vocabularies or ‘ontologies’. Unfortunately, the very success of this approach has led to a proliferation of ontologies, which itself creates obstacles to integration. The Open Biomedical Ontologies (OBO) consortium is pursuing a strategy to overcome this problem. Existing OBO ontologies, including the Gene Ontology, are undergoing coordinated reform, and new ontologies are being created on the basis of an evolving set of shared principles governing ontology development. The result is an expanding family of ontologies designed to be interoperable and logically well formed and to incorporate accurate representations of biological reality. We describe this OBO Foundry initiative and provide guidelines for those who might wish to become involved.
doi:10.1038/nbt1346
PMCID: PMC2814061  PMID: 17989687
22.  Development of FuGO: An Ontology for Functional Genomics Investigations 
The development of the Functional Genomics Investigation Ontology (FuGO) is a collaborative, international effort that will provide a resource for annotating functional genomics investigations, including the study design, protocols and instrumentation used, the data generated and the types of analysis performed on the data. FuGO will contain both terms that are universal to all functional genomics investigations and those that are domain specific. In this way, the ontology will serve as the “semantic glue” to provide a common understanding of data from across these disparate data sources. In addition, FuGO will reference out to existing mature ontologies to avoid the need to duplicate these resources, and will do so in such a way as to enable their ease of use in annotation. This project is in the early stages of development; the paper will describe efforts to initiate the project, the scope and organization of the project, the work accomplished to date, and the challenges encountered, as well as future plans.
doi:10.1089/omi.2006.10.199
PMCID: PMC2783628  PMID: 16901226
24.  Owner controlled data exchange in nutrigenomic collaborations: the NuGO information network 
Genes & Nutrition  2009;4(2):113-122.
New ‘omics’ technologies are changing nutritional sciences research. They enable to tackle increasingly complex questions but also increase the need for collaboration between research groups. An important challenge for successful collaboration is the management and structured exchange of information that accompanies data-intense technologies. NuGO, the European Nutrigenomics Organization, the major collaborating network in molecular nutritional sciences, is supporting the application of modern information technologies in this area. We have developed and implemented a concept for data management and computing infrastructure that supports collaboration between nutrigenomics researchers. The system fills the gap between “private” storing with occasional file sharing by email and the use of centralized databases. It provides flexible tools to share data, also during experiments, while preserving ownership. The NuGO Information Network is a decentral, distributed system for data exchange based on standard web technology. Secure access to data, maintained by the individual researcher, is enabled by web services based on the the BioMoby framework. A central directory provides information about available web services. The flexibility of the infrastructure allows a wide variety of services for data processing and integration by combining several web services, including public services. Therefore, this integrated information system is suited for other research collaborations.
doi:10.1007/s12263-009-0123-8
PMCID: PMC2690731  PMID: 19408032
Nutrigenomics; Data management; Data integration; Distributed information system; Web services
25.  Survey-based naming conventions for use in OBO Foundry ontology development 
BMC Bioinformatics  2009;10:125.
Background
A wide variety of ontologies relevant to the biological and medical domains are available through the OBO Foundry portal, and their number is growing rapidly. Integration of these ontologies, while requiring considerable effort, is extremely desirable. However, heterogeneities in format and style pose serious obstacles to such integration. In particular, inconsistencies in naming conventions can impair the readability and navigability of ontology class hierarchies, and hinder their alignment and integration. While other sources of diversity are tremendously complex and challenging, agreeing a set of common naming conventions is an achievable goal, particularly if those conventions are based on lessons drawn from pooled practical experience and surveys of community opinion.
Results
We summarize a review of existing naming conventions and highlight certain disadvantages with respect to general applicability in the biological domain. We also present the results of a survey carried out to establish which naming conventions are currently employed by OBO Foundry ontologies and to determine what their special requirements regarding the naming of entities might be. Lastly, we propose an initial set of typographic, syntactic and semantic conventions for labelling classes in OBO Foundry ontologies.
Conclusion
Adherence to common naming conventions is more than just a matter of aesthetics. Such conventions provide guidance to ontology creators, help developers avoid flaws and inaccuracies when editing, and especially when interlinking, ontologies. Common naming conventions will also assist consumers of ontologies to more readily understand what meanings were intended by the authors of ontologies used in annotating bodies of data.
doi:10.1186/1471-2105-10-125
PMCID: PMC2684543  PMID: 19397794

Results 1-25 (32)