The minimum information about a proteomics experiment (MIAPE).

Both the generation and the analysis of proteomics data are now widespread, and high-throughput approaches are commonplace. Protocols continue to increase in complexity as methods and technologies evolve and diversify. To encourage the standardized collection, integration, storage and dissemination of proteomics data, the Human Proteome Organization's Proteomics Standards Initiative develops guidance modules for reporting the use of techniques such as gel electrophoresis and mass spectrometry. This paper describes the processes and principles underpinning the development of these modules; discusses the ramifications for various interest groups such as experimentalists, funders, publishers and the private sector; addresses the issue of overlap with other reporting guidelines; and highlights the criticality of appropriate tools and resources in enabling 'MIAPE-compliant' reporting.

The Functional Genomics Experiment model (FuGE): an extensible framework for standards in functional genomics.

The Functional Genomics Experiment data model (FuGE) has been developed to facilitate convergence of data standards for high-throughput, comprehensive analyses in biology. FuGE models the components of an experimental activity that are common across different technologies, including protocols, samples and data. FuGE provides a foundation for describing entire laboratory workflows and for the development of new data formats. The Microarray Gene Expression Data society and the Proteomics Standards Initiative have committed to using FuGE as the basis for defining their respective standards, and other standards groups, including the Metabolomics Standards Initiative, are evaluating FuGE in their development efforts. Adoption of FuGE by multiple standards bodies will enable uniform reporting of common parts of functional genomics workflows, simplify data-integration efforts and ease the burden on researchers seeking to fulfill multiple minimum reporting requirements. Such advances are important for transparent data management and mining in functional genomics and systems biology.

Survey-based naming conventions for use in OBO Foundry ontology development.

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.

PRIDE: a public repository of protein and peptide identifications for the proteomics community.

PRIDE, the 'PRoteomics IDEntifications database' (http://www.ebi.ac.uk/pride) is a database of protein and peptide identifications that have been described in the scientific literature. These identifications will typically be from specific species, tissues and sub-cellular locations, perhaps under specific disease conditions. Any post-translational modifications that have been identified on individual peptides can be described. These identifications may be annotated with supporting mass spectra. At the time of writing, PRIDE includes the full set of identifications as submitted by individual laboratories participating in the HUPO Plasma Proteome Project and a profile of the human platelet proteome submitted by the University of Ghent in Belgium. By late 2005 PRIDE is expected to contain the identifications and spectra generated by the HUPO Brain Proteome Project. Proteomics laboratories are encouraged to submit their identifications and spectra to PRIDE to support their manuscript submissions to proteomics journals. Data can be submitted in PRIDE XML format if identifications are included or mzData format if the submitter is depositing mass spectra without identifications. PRIDE is a web application, so submission, searching and data retrieval can all be performed using an internet browser. PRIDE can be searched by experiment accession number, protein accession number, literature reference and sample parameters including species, tissue, sub-cellular location and disease state. Data can be retrieved as machine-readable PRIDE or mzData XML (the latter for mass spectra without identifications), or as human-readable HTML.

Standards for reporting bioscience data: a forward look.

Groups representing a number of domains in the life sciences have been developing specifications and resources for the description and transmission of data, including those produced by (high-throughput) omics technologies. Although these developments are individually valuable, there is now a need for coordination to avoid the problem of a multiplicity of competing candidate standards. Three ongoing collaborative projects (FuGE, OBI and MIBBI) offer the promise of support for truly integrated, cross-domain informatics solutions. This article briefly summarizes the status quo with respect to biological and biomedical data standards, and offers an assessment of coming developments.

Progress in standards for reporting omics data.

A number of research groups are generating standard mechanisms and prescriptions for reporting various kinds of biological and biomedical experiments. The motives for this generation include concern about the longevity of data sets (and the robustness of conclusions built upon them), the desire to integrate data from diverse scientific disciplines, and the facility to productively mine accrued data. The pharmaceutical industry continues to play a significant role in the genesis and development of such standards, in conjunction with technology vendors and academia. This review describes the context and nature of the new candidate standards and discusses their relevance to drug discovery and development.

A common open representation of mass spectrometry data and its application to proteomics research.

A broad range of mass spectrometers are used in mass spectrometry (MS)-based proteomics research. Each type of instrument possesses a unique design, data system and performance specifications, resulting in strengths and weaknesses for different types of experiments. Unfortunately, the native binary data formats produced by each type of mass spectrometer also differ and are usually proprietary. The diverse, nontransparent nature of the data structure complicates the integration of new instruments into preexisting infrastructure, impedes the analysis, exchange, comparison and publication of results from different experiments and laboratories, and prevents the bioinformatics community from accessing data sets required for software development. Here, we introduce the 'mzXML' format, an open, generic XML (extensible markup language) representation of MS data. We have also developed an accompanying suite of supporting programs. We expect that this format will facilitate data management, interpretation and dissemination in proteomics research.

A systematic approach to modeling, capturing, and disseminating proteomics experimental data.

Both the generation and the analysis of proteome data are becoming increasingly widespread, and the field of proteomics is moving incrementally toward high-throughput approaches. Techniques are also increasing in complexity as the relevant technologies evolve. A standard representation of both the methods used and the data generated in proteomics experiments, analogous to that of the MIAME (minimum information about a microarray experiment) guidelines for transcriptomics, and the associated MAGE (microarray gene expression) object model and XML (extensible markup language) implementation, has yet to emerge. This hinders the handling, exchange, and dissemination of proteomics data. Here, we present a UML (unified modeling language) approach to proteomics experimental data, describe XML and SQL (structured query language) implementations of that model, and discuss capture, storage, and dissemination strategies. These make explicit what data might be most usefully captured about proteomics experiments and provide complementary routes toward the implementation of a proteome repository.

Minimum reporting requirements for proteomics: a MIAPE primer.

Amongst other functions, the Human Proteome Organization's Proteomics Standards Initiative (HUPO PSI) facilitates the generation by the proteomics community of guidelines that specify the appropriate level of detail to provide when describing the various components of a proteomics experiment. These guidelines are codified as the MIAPE (Minimum Information About a Proteomics Experiment) specification, the first modules of which are now finalized. This primer describes the structure and scope of MIAPE, places it in context amongst reporting specifications for other domains, briefly discusses related informatics resources and closes by considering the ramifications for the proteomics community.

The work of the Human Proteome Organisation's Proteomics Standards Initiative (HUPO PSI).

This article describes the origins, working practices and various development projects of the HUman Proteome Organisation's Proteomics Standards Initiative (HUPO PSI), specifically, our work on reporting requirements, data exchange formats and controlled vocabulary terms. We also offer our view of the two functional genomics projects in which the PSI plays a role (FuGE and FuGO), discussing their impact on our process and laying out the benefits we see as accruing, both to the PSI and to biomedical science as a whole as a result of their widespread acceptance.

The Ontology for Biomedical Investigations.

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

Data standards for Omics data: the basis of data sharing and reuse.

To facilitate sharing of Omics data, many groups of scientists have been working to establish the relevant data standards. The main components of data sharing standards are experiment description standards, data exchange standards, terminology standards, and experiment execution standards. Here we provide a survey of existing and emerging standards that are intended to assist the free and open exchange of large-format data.

Debunking minimum information myths: one hat need not fit all.

A recent meeting report published in this journal suggests that the work of the various bodies attempting to improve the quality of articles describing the results of biomedical experimental work has been misunderstood or, at best, misinterpreted. This response is an attempt to set the record straight and ensure that other groups are not discouraged from using these standards or from joining in their further development in either existing or novel areas of research.

Towards interoperable reporting standards for omics data: hopes and hurdles.

BACKGROUND: As the size and complexity of scientific datasets and the corresponding information stores grow, standards for collecting, describing, formatting, submitting and exchanging information are playing an increasingly active role. Several initiatives occupy strategic positions in the international scenario, both within and across domains. However, the job of harmonising reporting standards is still very much a work in progress; both software interoperability and the data integration remain challenging as things stand. RESULTS: The status quo with respect to standardization initiatives is summarized here, with particular emphasis on the motivation for, and the challenges of, ongoing synergistic activities amongst the academic community focused on the creation of truly interoperable standards. CONCLUSIONS: Groups generating standards should engage with ongoing cross-domain activities to simplify the integration of heterogeneous data sets to the greatest possible extent.

Entering the implementation era: a report on the HUPO-PSI Fall workshop 25-27 September 2006, Washington DC, USA.

Since its conception in April 2002, the Human Proteome Organisation Proteomics Standards Initiative has contributed to the development of community standards for proteomics in a collaborative and very dynamic manner, resulting in the publication and increasing adoption of a number of interchange formats and controlled vocabularies. Repositories supporting these formats are being established or are already operational. In parallel with this, minimum reporting requirement have been developed and are now maturing to the point where they have been submitted for journal publication after prolonged exposure to community-input via the PSI website.

Further steps towards data standardisation: the Proteomic Standards Initiative HUPO 3(rd) annual congress, Beijing 25-27(th) October, 2004.

The increasing volume of proteomics data currently being generated by increasingly high-throughput methodologies has led to an increasing need for methods by which such data can be accurately described, stored and exchanged between experimental researchers and data repositories. Work by the Proteomics Standards Initiative of the Human Proteome Organisation has laid the foundation for the development of standards by which experimental design can be described and data exchange facilitated. The progress of these efforts, and the direct benefits already accruing from them, were described at a plenary session of the 3(rd) Annual HUPO congress. Parallel sessions allowed the three work groups to present their progress to interested parties and to collect feedback from groups already implementing the available formats.

Further steps in standardisation. Report of the second annual Proteomics Standards Initiative Spring Workshop (Siena, Italy 17-20th April 2005).

The spring workshop of the HUPO-PSI convened in Siena to further progress the data standards which are already making an impact on data exchange and deposition in the field of proteomics. Separate work groups pushed forward existing XML standards for the exchange of Molecular Interaction data (PSI-MI, MIF) and Mass Spectrometry data (PSI-MS, mzData) whilst significant progress was made on PSI-MS' mzIdent, which will allow the capture of data from analytical tools such as peak list search engines. A new focus for PSI (GPS, gel electrophoresis) was explored; as was the need for a common representation of protein modifications by all workers in the field of proteomics and beyond. All these efforts are contextualised by the work of the General Proteomics Standards workgroup; which in addition to the MIAPE reporting guidelines, is continually evolving an object model (PSI-OM) from which will be derived the general standard XML format for exchanging data between researchers, and for submission to repositories or journals.