CiteULike: jyuh's Paton

Recent advances in the reninangiotensin system: angiotensin-converting enzyme 2 and (pro)renin receptor

Raizada — 2008-04-29T05:11:16-00:00

Experimental Physiology, Vol. 93, No. 5. (May 2008), pp. 517-518.

PEDRo: a database for storing, searching and disseminating experimental proteomics data.

K Garwood — 2004-11-22T00:17:30-00:00

BMC Genomics, Vol. 5, No. 1. (17 September 2004)

BACKGROUND: Proteomics is rapidly evolving into a high-throughput technology, in which substantial and systematic studies are conducted on samples from a wide range of physiological, developmental, or pathological conditions. Reference maps from 2D gels are widely circulated. However, there is, as yet, no formally accepted standard representation to support the sharing of proteomics data, and little systematic dissemination of comprehensive proteomic data sets. RESULTS: This paper describes the design, implementation and use of a Proteome Experimental Data Repository (PEDRo), which makes comprehensive proteomics data sets available for browsing, searching and downloading. It is also serves to extend the debate on the level of detail at which proteomics data should be captured, the sorts of facilities that should be provided by proteome data management systems, and the techniques by which such facilities can be made available. CONCLUSIONS: The PEDRo database provides access to a collection of comprehensive descriptions of experimental data sets in proteomics. Not only are these data sets interesting in and of themselves, they also provide a useful early validation of the PEDRo data model, which has served as a starting point for the ongoing standardisation activity through the Proteome Standards Initiative of the Human Proteome Organisation.

Managing and sharing experimental data: standards, tools and pitfalls.

NW Paton — 2008-03-03T14:18:36-00:00

Biochem Soc Trans, Vol. 36, No. Pt 1. (February 2008), pp. 33-36.

Experimental processes in the life sciences are becoming increasingly complex. As a result, recording, archiving and sharing descriptions of these processes and of the results of experiments is becoming ever more challenging. However, validation of results, sharing of best practice and integrated analysis all require systematic description of experiments at carefully determined levels of detail. The present paper discusses issues associated with the management of experimental data in the life sciences, including: the different tasks that experimental data and metadata can support, the role of standards in informing data sharing and archiving, and the development of effective databases and tools, building on these standards.

ISPIDER Central: an integrated database web-server for proteomics.

Jennifer A Siepen — 2008-04-29T13:06:32-00:00

Nucleic acids research (25 April 2008)

Despite the growing volumes of proteomic data, integration of the underlying results remains problematic owing to differences in formats, data captured, protein accessions and services available from the individual repositories. To address this, we present the ISPIDER Central Proteomic Database search (http://www.ispider.manchester.ac.uk/cgi-bin/ProteomicSearch.pl), an integration service offering novel search capabilities over leading, mature, proteomic repositories including PRoteomics IDEntifications database (PRIDE), PepSeeker, PeptideAtlas and the Global Proteome Machine. It enables users to search for proteins and peptides that have been characterised in mass spectrometry-based proteomics experiments from different groups, stored in different databases, and view the collated results with specialist viewers/clients. In order to overcome limitations imposed by the great variability in protein accessions used by individual laboratories, the European Bioinformatics Institute's Protein Identifier Cross-Reference (PICR) service is used to resolve accessions from different sequence repositories. Custom-built clients allow users to view peptide/protein identifications in different contexts from multiple experiments and repositories, as well as integration with the Dasty2 client supporting any annotations available from Distributed Annotation System servers. Further information on the protein hits may also be added via external web services able to take a protein as input. This web server offers the first truly integrated access to proteomics repositories and provides a unique service to biologists interested in mass spectrometry-based proteomics.

Facilitating the development of controlled vocabularies for metabolomics technologies with text mining.

I Spasić — 2008-05-09T13:43:28-00:00

BMC bioinformatics, Vol. 9 Suppl 5 (2008)

BACKGROUND: Many bioinformatics applications rely on controlled vocabularies or ontologies to consistently interpret and seamlessly integrate information scattered across public resources. Experimental data sets from metabolomics studies need to be integrated with one another, but also with data produced by other types of omics studies in the spirit of systems biology, hence the pressing need for vocabularies and ontologies in metabolomics. However, it is time-consuming and non trivial to construct these resources manually. RESULTS: We describe a methodology for rapid development of controlled vocabularies, a study originally motivated by the needs for vocabularies describing metabolomics technologies. We present case studies involving two controlled vocabularies (for nuclear magnetic resonance spectroscopy and gas chromatography) whose development is currently underway as part of the Metabolomics Standards Initiative. The initial vocabularies were compiled manually, providing a total of 243 and 152 terms. A total of 5,699 and 2,612 new terms were acquired automatically from the literature. The analysis of the results showed that full-text articles (especially the Materials and Methods sections) are the major source of technology-specific terms as opposed to paper abstracts. CONCLUSIONS: We suggest a text mining method for efficient corpus-based term acquisition as a way of rapidly expanding a set of controlled vocabularies with the terms used in the scientific literature. We adopted an integrative approach, combining relatively generic software and data resources for time- and cost-effective development of a text mining tool for expansion of controlled vocabularies across various domains, as a practical alternative to both manual term collection and tailor-made named entity recognition methods.

Data capture in bioinformatics: requirements and experiences with Pedro

Daniel Jameson — 2008-04-10T14:56:42-00:00

BMC Bioinformatics, Vol. 9, No. 1. (2008)

BACKGROUND:The systematic capture of appropriately annotated experimental data is a prerequisite for most bioinformatics analyses. Data capture is required not only for submission of data to public repositories, but also to underpin integrated analysis, archiving, and sharing - both within laboratories and in collaborative projects. The widespread requirement to capture data means that data capture and annotation are taking place at many sites, but the small scale of the literature on tools, techniques and experiences suggests that there is work to be done to identify good practice and reduce duplication of effort.RESULTS:This paper reports on experience gained in the deployment of the Pedro data capture tool in a range of representative bioinformatics applications. The paper makes explicit the requirements that have recurred when capturing data in different contexts, indicates how these requirements are addressed in Pedro, and describes case studies that illustrate where the requirements have arisen in practice. CONCLUSIONS:Data capture is a fundamental activity for bioinformatics; all biological data resources build on some form of data capture activity, and many require a blend of import, analysis and annotation. Recurring requirements in data capture suggest that model-driven architectures can be used to construct data capture infrastructures that can be rapidly configured to meet the needs of individual use cases. We have described how one such model-driven infrastructure, namely Pedro, has been deployed in representative case studies, and discussed the extent to which the model-driven approach has been effective in practice.

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

Andrew Jones — 2007-10-11T16:03:11-00:00

Nat Biotech, Vol. 25, No. 10. (October 2007), pp. 1127-1133.

The minimum information about a proteomics experiment (MIAPE)

Chris Taylor — 2007-08-09T00:39:24-00:00

Nature Biotechnology, Vol. 25, No. 8. (08 August 2007), pp. 887-893.

Alcohol in the body.

A Paton — 2007-07-18T09:00:30-00:00

BMJ, Vol. 330, No. 7482. (8 January 2005), pp. 85-87.