Advancing translational research with the Semantic Web

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Abstract

Background

A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature.

Results

We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine.

Conclusion

Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base, and growing pains as the technology is scaled up. Still, the potential of interoperable knowledge sources for biomedicine, at the scale of the World Wide Web, merits continued work.

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Most cited references 77

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A specific amyloid-beta protein assembly in the brain impairs memory.

Sylvain Lesne, Ming Teng Koh, Linda Kotilinek … (2006)

Memory function often declines with age, and is believed to deteriorate initially because of changes in synaptic function rather than loss of neurons. Some individuals then go on to develop Alzheimer's disease with neurodegeneration. Here we use Tg2576 mice, which express a human amyloid-beta precursor protein (APP) variant linked to Alzheimer's disease, to investigate the cause of memory decline in the absence of neurodegeneration or amyloid-beta protein amyloidosis. Young Tg2576 mice ( 14 months old) form abundant neuritic plaques containing amyloid-beta (refs 3-6). We found that memory deficits in middle-aged Tg2576 mice are caused by the extracellular accumulation of a 56-kDa soluble amyloid-beta assembly, which we term Abeta*56 (Abeta star 56). Abeta*56 purified from the brains of impaired Tg2576 mice disrupts memory when administered to young rats. We propose that Abeta*56 impairs memory independently of plaques or neuronal loss, and may contribute to cognitive deficits associated with Alzheimer's disease.

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Long-term potentiation and memory.

M A Lynch (2004)

One of the most significant challenges in neuroscience is to identify the cellular and molecular processes that underlie learning and memory formation. The past decade has seen remarkable progress in understanding changes that accompany certain forms of acquisition and recall, particularly those forms which require activation of afferent pathways in the hippocampus. This progress can be attributed to a number of factors including well-characterized animal models, well-defined probes for analysis of cell signaling events and changes in gene transcription, and technology which has allowed gene knockout and overexpression in cells and animals. Of the several animal models used in identifying the changes which accompany plasticity in synaptic connections, long-term potentiation (LTP) has received most attention, and although it is not yet clear whether the changes that underlie maintenance of LTP also underlie memory consolidation, significant advances have been made in understanding cell signaling events that contribute to this form of synaptic plasticity. In this review, emphasis is focused on analysis of changes that occur after learning, especially spatial learning, and LTP and the value of assessing these changes in parallel is discussed. The effect of different stressors on spatial learning/memory and LTP is emphasized, and the review concludes with a brief analysis of the contribution of studies, in which transgenic animals were used, to the literature on memory/learning and LTP.

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BIND: the Biomolecular Interaction Network Database.

Gary Bader, Doron Betel, Christopher W. V. Hogue (2003)

The Biomolecular Interaction Network Database (BIND: http://bind.ca) archives biomolecular interaction, complex and pathway information. A web-based system is available to query, view and submit records. BIND continues to grow with the addition of individual submissions as well as interaction data from the PDB and a number of large-scale interaction and complex mapping experiments using yeast two hybrid, mass spectrometry, genetic interactions and phage display. We have developed a new graphical analysis tool that provides users with a view of the domain composition of proteins in interaction and complex records to help relate functional domains to protein interactions. An interaction network clustering tool has also been developed to help focus on regions of interest. Continued input from users has helped further mature the BIND data specification, which now includes the ability to store detailed information about genetic interactions. The BIND data specification is available as ASN.1 and XML DTD.

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Author and article information

Journal

Journal ID (nlm-ta): BMC Bioinformatics

Title: BMC Bioinformatics

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2105

Publication date Collection: 2007

Publication date (Electronic): 9 May 2007

Volume: 8

Issue: Suppl 3

Page: S2

Affiliations

[1 ]Millennium Pharmaceuticals, Cambridge, MA, USA

[2 ]Initiative in Innovative Computing, Harvard University, Cambridge, MA, USA

[3 ]Laboratory for Bioimaging and Anatomical Informatics, Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA, USA

[4 ]Section on Medical Expert and Knowledge-Based Systems, Medical University of Vienna, Vienna, Austria

[5 ]National Library of Medicine, Bethesda, MD, USA

[6 ]Agfa Healthcare, Waterloo, Ontario, Canada

[7 ]Brainstage Research, Pittsburgh, PA, USA

[8 ]AstraZeneca, Mölndal, Sweden

[9 ]MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA, USA

[10 ]Partners HealthCare System, Wellesley, MA, USA

[11 ]Alzheimer Research Forum, Boston, MA, USA

[12 ]Harvard Medical School, Boston, MA, USA

[13 ]Integrative Bioinformatics Unit, University of Amsterdam, Amsterdam, The Netherlands

[14 ]Cleveland Clinic Foundation, Cleveland, OH, USA

[15 ]Science Commons, Cambridge, MA, USA

[16 ]Oracle, Burlington, MA, USA

[17 ]Language & Computing, Reston, VA, USA

[18 ]Teranode Corporation, Seattle, WA, USA

[19 ]World Wide Web Consortium (W3C)

[20 ]Center for Medical Informatics, Yale University School of Medicine, New Haven, CT, USA

Article

Publisher ID: 1471-2105-8-S3-S2

DOI: 10.1186/1471-2105-8-S3-S2

PMC ID: 1892099

PubMed ID: 17493285

SO-VID: 2ad5c3ca-a5e8-4a82-bf7b-bb5f5e9b8956

License:

This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advancing translational research with the Semantic Web

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Abstract

Background

Results

Conclusion

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Genetoberfest

Most cited references 77

A specific amyloid-beta protein assembly in the brain impairs memory.

Long-term potentiation and memory.

BIND: the Biomolecular Interaction Network Database.

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