The TMO/TMKB paper is now available on-line here:  http://www.jbiomedsem.com/content/2/S2/S1/

An application interface was independently built by LINKatu (http://linkatu.net/), a Spanish start-up that recently joined W3C: http://85.48.202.13:8080/AD/ and is now working with us in the Translational Medicine Task Group led by Michel Duontier.

Thank you to all who contributed!  And thank you to Iger Huerga and tne LINKatu team for putting the very nice contribution.  

Kind Regards,
Joanne

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Joanne S. Luciano, PhD                            Rensselaer Polytechnic Institute 
Research Associate Professor                 110 8th Street, Winslow 2143
Tetherless World Constellation                Troy, NY 12180, USA 
Department of Computer Science            Email: jluciano@cs.rpi.edu
Office Tel. +1.518.276.4939                         Global Tel. +1.617.440.4364 (skypeIn)
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The Translational Medicine Ontology and Knowledge Base: Driving personalized medicine by bridging the gap between bench and bedside

Joanne S Luciano email, Bosse Andersson email, Colin Batchelor email, Olivier Bodenreider email, Tim Clark email, Christine K Denney email, Christopher Domarew email, Thomas Gambet email, Lee Harland email, Anja Jentzsch email, Vipul Kashyap email,Peter Kos email, Julia Kozlovsky email, Timothy Lebo email, Scott M Marshall email, James P McCusker email, Deborah L McGuinness email, Chimezie Ogbuji email, Elgar Pichler email, Robert L Powers email, Eric Prud¿hommeaux email, Matthias Samwald email, Lynn Schriml email, Peter J. Tonellato email, Patricia L. Whetzel email, Jun Zhao email, Susie Stephens email andMichel Dumontier email

Journal of Biomedical Semantics 2011, 2(Suppl 2):S1

Published:17 May 2011

Abstract (provisional)


Background

Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery.

Results

We developed the Translational Medicine Ontology (TMO) as a unifying ontology to integrate chemical, genomic and proteomic data with disease, treatment, and electronic health records. We demonstrate the use of Semantic Web technologies in the integration of patient and biomedical data, and reveal how such a knowledge base can aid physicians in providing tailored patient care and facilitate the recruitment of patients into active clinical trials. Thus, patients, physicians and researchers may explore the knowledge base to better understand therapeutic options, efficacy, and mechanisms of action.

Conclusions

This work takes an important step in using Semantic Web technologies to facilitate integration of relevant, distributed, external sources and progress towards a computational platform to support personalized medicine.

Availability

TMO can be downloaded from http://code.google.com/p/translationalmedicineontology and TMKB can be accessed at http://tm.semanticscience.org/sparql.