TMO/TMKB Paper Available Online

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