Ontrez Project Report
Résumé
Currently, genomics data and data repositories in the public domain are expanding at an
explosive pace.1 The wealth of publicly accessible data is beginning to enable cross‐cutting
integrative translational bioinformatics studies [1]. However, translational discoveries that
could be made by mining such public resources are hampered if they lack standard
terminologies to describe diagnoses, diseases, and experimental conditions. For discovery to
proceed in the eras of e‐science, researchers need tools to enable them to find all the data sets
relevant to their area of study—spanning the biological scales from molecular studies to clinical
medicine—and bridging the research modalities from high‐throughput experiments to clinical
trials and medical imaging. For example, a researcher studying the allelic variations in a gene
would want to know all the pathways that are affected by that gene, the drugs whose effects
could be modulated by the allelic variations in the gene, and any disease that could be caused
by the gene, and the clinical trials that have studied drugs or diseases related to that gene. The
knowledge needed to study such questions is available in public data sets; the challenge is
finding that information.
The key challenge common to all the needs outlined above is to annotate the various
resource elements consistently to identify the biomedical concepts to which they relate.
These resource elements range from experimental data sets in public repositories, to records of
disease associations of gene products in mutation databases, to entries of clinical‐trial
descriptions. Creating ontology‐based annotations from the metadata in biomedical resources
and identifying diagnoses, pathological states, and experimental agents contained in those
resources allows indexing of the resources, enabling end users to formulate flexible searches
for biomedical data [2‐6].
In the past two months, we have been developing a system that is integrated with BioPortal
known as Ontrez.2 Ontrez enables researchers to search for biomedical data (such as genomic
data sets, medical images, clinical trials and published papers). Ontrez promotes translational
research by enabling researchers to locate relevant biological data sets and to integrate them
with clinical data to bridge the bench‐to‐bedside gap.
Ontrez processes the metadata‐annotations of gene expression data sets, descriptions of
radiology images, clinical‐trial reports, as well as abstracts of Pubmed articles to annotate (or
tag) them with terms from appropriate ontologies.
While BioPortal addresses the ontological content need of the biomedical community, Ontrez
meets the data access and data discovery need of researchers, meeting many of the specific
aims outlined in Core 2 of the NCBO grant. In fact, we envision a tight integration of BioPortal
and Ontrez as we originally proposed (Figure 1). This tight integration of ontology access and
ontology‐based applications is essential to enable the capabilities that we present in our Ontrez
use cases. In this report, we outline our methodology as well as the current status of the
project.
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RR-BMIR-2007-1289_Shah-Jonquet-Musen_Ontrez_report.pdf (1.54 Mo)
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Ontrez_report_v07.pdf (1.51 Mo)
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