Ontrez Project Report - LARA - Libre accès aux rapports scientifiques et techniques Accéder directement au contenu
Rapport Année : 2007

Ontrez Project Report


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.
Fichier principal
Vignette du fichier
RR-BMIR-2007-1289_Shah-Jonquet-Musen_Ontrez_report.pdf (1.54 Mo) Télécharger le fichier
Ontrez_report_v07.pdf (1.51 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04312974 , version 1 (07-12-2023)


  • HAL Id : hal-04312974 , version 1


Nigam H. Shah, Clement Jonquet. Ontrez Project Report. Stanford University. 2007, pp.BMIR-2007-1289. ⟨hal-04312974⟩


10 Consultations
1 Téléchargements


Gmail Facebook X LinkedIn More