|Number of classes:||13539|
|Number of individuals:||0|
|Number of properties:||20|
|Maximum number of children:||3514|
|Average number of children:||13|
|Classes with a single child:||276|
|Classes with more than 25 children:||30|
|Classes with no definition:||13538|
|Description||This resource was designed during a PhD in medical informatics (funded by INSERM, 2010-2012). Its components are (i) a core ontology consistent with a metamodel (disorders and groups of disorders, genes, clinical signs and their relations) and (ii) an instantiation of this metamodel with Orphanet Data (available on http://orphadata.org). br> Research experiments demonstrated (i) efficient classifications generation based on SPARQL Construct, (ii) perspectives in semantic audit of a knowledge base, (iii) semantic comparison with OMIM (www.omim.org) using proximity measurements and (iv) opened perspectives in knowledge sharing (LORD, http://lord.bndmr.fr). Current production services of Orphanet developed ORDO, released in 2014, an ontology synchronized with their production database. This ontology is now available on Bioportal.|
|Contact||Ferdinand Dhombres, email@example.com|
|Submission||Release Date||Upload Date||Downloads|
|V2 (Parsed, Indexed, Metrics, Annotator)||09/11/2013||02/07/2014||OWL | CSV | RDF/XML|
In the context of prenatal diagnosis of fetal malformation,...
In the context of prenatal diagnosis of fetal malformation, knowledge of "similar'' and resolved cases (i.e. previous cases with a diagnosis validated by fetal post-mortem examination) is essential for diagnosis orientation. Therefore, access to biomedical data collected over the years by fetopathological experts is crucial.This work addresses the imperious need to gather all the fetopathological data and to make it easily accessible for an effective use of this collective memory. Our research hypothesis is that scanning fetopathological medical records will bring added value in terms of knowledge, allowing the design of a fetal abnormalities knowledge-base. The medical records will be structured and enriched by indexing using ontological and terminological resources and their links with external knowledge (publications, databases). Semantic and linguistic processes will provide access to similar cases.
Jean Charlet, Xavier Aim, Andreea Bodnari, Jean-Michel Daube,...
Jean Charlet, Xavier Aim, Andreea Bodnari, Jean-Michel Daube, Louise Delger, Ferdinand Dhombres, Egle Eensoo, Marie Gonzals, Brigitte Grau, Cyril Grouin, Marie-Christine Jaulent, Thomas Lavergne, Anne-Laure Ligozat, Jrme Mainka, Aurlie Nvol, Yves
|Inserm, Paris, France|
Linking Open Data for Rare Diseases
An integrated ORPHA browser enrich with HPO data and OMIM...
An integrated ORPHA browser enrich with HPO data and OMIM disease descriptions. The application features: 1. A RDF database with a SPARQL endpoint 2. A bigdata infrastructure allowing access to JSON objects through web services 3. a user interface written in ruby paper is available at : https://www.researchgate.net/publication/297693340_LORD_a_phenotype-genotype_semantically_integrated_biomedical_data_tool_to_support_rare_disease_diagnosis_coding_in_health_information_systems