Olivier Bodenreider

ORCID: 0000-0003-4769-4217
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • Biomedical Text Mining and Ontologies
  • Semantic Web and Ontologies
  • Natural Language Processing Techniques
  • Bioinformatics and Genomic Networks
  • linguistics and terminology studies
  • Topic Modeling
  • Genomics and Rare Diseases
  • Computational Drug Discovery Methods
  • Electronic Health Records Systems
  • Scientific Computing and Data Management
  • Genetics, Bioinformatics, and Biomedical Research
  • Pharmacovigilance and Adverse Drug Reactions
  • Advanced Text Analysis Techniques
  • Gene expression and cancer classification
  • Clinical practice guidelines implementation
  • Medical Coding and Health Information
  • Nutrition, Genetics, and Disease
  • Service-Oriented Architecture and Web Services
  • Business Process Modeling and Analysis
  • Data Quality and Management
  • Advanced Database Systems and Queries
  • Rough Sets and Fuzzy Logic
  • Gene Regulatory Network Analysis
  • Pharmaceutical Practices and Patient Outcomes
  • Biosimilars and Bioanalytical Methods

National Institutes of Health
2014-2023

United States National Library of Medicine
2014-2023

National Center for Biotechnology Information
2010-2022

Center for Devices and Radiological Health
2010

University of Maryland, Baltimore County
2010

United States Food and Drug Administration
2010

Erasmus MC
2009

University Medical Center Freiburg
2009

United States Department of Health and Human Services
2006

Université de Rennes
2003

The Unified Medical Language System ( http://umlsks.nlm.nih.gov ) is a repository of biomedical vocabularies developed by the US National Library Medicine. UMLS integrates over 2 million names for some 900 000 concepts from more than 60 families vocabularies, as well 12 relations among these concepts. Vocabularies integrated in Metathesaurus include NCBI taxonomy, Gene Ontology, Subject Headings (MeSH), OMIM and Digital Anatomist Symbolic Knowledge Base. are not only inter‐related, but may...

10.1093/nar/gkh061 article EN Nucleic Acids Research 2003-12-17

To provide typical examples of biomedical ontologies in action, emphasizing the role played by knowledge management, data integration and decision support.Biomedical selected for their practical impact are examined from a functional perspective. Examples applications taken operational systems literature, with bias towards recent journal articles.The under investigation this survey include SNOMED CT, Logical Observation Identifiers, Names, Codes (LOINC), Foundational Model Anatomy, Gene...

10.1055/s-0038-1638585 article EN other-oa Yearbook of Medical Informatics 2008-08-01

Statements about RDF statements, or meta triples, provide additional information individual such as the source, occurring time place, certainty. Integrating triples into semantic knowledge bases would enable querying and reasoning mechanisms to be aware of provenance, time, location, certainty triples. However, an efficient representation for remains challenging. The existing standard reification approach allows expressed using by two steps. first step is representing triple a Statement...

10.1145/2566486.2567973 article EN 2014-04-07

10.1016/j.jbi.2003.11.002 article EN publisher-specific-oa Journal of Biomedical Informatics 2003-12-01

The gene ontology and annotations derived from the S.cerivisiae genome database were analyzed to calculate functional similarity of products. Three methods for measuring (including a distance-based approach) implemented. Significant, quantitative relationships between expression correlation pairs genes detected. Using known dataset in yeast, this study compared more than three million products on basis these properties. Highly correlated exhibit strong based information originating...

10.1109/cibcb.2004.1393927 article EN 2005-03-21

Abstract Motivation: A major goal of biomedical research in personalized medicine is to find relationships between mutations and their corresponding disease phenotypes. However, most the disease-related mutational data are currently buried literature textual form lack necessary structure allow easy retrieval visualization. We introduce a high-throughput computational method for identification relevant PubMed abstracts applied prostate (PCa) breast cancer (BCa) mutations. Results: developed...

10.1093/bioinformatics/btq667 article EN Bioinformatics 2010-12-07

Abstract Background Translational medicine requires the integration of knowledge using heterogeneous data from health care to life sciences. Here, we describe a collaborative effort produce prototype Medicine Knowledge Base (TMKB) capable answering questions relating clinical practice and pharmaceutical drug discovery. Results We developed Ontology (TMO) as unifying ontology integrate chemical, genomic proteomic with disease, treatment, electronic records. demonstrate use Semantic Web...

10.1186/2041-1480-2-s2-s1 article EN cc-by Journal of Biomedical Semantics 2011-05-17

To study the newly adopted International Classification of Diseases 11th revision (ICD-11) and compare it to 10th (ICD-10) revision-Clinical Modification (ICD-10-CM).: Data files maps were downloaded from World Health Organization (WHO) website through application programming interfaces. A round trip method based on WHO was used identify equivalent codes between ICD-10 ICD-11, which validated by limited manual review. ICD-11 terms mapped ICD-10-CM normalized lexical mapping. in 6 disease...

10.1093/jamia/ocaa030 article EN public-domain Journal of the American Medical Informatics Association 2020-03-09

The national mandate for health systems to transition from ICD-9-CM ICD-10-CM in October 2015 has an impact on research activities. Clinical phenotypes defined by codes need be converted ICD-10-CM, which nearly four times more and a very different structure than ICD-9-CM.We used the Centers Medicare & Medicaid Services (CMS) General Equivalent Maps (GEMs) translate, using methods, condition-specific code sets pragmatic trials (n=32) into ICD-10-CM. We calculated recall, precision, F score of...

10.13063/2327-9214.1211 article EN eGEMs (Generating Evidence & Methods to improve patient outcomes) 2016-04-12

Abstract Objective: To compare 3 commercial knowledge bases (KBs) used for detection and avoidance of potential drug-drug interactions (DDIs) in clinical practice. Methods: Drugs the DDI tables from First DataBank (FDB), Micromedex, Multum were mapped to RxNorm. The KBs compared at drug, ingredient, rule levels. evaluated against a reference list highly significant DDIs Office National Coordinator Health Information Technology (ONC). ONC applied prescription data set simulate their use...

10.1093/jamia/ocx010 article EN public-domain Journal of the American Medical Informatics Association 2017-01-30

The objective of this article is to recapitulate our experience in aligning large anatomical ontologies (Foundational Model Anatomy, GALEN, Adult Mouse Anatomical Dictionary and NCI Thesaurus) having different representation formalisms. Our approach concepts (directly) automatic, rule-based, operates at the schema level, generating mostly point-to-point mappings. It uses a combination lexical, structural semantic techniques. also takes advantage domain-specific knowledge (lexical from...

10.4018/jswis.2007040101 article EN International Journal on Semantic Web and Information Systems 2007-04-01

To review the issues that have arisen with advent of translational research in terms integration data and knowledge, survey current efforts to address these issues.Using examples form biomedical literature, we identified new trends their impact on bioinformatics. We analyzed requirements for effective knowledge repositories studied knowledge.New diagnostic therapeutic approaches based gene expression patterns brought about statistical analysis data, workflows are needed support research....

10.1055/s-0038-1638588 article EN Yearbook of Medical Informatics 2008-08-01

Abstract Objective: Quality assurance of large ontological systems such as SNOMED CT is an indispensable part the terminology management lifecycle. We introduce a hybrid structural-lexical method for scalable and systematic discovery missing hierarchical relations concepts in CT. Material Methods: All non-lattice subgraphs (the structural part) are exhaustively extracted using MapReduce algorithm. Four lexical patterns identified among subgraphs. Non-lattice exhibiting often indicative or...

10.1093/jamia/ocw175 article EN cc-by-nc-nd Journal of the American Medical Informatics Association 2016-12-03

Phenotypes have gained increased notoriety in the clinical and biological domain owing to their application numerous areas such as discovery of disease genes drug targets, phylogenetics pharmacogenomics. Phenotypes, defined observable characteristics organisms, can be seen one bridges that lead a translation experimental findings into applications thereby support 'bench bedside' efforts. However, build this translational bridge, common universal understanding phenotypes is required goes...

10.1093/bib/bbv083 article EN cc-by Briefings in Bioinformatics 2015-09-29
Coming Soon ...