Thematic Series on Biomedical Ontologies in JBMS: Challenges and New Directions

Overview

Journal J Biomed Semantics

Publisher Biomed Central

Specialties Biology
Biomedical Engineering

Date 2014 Mar 8

PMID 24602198

Citations 4

Authors

Robert Hoehndorf

Melissa Haendel

Robert Stevens

Dietrich Rebholz-Schuhmann

Affiliations

Soon will be listed here.

Abstract

Over the past 15 years, the biomedical research community has increased its efforts to produce ontologies encoding biomedical knowledge, and to provide the corresponding infrastructure to maintain them. As ontologies are becoming a central part of biological and biomedical research, a communication channel to publish frequent updates and latest developments on them would be an advantage. Here, we introduce the JBMS thematic series on Biomedical Ontologies. The aim of the series is to disseminate the latest developments in research on biomedical ontologies and provide a venue for publishing newly developed ontologies, updates to existing ontologies as well as methodological advances, and selected contributions from conferences and workshops. We aim to give this thematic series a central role in the exploration of ongoing research in biomedical ontologies and intend to work closely together with the research community towards this aim. Researchers and working groups are encouraged to provide feedback on novel developments and special topics to be integrated into the existing publication cycles.

Citing Articles

Consolidating drug data on a global scale using Linked Data.

Jovanovik M, Trajanov D J Biomed Semantics. 2017; 8(1):3.

PMID: 28109310 PMC: 5251285. DOI: 10.1186/s13326-016-0111-z.

Supporting the analysis of ontology evolution processes through the combination of static and dynamic scaling functions in OQuaRE.

Duque-Ramos A, Quesada-Martinez M, Iniesta-Moreno M, Fernandez-Breis J, Stevens R J Biomed Semantics. 2016; 7(1):63.

PMID: 27751176 PMC: 5067895. DOI: 10.1186/s13326-016-0091-z.

Automated concept and relationship extraction for the semi-automated ontology management (SEAM) system.

Doing-Harris K, Livnat Y, Meystre S J Biomed Semantics. 2015; 6:15.

PMID: 25874077 PMC: 4396714. DOI: 10.1186/s13326-015-0011-7.

An effective method of large scale ontology matching.

Diallo G J Biomed Semantics. 2014; 5(1):44.

PMID: 25411633 PMC: 4236493. DOI: 10.1186/2041-1480-5-44.

References

Wolstencroft K, Lord P, Tabernero L, Brass A, Stevens R . Protein classification using ontology classification. Bioinformatics. 2006; 22(14):e530-8. DOI: 10.1093/bioinformatics/btl208. View

Rebholz-Schuhmann D, Grabmuller C, Kavaliauskas S, Croset S, Woollard P, Backofen R . A case study: semantic integration of gene-disease associations for type 2 diabetes mellitus from literature and biomedical data resources. Drug Discov Today. 2013; 19(7):882-9. DOI: 10.1016/j.drudis.2013.10.024. View

Bard J, Rhee S, Ashburner M . An ontology for cell types. Genome Biol. 2005; 6(2):R21. PMC: 551541. DOI: 10.1186/gb-2005-6-2-r21. View

Pesquita C, Faria D, Falcao A, Lord P, Couto F . Semantic similarity in biomedical ontologies. PLoS Comput Biol. 2009; 5(7):e1000443. PMC: 2712090. DOI: 10.1371/journal.pcbi.1000443. View

LePendu P, Musen M, Shah N . Enabling enrichment analysis with the Human Disease Ontology. J Biomed Inform. 2011; 44 Suppl 1:S31-S38. PMC: 3392036. DOI: 10.1016/j.jbi.2011.04.007. View

Mabee P, Ashburner M, Cronk Q, Gkoutos G, Haendel M, Segerdell E . Phenotype ontologies: the bridge between genomics and evolution. Trends Ecol Evol. 2007; 22(7):345-50. DOI: 10.1016/j.tree.2007.03.013. View

Smith B, Ceusters W . Ontological realism: A methodology for coordinated evolution of scientific ontologies. Appl Ontol. 2011; 5(3-4):139-188. PMC: 3104413. DOI: 10.3233/AO-2010-0079. View

Smedley D, Oellrich A, Kohler S, Ruef B, Westerfield M, Robinson P . PhenoDigm: analyzing curated annotations to associate animal models with human diseases. Database (Oxford). 2013; 2013:bat025. PMC: 3649640. DOI: 10.1093/database/bat025. View

Chelliah V, Laibe C, Le Novere N . BioModels Database: a repository of mathematical models of biological processes. Methods Mol Biol. 2013; 1021:189-99. DOI: 10.1007/978-1-62703-450-0_10. View

10.

Niknejad A, Comte A, Parmentier G, Roux J, Bastian F, Robinson-Rechavi M . vHOG, a multispecies vertebrate ontology of homologous organs groups. Bioinformatics. 2012; 28(7):1017-20. PMC: 3315709. DOI: 10.1093/bioinformatics/bts048. View

11.

Rebholz-Schuhmann D, Oellrich A, Hoehndorf R . Text-mining solutions for biomedical research: enabling integrative biology. Nat Rev Genet. 2012; 13(12):829-39. DOI: 10.1038/nrg3337. View

12.

Belleau F, Nolin M, Tourigny N, Rigault P, Morissette J . Bio2RDF: towards a mashup to build bioinformatics knowledge systems. J Biomed Inform. 2008; 41(5):706-16. DOI: 10.1016/j.jbi.2008.03.004. View

13.

Gottlieb A, Stein G, Ruppin E, Sharan R . PREDICT: a method for inferring novel drug indications with application to personalized medicine. Mol Syst Biol. 2011; 7:496. PMC: 3159979. DOI: 10.1038/msb.2011.26. View

14.

Joshi-Tope G, Gillespie M, Vastrik I, DEustachio P, Schmidt E, de Bono B . Reactome: a knowledgebase of biological pathways. Nucleic Acids Res. 2004; 33(Database issue):D428-32. PMC: 540026. DOI: 10.1093/nar/gki072. View

15.

Washington N, Haendel M, Mungall C, Ashburner M, Westerfield M, Lewis S . Linking human diseases to animal models using ontology-based phenotype annotation. PLoS Biol. 2009; 7(11):e1000247. PMC: 2774506. DOI: 10.1371/journal.pbio.1000247. View

16.

Ferreira J, Couto F . Semantic similarity for automatic classification of chemical compounds. PLoS Comput Biol. 2010; 6(9). PMC: 2944781. DOI: 10.1371/journal.pcbi.1000937. View

17.

Kohler S, Doelken S, Mungall C, Bauer S, Firth H, Bailleul-Forestier I . The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data. Nucleic Acids Res. 2013; 42(Database issue):D966-74. PMC: 3965098. DOI: 10.1093/nar/gkt1026. View

18.

Schriml L, Arze C, Nadendla S, Chang Y, Mazaitis M, Felix V . Disease Ontology: a backbone for disease semantic integration. Nucleic Acids Res. 2011; 40(Database issue):D940-6. PMC: 3245088. DOI: 10.1093/nar/gkr972. View

19.

Lord P, Stevens R . Adding a little reality to building ontologies for biology. PLoS One. 2010; 5(9):e12258. PMC: 2933225. DOI: 10.1371/journal.pone.0012258. View

20.

Hoehndorf R, Hiebert T, Hardy N, Schofield P, Gkoutos G, Dumontier M . Mouse model phenotypes provide information about human drug targets. Bioinformatics. 2013; 30(5):719-25. PMC: 3933875. DOI: 10.1093/bioinformatics/btt613. View