Controlled Vocabularies are standardized term lists, widely used in biological databases today. An understanding of the structure and usage of Controlled Vocabularies can improve researcher's database searches, and can assist biological programmers in standardizing many terms and analyses. Popular controlled vocabularies in biological science include Gene Ontology, MeSH, and the EC number system from the Enzyme Commission. The Open Biomedical Ontologies site provides access to many useful ontology collections for biologists and bioinformaticians, including species specific, anatomy and phenotype based ontologies.
You will learn:
This tutorial is a part of the tutorial group Text-related tools. You might find the other tutorials in the group interesting:
PubMatrix: PubMatrix, an on-line tool for multiplex literature mining of the PubMed database.
iHOP: Information Hyperlinked Over Proteins text mining resource
STRING: known and predicted protein-protein interactions
Textpresso: Text-mining the biological literature
Gene Ontology: Gene Ontology controlled vocabularies in biology
XplorMed: eXploring Medline abstracts
GoMiner: Ascribe biological significance to large lists of genes by annotating them with their corresponding GO categories
DAVID: A tool that analyzes large lists of genes to provide biological meaning
Entrez Overview: Overview of NCBI's Entrez Search Resource
PubMed: PubMed access to biomedical research literature
Literature and Text Mining : Tools which are related to scientific literature. Repositories, query tools, and mining resources are included.
More Big Data to Consider: Bioimage Informatics: I'm not sure any more when I signed up for complementary copies of Nature Methods, but just like clockwork my copy arrives each month. If you'd like toÂ get it too, you can apply for a subscription here...
New and Updated Online Tutorials for Textpresso and Gene Ontology: Comprehensive tutorials on the Gene Ontology and Textpresso databases enable researchers to quickly and effectively use these invaluable resources. Seattle, WA (PRWEB) December 8, 2008 -- OpenHelix tod...
Recent BioMed Central research articles citing this resource
Özgür Arzucan et al., The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature. BioData Mining (2016) doi:10.1186/s13040-016-0118-0
Vita Randi et al., An ontology for major histocompatibility restriction. Journal of Biomedical Semantics (2016) doi:10.1186/s13326-016-0045-5
Hicks Amanda et al., The ontology of medically related social entities: recent developments. Journal of Biomedical Semantics (2016) doi:10.1186/s13326-016-0087-8
Livingston M Kevin et al., KaBOB: ontology-based semantic integration of biomedical databases Knowledge-based analysis. BMC Bioinformatics (2015) doi:10.1186/s12859-015-0559-3
Hastings Janna et al., eNanoMapper: harnessing ontologies to enable data integration for nanomaterial risk assessment. Journal of Biomedical Semantics (2015) doi:10.1186/s13326-015-0005-5