Cargando…
Evaluating Functional Annotations of Enzymes Using the Gene Ontology
The Gene Ontology (GO) (Ashburner et al., Nat Genet 25(1):25–29, 2000) is a powerful tool in the informatics arsenal of methods for evaluating annotations in a protein dataset. From identifying the nearest well annotated homologue of a protein of interest to predicting where misannotation has occurr...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837055/ https://www.ncbi.nlm.nih.gov/pubmed/27812939 http://dx.doi.org/10.1007/978-1-4939-3743-1_9 |
_version_ | 1783304051031539712 |
---|---|
author | Holliday, Gemma L. Davidson, Rebecca Akiva, Eyal Babbitt, Patricia C. |
author_facet | Holliday, Gemma L. Davidson, Rebecca Akiva, Eyal Babbitt, Patricia C. |
author_sort | Holliday, Gemma L. |
collection | PubMed |
description | The Gene Ontology (GO) (Ashburner et al., Nat Genet 25(1):25–29, 2000) is a powerful tool in the informatics arsenal of methods for evaluating annotations in a protein dataset. From identifying the nearest well annotated homologue of a protein of interest to predicting where misannotation has occurred to knowing how confident you can be in the annotations assigned to those proteins is critical. In this chapter we explore what makes an enzyme unique and how we can use GO to infer aspects of protein function based on sequence similarity. These can range from identification of misannotation or other errors in a predicted function to accurate function prediction for an enzyme of entirely unknown function. Although GO annotation applies to any gene products, we focus here a describing our approach for hierarchical classification of enzymes in the Structure-Function Linkage Database (SFLD) (Akiva et al., Nucleic Acids Res 42(Database issue):D521–530, 2014) as a guide for informed utilisation of annotation transfer based on GO terms. |
format | Online Article Text |
id | pubmed-5837055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
record_format | MEDLINE/PubMed |
spelling | pubmed-58370552018-03-05 Evaluating Functional Annotations of Enzymes Using the Gene Ontology Holliday, Gemma L. Davidson, Rebecca Akiva, Eyal Babbitt, Patricia C. Methods Mol Biol Article The Gene Ontology (GO) (Ashburner et al., Nat Genet 25(1):25–29, 2000) is a powerful tool in the informatics arsenal of methods for evaluating annotations in a protein dataset. From identifying the nearest well annotated homologue of a protein of interest to predicting where misannotation has occurred to knowing how confident you can be in the annotations assigned to those proteins is critical. In this chapter we explore what makes an enzyme unique and how we can use GO to infer aspects of protein function based on sequence similarity. These can range from identification of misannotation or other errors in a predicted function to accurate function prediction for an enzyme of entirely unknown function. Although GO annotation applies to any gene products, we focus here a describing our approach for hierarchical classification of enzymes in the Structure-Function Linkage Database (SFLD) (Akiva et al., Nucleic Acids Res 42(Database issue):D521–530, 2014) as a guide for informed utilisation of annotation transfer based on GO terms. 2017 /pmc/articles/PMC5837055/ /pubmed/27812939 http://dx.doi.org/10.1007/978-1-4939-3743-1_9 Text en http://creativecommons.org/licenses/by/4.0/ This chapter is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, a link is provided to the Creative Commons license and any changes made are indicated. |
spellingShingle | Article Holliday, Gemma L. Davidson, Rebecca Akiva, Eyal Babbitt, Patricia C. Evaluating Functional Annotations of Enzymes Using the Gene Ontology |
title | Evaluating Functional Annotations of Enzymes Using the Gene Ontology |
title_full | Evaluating Functional Annotations of Enzymes Using the Gene Ontology |
title_fullStr | Evaluating Functional Annotations of Enzymes Using the Gene Ontology |
title_full_unstemmed | Evaluating Functional Annotations of Enzymes Using the Gene Ontology |
title_short | Evaluating Functional Annotations of Enzymes Using the Gene Ontology |
title_sort | evaluating functional annotations of enzymes using the gene ontology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837055/ https://www.ncbi.nlm.nih.gov/pubmed/27812939 http://dx.doi.org/10.1007/978-1-4939-3743-1_9 |
work_keys_str_mv | AT hollidaygemmal evaluatingfunctionalannotationsofenzymesusingthegeneontology AT davidsonrebecca evaluatingfunctionalannotationsofenzymesusingthegeneontology AT akivaeyal evaluatingfunctionalannotationsofenzymesusingthegeneontology AT babbittpatriciac evaluatingfunctionalannotationsofenzymesusingthegeneontology |