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dc.contributor.author
Škunca, Nives
dc.contributor.author
Roberts, Richard J.
dc.contributor.author
Steffen, Martin
dc.contributor.editor
Dessimoz, Christophe
dc.contributor.editor
Škunca, Nives
dc.date.accessioned
2021-07-09T08:27:21Z
dc.date.available
2017-06-12T16:11:05Z
dc.date.available
2021-07-09T08:27:21Z
dc.date.issued
2017
dc.identifier.isbn
978-1-4939-3741-7
en_US
dc.identifier.isbn
978-1-4939-3743-1
en_US
dc.identifier.issn
1064-3745
dc.identifier.issn
1940-6029
dc.identifier.other
10.1007/978-1-4939-3743-1_8
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/122770
dc.identifier.doi
10.3929/ethz-b-000122770
dc.description.abstract
Two avenues to understanding gene function are complementary and often overlapping: experimental work and computational prediction. While experimental annotation generally produces high-quality annotations, it is low throughput. Conversely, computational annotations have broad coverage, but the quality of annotations may be variable, and therefore evaluating the quality of computational annotations is a critical concern. In this chapter, we provide an overview of strategies to evaluate the quality of computational annotations. First, we discuss why evaluating quality in this setting is not trivial. We highlight the various issues that threaten to bias the evaluation of computational annotations, most of which stem from the incompleteness of biological databases. Second, we discuss solutions that address these issues, for example, targeted selection of new experimental annotations and leveraging the existing experimental annotations.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Humana Press
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Annotation
en_US
dc.subject
Evaluation
en_US
dc.subject
Function
en_US
dc.subject
Gene ontology
en_US
dc.subject
Prediction
en_US
dc.subject
Tools
en_US
dc.title
Evaluating computational gene ontology annotations
en_US
dc.type
Book Chapter
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2016-11-04
ethz.book.title
The Gene Ontology Handbook
en_US
ethz.journal.title
Methods in Molecular Biology
ethz.journal.volume
1446
en_US
ethz.journal.abbreviated
Methods Mol Biol
ethz.pages.start
97
en_US
ethz.pages.end
109
en_US
ethz.size
13 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.scopus
ethz.publication.place
New York, NY
en_US
ethz.publication.status
published
en_US
ethz.relation.isPartOf
20.500.11850/122782
ethz.date.deposited
2017-06-12T16:15:52Z
ethz.source
ECIT
ethz.identifier.importid
imp593654e11e4d546579
ethz.ecitpid
pub:185098
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-13T15:19:18Z
ethz.rosetta.lastUpdated
2022-03-29T10:20:22Z
ethz.rosetta.versionExported
true
ethz.COinS
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