Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

 
 
DownloadE-Mail
  Mining GO Annotations for Improving Annotation Consistency

Faria, D., Schlicker, A., Pesquita, C., Bastos, H., Ferreira, A. E. N., Albrecht, M., et al. (2012). Mining GO Annotations for Improving Annotation Consistency. PLoS One, 7(7): e40519, pp.,1-7. doi:10.1371/journal.pone.0040519.

Item is

Basisdaten

einblenden: ausblenden:
Genre: Zeitschriftenartikel
Latex : Mining {GO} Annotations for Improving Annotation Consistency

Dateien

einblenden: Dateien
ausblenden: Dateien
:
journal.pone.0040519.pdf (Verlagsversion), 92KB
Name:
journal.pone.0040519.pdf
Beschreibung:
-
OA-Status:
Sichtbarkeit:
Öffentlich
MIME-Typ / Prüfsumme:
application/pdf / [MD5]
Technische Metadaten:
Copyright Datum:
-
Copyright Info:
Copyright: 2012 Faria et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Externe Referenzen

einblenden:
ausblenden:
externe Referenz:
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3405096/ (beliebiger Volltext)
Beschreibung:
-
OA-Status:

Urheber

einblenden:
ausblenden:
 Urheber:
Faria, Daniel1, Autor
Schlicker, Andreas2, Autor           
Pesquita, Catia1, Autor
Bastos, Hugo1, Autor
Ferreira, António E. N.1, Autor
Albrecht, Mario2, Autor           
Falcao, André O.1, Autor
Affiliations:
1External Organizations, ou_persistent22              
2Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society, ou_40046              

Inhalt

einblenden:
ausblenden:
Schlagwörter: *Databases, Protein Molecular Sequence Annotation/*methods Sequence Analysis, Protein/*methods *Software
 Zusammenfassung: Despite the structure and objectivity provided by the Gene Ontology (GO), the annotation of proteins is a complex task that is subject to errors and inconsistencies. Electronically inferred annotations in particular are widely considered unreliable. However, given that manual curation of all GO annotations is unfeasible, it is imperative to improve the quality of electronically inferred annotations. In this work, we analyze the full GO molecular function annotation of UniProtKB proteins, and discuss some of the issues that affect their quality, focusing particularly on the lack of annotation consistency. Based on our analysis, we estimate that 64% of the UniProtKB proteins are incompletely annotated, and that inconsistent annotations affect 83% of the protein functions and at least 23% of the proteins. Additionally, we present and evaluate a data mining algorithm, based on the association rule learning methodology, for identifying implicit relationships between molecular function terms. The goal of this algorithm is to assist GO curators in updating GO and correcting and preventing inconsistent annotations. Our algorithm predicted 501 relationships with an estimated precision of 94%, whereas the basic association rule learning methodology predicted 12,352 relationships with a precision below 9%.

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 2012-07-25
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: PMID: 22848383
PMC: PMC3405096
DOI: 10.1371/journal.pone.0040519
URI: http://www.ncbi.nlm.nih.gov/pubmed/22848383
BibTex Citekey: Albrecht2012d
Anderer: Local-ID: 41B05E900499D8FAC1257AD900397AD0-Albrecht2012d
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: PLoS One
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: San Francisco, CA : Public Library of Science
Seiten: - Band / Heft: 7 (7) Artikelnummer: e40519 Start- / Endseite: ,1 - 7 Identifikator: ISSN: 1932-6203
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277850