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Pregled bibliografske jedinice broj: 672539

A large-scale evaluation of computational protein function prediction


Radivojac, Predrag; ...; Škunca, Nives; Supek, Fran; Bošnjak, Matko; ...; Šmuc, Tomislav; ...; Friedberg, Iddo
A large-scale evaluation of computational protein function prediction // Nature methods, 10 (2013), 3; 221-227 doi:10.1038/nmeth.2340 (međunarodna recenzija, članak, znanstveni)


Naslov
A large-scale evaluation of computational protein function prediction

Autori
Radivojac, Predrag ; ... ; Škunca, Nives ; Supek, Fran ; Bošnjak, Matko ; ... ; Šmuc, Tomislav ; ... ; Friedberg, Iddo

Izvornik
Nature methods (1548-7091) 10 (2013), 3; 221-227

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Protein function; computational annotation; CAFA experiment

Sažetak
Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. if computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. here we report the results from the first large-scale community- based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. two findings stand out: (i) today’s best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets ; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools.

Izvorni jezik
Engleski

Znanstvena područja
Biologija, Računarstvo



POVEZANOST RADA


Projekt / tema
098-0000000-3168 - Strojno učenje prediktivnih modela u računalnoj biologiji (Tomislav Šmuc, )
098-0982560-2563 - Algoritmi strojnog učenja i njihova primjena (Dragan Gamberger, )

Ustanove
Institut "Ruđer Bošković", Zagreb

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


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