Pregled bibliografske jedinice broj: 823971
MUFFINN: cancer gene discovery via network analysis of somatic mutation data
MUFFINN: cancer gene discovery via network analysis of somatic mutation data // Genome biology, 17 (2016), 129, 16 doi:10.1186/s13059-016-0989-x (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 823971 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
MUFFINN: cancer gene discovery via network analysis of somatic mutation data
Autori
Cho, Ara ; Shim, Jung Eun ; Kim, Eiru ; Supek, Fran ; Lehner, Ben ; Lee, Insuk
Izvornik
Genome biology (1474-7596) 17
(2016);
129, 16
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Cancer gene prediction ; Cancer somatic mutation ; Cancer genomes ; Mutation frequency ; Functional gene network ; Pathway-centric analysis
Sažetak
A major challenge for distinguishing cancer-causing driver mutations from inconsequential passenger mutations is the long-tail of infrequently mutated genes in cancer genomes. Here, we present and evaluate a method for prioritizing cancer genes accounting not only for mutations in individual genes but also in their neighbors in functional networks, MUFFINN (MUtations For Functional Impact on Network Neighbors). This pathway-centric method shows high sensitivity compared with gene-centric analyses of mutation data. Notably, only a marginal decrease in performance is observed when using 10 % of TCGA patient samples, suggesting the method may potentiate cancer genome projects with small patient populations.
Izvorni jezik
Engleski
Znanstvena područja
Biologija, Računarstvo
POVEZANOST RADA
Projekti:
098-0000000-3168 - Strojno učenje prediktivnih modela u računalnoj biologiji (Šmuc, Tomislav, MZOS ) ( CroRIS)
ICT-2013-612944
HRZZ-IP-2013-11-9623 - Postupci strojnog učenja za dubinsku analizu složenih struktura podataka (DescriptiveInduction) (Gamberger, Dragan, HRZZ - 2013-11) ( CroRIS)
Ustanove:
Institut "Ruđer Bošković", Zagreb
Profili:
Fran Supek
(autor)
Citiraj ovu publikaciju:
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