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Pregled bibliografske jedinice broj: 823971

MUFFINN: cancer gene discovery via network analysis of somatic mutation data


Cho, Ara; Shim, Jung Eun; Kim, Eiru; Supek, Fran; Lehner, Ben; Lee, Insuk
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:

Avatar Url Fran Supek (autor)

Poveznice na cjeloviti tekst rada:

doi genomebiology.biomedcentral.com

Citiraj ovu publikaciju:

Cho, Ara; Shim, Jung Eun; Kim, Eiru; Supek, Fran; Lehner, Ben; Lee, Insuk
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)
Cho, A., Shim, J., Kim, E., Supek, F., Lehner, B. & Lee, I. (2016) MUFFINN: cancer gene discovery via network analysis of somatic mutation data. Genome biology, 17, 129, 16 doi:10.1186/s13059-016-0989-x.
@article{article, author = {Cho, Ara and Shim, Jung Eun and Kim, Eiru and Supek, Fran and Lehner, Ben and Lee, Insuk}, year = {2016}, pages = {16}, DOI = {10.1186/s13059-016-0989-x}, chapter = {129}, keywords = {Cancer gene prediction, Cancer somatic mutation, Cancer genomes, Mutation frequency, Functional gene network, Pathway-centric analysis}, journal = {Genome biology}, doi = {10.1186/s13059-016-0989-x}, volume = {17}, issn = {1474-7596}, title = {MUFFINN: cancer gene discovery via network analysis of somatic mutation data}, keyword = {Cancer gene prediction, Cancer somatic mutation, Cancer genomes, Mutation frequency, Functional gene network, Pathway-centric analysis}, chapternumber = {129} }
@article{article, author = {Cho, Ara and Shim, Jung Eun and Kim, Eiru and Supek, Fran and Lehner, Ben and Lee, Insuk}, year = {2016}, pages = {16}, DOI = {10.1186/s13059-016-0989-x}, chapter = {129}, keywords = {Cancer gene prediction, Cancer somatic mutation, Cancer genomes, Mutation frequency, Functional gene network, Pathway-centric analysis}, journal = {Genome biology}, doi = {10.1186/s13059-016-0989-x}, volume = {17}, issn = {1474-7596}, title = {MUFFINN: cancer gene discovery via network analysis of somatic mutation data}, keyword = {Cancer gene prediction, Cancer somatic mutation, Cancer genomes, Mutation frequency, Functional gene network, Pathway-centric analysis}, chapternumber = {129} }

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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