183 related articles for article (PubMed ID: 27095575)
1. Altered oncomodules underlie chromatin regulatory factors driver mutations.
Frigola J; Iturbide A; Lopez-Bigas N; Peiro S; Gonzalez-Perez A
Oncotarget; 2016 May; 7(21):30748-59. PubMed ID: 27095575
[TBL] [Abstract][Full Text] [Related]
2. Identification of druggable cancer driver genes amplified across TCGA datasets.
Chen Y; McGee J; Chen X; Doman TN; Gong X; Zhang Y; Hamm N; Ma X; Higgs RE; Bhagwat SV; Buchanan S; Peng SB; Staschke KA; Yadav V; Yue Y; Kouros-Mehr H
PLoS One; 2014; 9(5):e98293. PubMed ID: 24874471
[TBL] [Abstract][Full Text] [Related]
3. OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers.
Wang T; Ruan S; Zhao X; Shi X; Teng H; Zhong J; You M; Xia K; Sun Z; Mao F
Nucleic Acids Res; 2021 Jan; 49(D1):D1289-D1301. PubMed ID: 33179738
[TBL] [Abstract][Full Text] [Related]
4. Machine Learning Classification and Structure-Functional Analysis of Cancer Mutations Reveal Unique Dynamic and Network Signatures of Driver Sites in Oncogenes and Tumor Suppressor Genes.
Agajanian S; Odeyemi O; Bischoff N; Ratra S; Verkhivker GM
J Chem Inf Model; 2018 Oct; 58(10):2131-2150. PubMed ID: 30253099
[TBL] [Abstract][Full Text] [Related]
5. Candidate Cancer Driver Mutations in Distal Regulatory Elements and Long-Range Chromatin Interaction Networks.
Zhu H; Uusküla-Reimand L; Isaev K; Wadi L; Alizada A; Shuai S; Huang V; Aduluso-Nwaobasi D; Paczkowska M; Abd-Rabbo D; Ocsenas O; Liang M; Thompson JD; Li Y; Ruan L; Krassowski M; Dzneladze I; Simpson JT; Lupien M; Stein LD; Boutros PC; Wilson MD; Reimand J
Mol Cell; 2020 Mar; 77(6):1307-1321.e10. PubMed ID: 31954095
[TBL] [Abstract][Full Text] [Related]
6. Rational design of cancer gene panels with OncoPaD.
Rubio-Perez C; Deu-Pons J; Tamborero D; Lopez-Bigas N; Gonzalez-Perez A
Genome Med; 2016 Oct; 8(1):98. PubMed ID: 27716338
[TBL] [Abstract][Full Text] [Related]
7. Molecular analysis of urothelial cancer cell lines for modeling tumor biology and drug response.
Nickerson ML; Witte N; Im KM; Turan S; Owens C; Misner K; Tsang SX; Cai Z; Wu S; Dean M; Costello JC; Theodorescu D
Oncogene; 2017 Jan; 36(1):35-46. PubMed ID: 27270441
[TBL] [Abstract][Full Text] [Related]
8. Discovering potential cancer driver genes by an integrated network-based approach.
Shi K; Gao L; Wang B
Mol Biosyst; 2016 Aug; 12(9):2921-31. PubMed ID: 27426053
[TBL] [Abstract][Full Text] [Related]
9. Mutated Chromatin Regulatory Factors as Tumor Drivers in Cancer.
Koschmann C; Nunez FJ; Mendez F; Brosnan-Cashman JA; Meeker AK; Lowenstein PR; Castro MG
Cancer Res; 2017 Jan; 77(2):227-233. PubMed ID: 28062403
[TBL] [Abstract][Full Text] [Related]
10. A computational method for clinically relevant cancer stratification and driver mutation module discovery using personal genomics profiles.
Wang L; Li F; Sheng J; Wong ST
BMC Genomics; 2015; 16 Suppl 7(Suppl 7):S6. PubMed ID: 26099165
[TBL] [Abstract][Full Text] [Related]
11. Identifying Cancer Specific Driver Modules Using a Network-Based Method.
Li F; Gao L; Wang P; Hu Y
Molecules; 2018 May; 23(5):. PubMed ID: 29738475
[TBL] [Abstract][Full Text] [Related]
12. Understanding oncogenicity of cancer driver genes and mutations in the cancer genomics era.
Porta-Pardo E; Valencia A; Godzik A
FEBS Lett; 2020 Dec; 594(24):4233-4246. PubMed ID: 32239503
[TBL] [Abstract][Full Text] [Related]
13. A Novel Method for Identifying the Potential Cancer Driver Genes Based on Molecular Data Integration.
Zhang W; Wang SL
Biochem Genet; 2020 Feb; 58(1):16-39. PubMed ID: 31115714
[TBL] [Abstract][Full Text] [Related]
14. The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes.
Lu X; Li X; Liu P; Qian X; Miao Q; Peng S
Molecules; 2018 Jan; 23(2):. PubMed ID: 29364829
[TBL] [Abstract][Full Text] [Related]
15. Frequent mutations in acetylation and ubiquitination sites suggest novel driver mechanisms of cancer.
Narayan S; Bader GD; Reimand J
Genome Med; 2016 May; 8(1):55. PubMed ID: 27175787
[TBL] [Abstract][Full Text] [Related]
16. Gene-expression signature regulated by the KEAP1-NRF2-CUL3 axis is associated with a poor prognosis in head and neck squamous cell cancer.
Namani A; Matiur Rahaman M; Chen M; Tang X
BMC Cancer; 2018 Jan; 18(1):46. PubMed ID: 29306329
[TBL] [Abstract][Full Text] [Related]
17. Deciphering oncogenic drivers: from single genes to integrated pathways.
Chen J; Sun M; Shen B
Brief Bioinform; 2015 May; 16(3):413-28. PubMed ID: 25378434
[TBL] [Abstract][Full Text] [Related]
18. MUFFINN: cancer gene discovery via network analysis of somatic mutation data.
Cho A; Shim JE; Kim E; Supek F; Lehner B; Lee I
Genome Biol; 2016 Jun; 17(1):129. PubMed ID: 27333808
[TBL] [Abstract][Full Text] [Related]
19. DEOD: uncovering dominant effects of cancer-driver genes based on a partial covariance selection method.
Amgalan B; Lee H
Bioinformatics; 2015 Aug; 31(15):2452-60. PubMed ID: 25819079
[TBL] [Abstract][Full Text] [Related]
20. The pan-cancer analysis of gain-of-functional mutations to identify the common oncogenic signatures in multiple cancers.
Wee Y; Liu Y; Bhyan SB; Lu J; Zhao M
Gene; 2019 May; 697():57-66. PubMed ID: 30796966
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
