308 related articles for article (PubMed ID: 23383675)
41. Identification of High-Impact cis-Regulatory Mutations Using Transcription Factor Specific Random Forest Models.
Svetlichnyy D; Imrichova H; Fiers M; Kalender Atak Z; Aerts S
PLoS Comput Biol; 2015 Nov; 11(11):e1004590. PubMed ID: 26562774
[TBL] [Abstract][Full Text] [Related]
42. VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data.
Jia P; Zhao Z
PLoS Comput Biol; 2014 Feb; 10(2):e1003460. PubMed ID: 24516372
[TBL] [Abstract][Full Text] [Related]
43. SomInaClust: detection of cancer genes based on somatic mutation patterns of inactivation and clustering.
Van den Eynden J; Fierro AC; Verbeke LP; Marchal K
BMC Bioinformatics; 2015 Apr; 16():125. PubMed ID: 25903787
[TBL] [Abstract][Full Text] [Related]
44. Alterations in transcriptional networks in cancer: the role of noncoding somatic driver mutations.
Doane AS; Elemento O
Curr Opin Genet Dev; 2022 Aug; 75():101919. PubMed ID: 35609422
[TBL] [Abstract][Full Text] [Related]
45. De novo discovery of mutated driver pathways in cancer.
Vandin F; Upfal E; Raphael BJ
Genome Res; 2012 Feb; 22(2):375-85. PubMed ID: 21653252
[TBL] [Abstract][Full Text] [Related]
46. e-MutPath: computational modeling reveals the functional landscape of genetic mutations rewiring interactome networks.
Li Y; Burgman B; Khatri IS; Pentaparthi SR; Su Z; McGrail DJ; Li Y; Wu E; Eckhardt SG; Sahni N; Yi SS
Nucleic Acids Res; 2021 Jan; 49(1):e2. PubMed ID: 33211847
[TBL] [Abstract][Full Text] [Related]
47. Individualized discovery of rare cancer drivers in global network context.
Petrov I; Alexeyenko A
Elife; 2022 May; 11():. PubMed ID: 35593700
[TBL] [Abstract][Full Text] [Related]
48. 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]
49. Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.
Cava C; Bertoli G; Colaprico A; Olsen C; Bontempi G; Castiglioni I
BMC Genomics; 2018 Jan; 19(1):25. PubMed ID: 29304754
[TBL] [Abstract][Full Text] [Related]
50. Cancer driver gene discovery through an integrative genomics approach in a non-parametric Bayesian framework.
Yang H; Wei Q; Zhong X; Yang H; Li B
Bioinformatics; 2017 Feb; 33(4):483-490. PubMed ID: 27797769
[TBL] [Abstract][Full Text] [Related]
51. Predicting the functional consequences of cancer-associated amino acid substitutions.
Shihab HA; Gough J; Cooper DN; Day IN; Gaunt TR
Bioinformatics; 2013 Jun; 29(12):1504-10. PubMed ID: 23620363
[TBL] [Abstract][Full Text] [Related]
52. Detection of gene communities in multi-networks reveals cancer drivers.
Cantini L; Medico E; Fortunato S; Caselle M
Sci Rep; 2015 Dec; 5():17386. PubMed ID: 26639632
[TBL] [Abstract][Full Text] [Related]
53. Improving existing analysis pipeline to identify and analyze cancer driver genes using multi-omics data.
Nguyen QH; Le DH
Sci Rep; 2020 Nov; 10(1):20521. PubMed ID: 33239644
[TBL] [Abstract][Full Text] [Related]
54. Snowball: resampling combined with distance-based regression to discover transcriptional consequences of a driver mutation.
Xu Y; Guo X; Sun J; Zhao Z
Bioinformatics; 2015 Jan; 31(1):84-93. PubMed ID: 25192743
[TBL] [Abstract][Full Text] [Related]
55. Whole-exome sequencing reveals recurrent somatic mutation networks in cancer.
Liu X; Wang J; Chen L
Cancer Lett; 2013 Nov; 340(2):270-6. PubMed ID: 23153794
[TBL] [Abstract][Full Text] [Related]
56. Adaptation of a mutual exclusivity framework to identify driver mutations within oncogenic pathways.
Wang X; Kostrzewa C; Reiner A; Shen R; Begg C
Am J Hum Genet; 2024 Feb; 111(2):227-241. PubMed ID: 38232729
[TBL] [Abstract][Full Text] [Related]
57. 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]
58. Cancer-mutation network and the number and specificity of driver mutations.
Iranzo J; Martincorena I; Koonin EV
Proc Natl Acad Sci U S A; 2018 Jun; 115(26):E6010-E6019. PubMed ID: 29895694
[TBL] [Abstract][Full Text] [Related]
59. Uncovering driver genes in breast cancer through an innovative machine learning mutational analysis method.
Taheri G; Habibi M
Comput Biol Med; 2024 Mar; 171():108234. PubMed ID: 38430742
[TBL] [Abstract][Full Text] [Related]
60. Evaluating the evaluation of cancer driver genes.
Tokheim CJ; Papadopoulos N; Kinzler KW; Vogelstein B; Karchin R
Proc Natl Acad Sci U S A; 2016 Dec; 113(50):14330-14335. PubMed ID: 27911828
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
