211 related articles for article (PubMed ID: 34321661)
1. In silico saturation mutagenesis of cancer genes.
Muiños F; Martínez-Jiménez F; Pich O; Gonzalez-Perez A; Lopez-Bigas N
Nature; 2021 Aug; 596(7872):428-432. PubMed ID: 34321661
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. SB Driver Analysis: a Sleeping Beauty cancer driver analysis framework for identifying and prioritizing experimentally actionable oncogenes and tumor suppressors.
Newberg JY; Black MA; Jenkins NA; Copeland NG; Mann KM; Mann MB
Nucleic Acids Res; 2018 Sep; 46(16):e94. PubMed ID: 29846651
[TBL] [Abstract][Full Text] [Related]
4. A compendium of mutational cancer driver genes.
Martínez-Jiménez F; Muiños F; Sentís I; Deu-Pons J; Reyes-Salazar I; Arnedo-Pac C; Mularoni L; Pich O; Bonet J; Kranas H; Gonzalez-Perez A; Lopez-Bigas N
Nat Rev Cancer; 2020 Oct; 20(10):555-572. PubMed ID: 32778778
[TBL] [Abstract][Full Text] [Related]
5. The landscape of cancer genes and mutational processes in breast cancer.
Stephens PJ; Tarpey PS; Davies H; Van Loo P; Greenman C; Wedge DC; Nik-Zainal S; Martin S; Varela I; Bignell GR; Yates LR; Papaemmanuil E; Beare D; Butler A; Cheverton A; Gamble J; Hinton J; Jia M; Jayakumar A; Jones D; Latimer C; Lau KW; McLaren S; McBride DJ; Menzies A; Mudie L; Raine K; Rad R; Chapman MS; Teague J; Easton D; Langerød A; ; Lee MT; Shen CY; Tee BT; Huimin BW; Broeks A; Vargas AC; Turashvili G; Martens J; Fatima A; Miron P; Chin SF; Thomas G; Boyault S; Mariani O; Lakhani SR; van de Vijver M; van 't Veer L; Foekens J; Desmedt C; Sotiriou C; Tutt A; Caldas C; Reis-Filho JS; Aparicio SA; Salomon AV; Børresen-Dale AL; Richardson AL; Campbell PJ; Futreal PA; Stratton MR
Nature; 2012 May; 486(7403):400-4. PubMed ID: 22722201
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. LOTUS: A single- and multitask machine learning algorithm for the prediction of cancer driver genes.
Collier O; Stoven V; Vert JP
PLoS Comput Biol; 2019 Sep; 15(9):e1007381. PubMed ID: 31568528
[TBL] [Abstract][Full Text] [Related]
8. A novel heterophilic graph diffusion convolutional network for identifying cancer driver genes.
Zhang T; Zhang SW; Xie MY; Li Y
Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37055234
[TBL] [Abstract][Full Text] [Related]
9. Dynamic changes of driver genes' mutations across clinical stages in nine cancer types.
Li X
Cancer Med; 2016 Jul; 5(7):1556-65. PubMed ID: 26992457
[TBL] [Abstract][Full Text] [Related]
10. Machine learning methods for prediction of cancer driver genes: a survey paper.
Andrades R; Recamonde-Mendoza M
Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35323900
[TBL] [Abstract][Full Text] [Related]
11. Mutational landscape and significance across 12 major cancer types.
Kandoth C; McLellan MD; Vandin F; Ye K; Niu B; Lu C; Xie M; Zhang Q; McMichael JF; Wyczalkowski MA; Leiserson MDM; Miller CA; Welch JS; Walter MJ; Wendl MC; Ley TJ; Wilson RK; Raphael BJ; Ding L
Nature; 2013 Oct; 502(7471):333-339. PubMed ID: 24132290
[TBL] [Abstract][Full Text] [Related]
12. InDEP: an interpretable machine learning approach to predict cancer driver genes from multi-omics data.
Yang H; Liu Y; Yang Y; Li D; Wang Z
Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37649392
[TBL] [Abstract][Full Text] [Related]
13. Why Are Some Driver Mutations Rare?
Nussinov R; Tsai CJ; Jang H
Trends Pharmacol Sci; 2019 Dec; 40(12):919-929. PubMed ID: 31699406
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Multiscale Modeling of Inflammation-Induced Tumorigenesis Reveals Competing Oncogenic and Oncoprotective Roles for Inflammation.
Guo Y; Nie Q; MacLean AL; Li Y; Lei J; Li S
Cancer Res; 2017 Nov; 77(22):6429-6441. PubMed ID: 28951462
[TBL] [Abstract][Full Text] [Related]
16. Current cancer driver variant predictors learn to recognize driver genes instead of functional variants.
Raimondi D; Passemiers A; Fariselli P; Moreau Y
BMC Biol; 2021 Jan; 19(1):3. PubMed ID: 33441128
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Identification of Latent Oncogenes with a Network Embedding Method and Random Forest.
Zhao R; Hu B; Chen L; Zhou B
Biomed Res Int; 2020; 2020():5160396. PubMed ID: 33029511
[TBL] [Abstract][Full Text] [Related]
19. An evolution-based machine learning to identify cancer type-specific driver mutations.
Kim D; Ha D; Lee K; Lee H; Kim I; Kim S
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36575568
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
