239 related articles for article (PubMed ID: 26304545)
1. LARVA: an integrative framework for large-scale analysis of recurrent variants in noncoding annotations.
Lochovsky L; Zhang J; Fu Y; Khurana E; Gerstein M
Nucleic Acids Res; 2015 Sep; 43(17):8123-34. PubMed ID: 26304545
[TBL] [Abstract][Full Text] [Related]
2. NIMBus: a negative binomial regression based Integrative Method for mutation Burden Analysis.
Zhang J; Liu J; McGillivray P; Yi C; Lochovsky L; Lee D; Gerstein M
BMC Bioinformatics; 2020 Oct; 21(1):474. PubMed ID: 33092526
[TBL] [Abstract][Full Text] [Related]
3. Identification of coding and non-coding mutational hotspots in cancer genomes.
Piraino SW; Furney SJ
BMC Genomics; 2017 Jan; 18(1):17. PubMed ID: 28056774
[TBL] [Abstract][Full Text] [Related]
4. MOAT: efficient detection of highly mutated regions with the Mutations Overburdening Annotations Tool.
Lochovsky L; Zhang J; Gerstein M
Bioinformatics; 2018 Mar; 34(6):1031-1033. PubMed ID: 29121169
[TBL] [Abstract][Full Text] [Related]
5. Functional annotation of noncoding mutations in cancer.
Umer HM; Smolinska K; Komorowski J; Wadelius C
Life Sci Alliance; 2021 Sep; 4(9):. PubMed ID: 34282050
[TBL] [Abstract][Full Text] [Related]
6. IW-Scoring: an Integrative Weighted Scoring framework for annotating and prioritizing genetic variations in the noncoding genome.
Wang J; Dayem Ullah AZ; Chelala C
Nucleic Acids Res; 2018 May; 46(8):e47. PubMed ID: 29390075
[TBL] [Abstract][Full Text] [Related]
7. Whole-genome mutational landscape and characterization of noncoding and structural mutations in liver cancer.
Fujimoto A; Furuta M; Totoki Y; Tsunoda T; Kato M; Shiraishi Y; Tanaka H; Taniguchi H; Kawakami Y; Ueno M; Gotoh K; Ariizumi S; Wardell CP; Hayami S; Nakamura T; Aikata H; Arihiro K; Boroevich KA; Abe T; Nakano K; Maejima K; Sasaki-Oku A; Ohsawa A; Shibuya T; Nakamura H; Hama N; Hosoda F; Arai Y; Ohashi S; Urushidate T; Nagae G; Yamamoto S; Ueda H; Tatsuno K; Ojima H; Hiraoka N; Okusaka T; Kubo M; Marubashi S; Yamada T; Hirano S; Yamamoto M; Ohdan H; Shimada K; Ishikawa O; Yamaue H; Chayama K; Miyano S; Aburatani H; Shibata T; Nakagawa H
Nat Genet; 2016 May; 48(5):500-9. PubMed ID: 27064257
[TBL] [Abstract][Full Text] [Related]
8. Genome-wide analysis of noncoding regulatory mutations in cancer.
Weinhold N; Jacobsen A; Schultz N; Sander C; Lee W
Nat Genet; 2014 Nov; 46(11):1160-5. PubMed ID: 25261935
[TBL] [Abstract][Full Text] [Related]
9. Combined burden and functional impact tests for cancer driver discovery using DriverPower.
Shuai S; ; Gallinger S; Stein LD;
Nat Commun; 2020 Feb; 11(1):734. PubMed ID: 32024818
[TBL] [Abstract][Full Text] [Related]
10. Using FunSeq2 for Coding and Non-Coding Variant Annotation and Prioritization.
Dhingra P; Fu Y; Gerstein M; Khurana E
Curr Protoc Bioinformatics; 2017 May; 57():15.11.1-15.11.17. PubMed ID: 28463398
[TBL] [Abstract][Full Text] [Related]
11. FunSeq2: a framework for prioritizing noncoding regulatory variants in cancer.
Fu Y; Liu Z; Lou S; Bedford J; Mu XJ; Yip KY; Khurana E; Gerstein M
Genome Biol; 2014; 15(10):480. PubMed ID: 25273974
[TBL] [Abstract][Full Text] [Related]
12. Epigenomic annotation of noncoding mutations identifies mutated pathways in primary liver cancer.
Lowdon RF; Wang T
PLoS One; 2017; 12(3):e0174032. PubMed ID: 28333948
[TBL] [Abstract][Full Text] [Related]
13. Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations.
Araya CL; Cenik C; Reuter JA; Kiss G; Pande VS; Snyder MP; Greenleaf WJ
Nat Genet; 2016 Feb; 48(2):117-25. PubMed ID: 26691984
[TBL] [Abstract][Full Text] [Related]
14. Chromatin structure-based prediction of recurrent noncoding mutations in cancer.
Kim K; Jang K; Yang W; Choi EY; Park SM; Bae M; Kim YJ; Choi JK
Nat Genet; 2016 Nov; 48(11):1321-1326. PubMed ID: 27723759
[TBL] [Abstract][Full Text] [Related]
15. A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.
Bertl J; Guo Q; Juul M; Besenbacher S; Nielsen MM; Hornshøj H; Pedersen JS; Hobolth A
BMC Bioinformatics; 2018 Apr; 19(1):147. PubMed ID: 29673314
[TBL] [Abstract][Full Text] [Related]
16. SMuRF: a novel tool to identify regulatory elements enriched for somatic point mutations.
Guilhamon P; Lupien M
BMC Bioinformatics; 2018 Nov; 19(1):454. PubMed ID: 30477433
[TBL] [Abstract][Full Text] [Related]
17. Recurrent somatic mutations in regulatory regions of human cancer genomes.
Melton C; Reuter JA; Spacek DV; Snyder M
Nat Genet; 2015 Jul; 47(7):710-6. PubMed ID: 26053494
[TBL] [Abstract][Full Text] [Related]
18. Pan-cancer noncoding genomic analysis identifies functional
He Z; Wu T; Wang S; Zhang J; Sun X; Tao Z; Zhao X; Li H; Wu K; Liu XS
iScience; 2021 Apr; 24(4):102285. PubMed ID: 33851100
[TBL] [Abstract][Full Text] [Related]
19. CScape: a tool for predicting oncogenic single-point mutations in the cancer genome.
Rogers MF; Shihab HA; Gaunt TR; Campbell C
Sci Rep; 2017 Sep; 7(1):11597. PubMed ID: 28912487
[TBL] [Abstract][Full Text] [Related]
20. Dr.Nod: computational framework for discovery of regulatory non-coding drivers in tissue-matched distal regulatory elements.
Tomkova M; Tomek J; Chow J; McPherson JD; Segal DJ; Hormozdiari F
Nucleic Acids Res; 2023 Feb; 51(4):e23. PubMed ID: 36625266
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
