156 related articles for article (PubMed ID: 34556174)
1. ACE: a probabilistic model for characterizing gene-level essentiality in CRISPR screens.
Hutton ER; Vakoc CR; Siepel A
Genome Biol; 2021 Sep; 22(1):278. PubMed ID: 34556174
[TBL] [Abstract][Full Text] [Related]
2. Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting.
Iorio F; Behan FM; Gonçalves E; Bhosle SG; Chen E; Shepherd R; Beaver C; Ansari R; Pooley R; Wilkinson P; Harper S; Butler AP; Stronach EA; Saez-Rodriguez J; Yusa K; Garnett MJ
BMC Genomics; 2018 Aug; 19(1):604. PubMed ID: 30103702
[TBL] [Abstract][Full Text] [Related]
3. Quality control, modeling, and visualization of CRISPR screens with MAGeCK-VISPR.
Li W; Köster J; Xu H; Chen CH; Xiao T; Liu JS; Brown M; Liu XS
Genome Biol; 2015 Dec; 16():281. PubMed ID: 26673418
[TBL] [Abstract][Full Text] [Related]
4. Improved analysis of CRISPR fitness screens and reduced off-target effects with the BAGEL2 gene essentiality classifier.
Kim E; Hart T
Genome Med; 2021 Jan; 13(1):2. PubMed ID: 33407829
[TBL] [Abstract][Full Text] [Related]
5. Network analysis of gene essentiality in functional genomics experiments.
Jiang P; Wang H; Li W; Zang C; Li B; Wong YJ; Meyer C; Liu JS; Aster JC; Liu XS
Genome Biol; 2015 Oct; 16():239. PubMed ID: 26518695
[TBL] [Abstract][Full Text] [Related]
6. A CRISPR-based method for testing the essentiality of a gene.
You Y; Ramachandra SG; Jin T
Sci Rep; 2020 Sep; 10(1):14779. PubMed ID: 32901070
[TBL] [Abstract][Full Text] [Related]
7. Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells.
Meyers RM; Bryan JG; McFarland JM; Weir BA; Sizemore AE; Xu H; Dharia NV; Montgomery PG; Cowley GS; Pantel S; Goodale A; Lee Y; Ali LD; Jiang G; Lubonja R; Harrington WF; Strickland M; Wu T; Hawes DC; Zhivich VA; Wyatt MR; Kalani Z; Chang JJ; Okamoto M; Stegmaier K; Golub TR; Boehm JS; Vazquez F; Root DE; Hahn WC; Tsherniak A
Nat Genet; 2017 Dec; 49(12):1779-1784. PubMed ID: 29083409
[TBL] [Abstract][Full Text] [Related]
8. Inferring cancer dependencies on metabolic genes from large-scale genetic screens.
Lagziel S; Lee WD; Shlomi T
BMC Biol; 2019 Apr; 17(1):37. PubMed ID: 31039782
[TBL] [Abstract][Full Text] [Related]
9. Discovery of rice essential genes by characterizing a CRISPR-edited mutation of closely related rice MAP kinase genes.
Minkenberg B; Xie K; Yang Y
Plant J; 2017 Feb; 89(3):636-648. PubMed ID: 27747971
[TBL] [Abstract][Full Text] [Related]
10. A High-Resolution Genome-Wide CRISPR/Cas9 Viability Screen Reveals Structural Features and Contextual Diversity of the Human Cell-Essential Proteome.
Bertomeu T; Coulombe-Huntington J; Chatr-Aryamontri A; Bourdages KG; Coyaud E; Raught B; Xia Y; Tyers M
Mol Cell Biol; 2018 Jan; 38(1):. PubMed ID: 29038160
[TBL] [Abstract][Full Text] [Related]
11. An interactive web application for processing, correcting, and visualizing genome-wide pooled CRISPR-Cas9 screens.
Vinceti A; De Lucia RR; Cremaschi P; Perron U; Karakoc E; Mauri L; Fernandez C; Kluczynski KH; Anderson DS; Iorio F
Cell Rep Methods; 2023 Jan; 3(1):100373. PubMed ID: 36814834
[TBL] [Abstract][Full Text] [Related]
12. MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens.
Li W; Xu H; Xiao T; Cong L; Love MI; Zhang F; Irizarry RA; Liu JS; Brown M; Liu XS
Genome Biol; 2014; 15(12):554. PubMed ID: 25476604
[TBL] [Abstract][Full Text] [Related]
13. Genome-scale CRISPR screening at high sensitivity with an empirically designed sgRNA library.
Henkel L; Rauscher B; Schmitt B; Winter J; Boutros M
BMC Biol; 2020 Nov; 18(1):174. PubMed ID: 33228647
[TBL] [Abstract][Full Text] [Related]
14. Combined gene essentiality scoring improves the prediction of cancer dependency maps.
Wang W; Malyutina A; Pessia A; Saarela J; Heckman CA; Tang J
EBioMedicine; 2019 Dec; 50():67-80. PubMed ID: 31732481
[TBL] [Abstract][Full Text] [Related]
15. Genome-wide CRISPR-dCas9 screens in E. coli identify essential genes and phage host factors.
Rousset F; Cui L; Siouve E; Becavin C; Depardieu F; Bikard D
PLoS Genet; 2018 Nov; 14(11):e1007749. PubMed ID: 30403660
[TBL] [Abstract][Full Text] [Related]
16. Recovering false negatives in CRISPR fitness screens with JLOE.
Dede M; Hart T
Nucleic Acids Res; 2023 Feb; 51(4):1637-1651. PubMed ID: 36727483
[TBL] [Abstract][Full Text] [Related]
17. PICKLES: the database of pooled in-vitro CRISPR knockout library essentiality screens.
Lenoir WF; Lim TL; Hart T
Nucleic Acids Res; 2018 Jan; 46(D1):D776-D780. PubMed ID: 29077937
[TBL] [Abstract][Full Text] [Related]
18. OGEE v3: Online GEne Essentiality database with increased coverage of organisms and human cell lines.
Gurumayum S; Jiang P; Hao X; Campos TL; Young ND; Korhonen PK; Gasser RB; Bork P; Zhao XM; He LJ; Chen WH
Nucleic Acids Res; 2021 Jan; 49(D1):D998-D1003. PubMed ID: 33084874
[TBL] [Abstract][Full Text] [Related]
19. Integration of CRISPR-Cas9, shRNA with other genomic data provides reliable predicions of gene essentiality.
Rubio A
EBioMedicine; 2020 Jan; 51():102577. PubMed ID: 31901860
[No Abstract] [Full Text] [Related]
20. CEN-tools: an integrative platform to identify the contexts of essential genes.
Sharma S; Dincer C; Weidemüller P; Wright GJ; Petsalaki E
Mol Syst Biol; 2020 Oct; 16(10):e9698. PubMed ID: 33073517
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
