These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
184 related articles for article (PubMed ID: 38148337)
1. ACIDES: on-line monitoring of forward genetic screens for protein engineering. Nemoto T; Ocari T; Planul A; Tekinsoy M; Zin EA; Dalkara D; Ferrari U Nat Commun; 2023 Dec; 14(1):8504. PubMed ID: 38148337 [TBL] [Abstract][Full Text] [Related]
2. [Application of deep mutational scanning technology in protein research]. Li Y; Wang Y; Zhang K; Li S Sheng Wu Gong Cheng Xue Bao; 2023 Sep; 39(9):3710-3723. PubMed ID: 37805848 [TBL] [Abstract][Full Text] [Related]
3. Inference for one-step beneficial mutations using next generation sequencing. Wojtowicz AJ; Miller CR; Joyce P Stat Appl Genet Mol Biol; 2015 Feb; 14(1):65-81. PubMed ID: 25720101 [TBL] [Abstract][Full Text] [Related]
4. High-Throughput Protein Engineering by Massively Parallel Combinatorial Mutagenesis. Wan YK; Choi GCG; Wong ASL Methods Mol Biol; 2021; 2199():3-12. PubMed ID: 33125641 [TBL] [Abstract][Full Text] [Related]
5. High-throughput antibody engineering in mammalian cells by CRISPR/Cas9-mediated homology-directed mutagenesis. Mason DM; Weber CR; Parola C; Meng SM; Greiff V; Kelton WJ; Reddy ST Nucleic Acids Res; 2018 Aug; 46(14):7436-7449. PubMed ID: 29931269 [TBL] [Abstract][Full Text] [Related]
6. Systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers. Chen J; Li X; Zhong H; Meng Y; Du H Sci Rep; 2019 Jun; 9(1):9345. PubMed ID: 31249349 [TBL] [Abstract][Full Text] [Related]
7. High-throughput screening, next generation sequencing and machine learning: advanced methods in enzyme engineering. Vanella R; Kovacevic G; Doffini V; Fernández de Santaella J; Nash MA Chem Commun (Camb); 2022 Feb; 58(15):2455-2467. PubMed ID: 35107442 [TBL] [Abstract][Full Text] [Related]
8. Software for the analysis and visualization of deep mutational scanning data. Bloom JD BMC Bioinformatics; 2015 May; 16():168. PubMed ID: 25990960 [TBL] [Abstract][Full Text] [Related]
9. Predicting mutant outcome by combining deep mutational scanning and machine learning. Sarfati H; Naftaly S; Papo N; Keasar C Proteins; 2022 Jan; 90(1):45-57. PubMed ID: 34293212 [TBL] [Abstract][Full Text] [Related]
10. Directed Evolution of Reprogramming Factors by Cell Selection and Sequencing. Veerapandian V; Ackermann JO; Srivastava Y; Malik V; Weng M; Yang X; Jauch R Stem Cell Reports; 2018 Aug; 11(2):593-606. PubMed ID: 30078555 [TBL] [Abstract][Full Text] [Related]
11. Deep sequencing methods for protein engineering and design. Wrenbeck EE; Faber MS; Whitehead TA Curr Opin Struct Biol; 2017 Aug; 45():36-44. PubMed ID: 27886568 [TBL] [Abstract][Full Text] [Related]
12. Rational Protein Engineering Guided by Deep Mutational Scanning. Shin H; Cho BK Int J Mol Sci; 2015 Sep; 16(9):23094-110. PubMed ID: 26404267 [TBL] [Abstract][Full Text] [Related]
13. Detection of minor variants in Mycobacterium tuberculosis whole genome sequencing data. Goossens SN; Heupink TH; De Vos E; Dippenaar A; De Vos M; Warren R; Van Rie A Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34962257 [TBL] [Abstract][Full Text] [Related]
14. FASTQSim: platform-independent data characterization and in silico read generation for NGS datasets. Shcherbina A BMC Res Notes; 2014 Aug; 7():533. PubMed ID: 25123167 [TBL] [Abstract][Full Text] [Related]
15. Optimization of a deep mutational scanning workflow to improve quantification of mutation effects on protein-protein interactions. Bendel AM; Skendo K; Klein D; Shimada K; Kauneckaite-Griguole K; Diss G BMC Genomics; 2024 Jun; 25(1):630. PubMed ID: 38914936 [TBL] [Abstract][Full Text] [Related]
16. Variational inference for rare variant detection in deep, heterogeneous next-generation sequencing data. Zhang F; Flaherty P BMC Bioinformatics; 2017 Jan; 18(1):45. PubMed ID: 28103803 [TBL] [Abstract][Full Text] [Related]
17. Integrating deep mutational scanning and low-throughput mutagenesis data to predict the impact of amino acid variants. Fu Y; Bedő J; Papenfuss AT; Rubin AF Gigascience; 2022 Dec; 12():. PubMed ID: 37721410 [TBL] [Abstract][Full Text] [Related]
18. Deep Mutational Scanning: Library Construction, Functional Selection, and High-Throughput Sequencing. Starita LM; Fields S Cold Spring Harb Protoc; 2015 Aug; 2015(8):777-80. PubMed ID: 26240405 [TBL] [Abstract][Full Text] [Related]
19. Machine learning random forest for predicting oncosomatic variant NGS analysis. Pellegrino E; Jacques C; Beaufils N; Nanni I; Carlioz A; Metellus P; Ouafik L Sci Rep; 2021 Nov; 11(1):21820. PubMed ID: 34750410 [TBL] [Abstract][Full Text] [Related]