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.
135 related articles for article (PubMed ID: 37591206)
1. Learning protein fitness landscapes with deep mutational scanning data from multiple sources. Chen L; Zhang Z; Li Z; Li R; Huo R; Chen L; Wang D; Luo X; Chen K; Liao C; Zheng M Cell Syst; 2023 Aug; 14(8):706-721.e5. PubMed ID: 37591206 [TBL] [Abstract][Full Text] [Related]
2. Informed training set design enables efficient machine learning-assisted directed protein evolution. Wittmann BJ; Yue Y; Arnold FH Cell Syst; 2021 Nov; 12(11):1026-1045.e7. PubMed ID: 34416172 [TBL] [Abstract][Full Text] [Related]
3. Accurate top protein variant discovery via low-N pick-and-validate machine learning. Chu HY; Fong JHC; Thean DGL; Zhou P; Fung FKC; Huang Y; Wong ASL Cell Syst; 2024 Feb; 15(2):193-203.e6. PubMed ID: 38340729 [TBL] [Abstract][Full Text] [Related]
5. Minding the gaps: The importance of navigating holes in protein fitness landscapes. Thomas N; Colwell LJ Cell Syst; 2021 Nov; 12(11):1019-1020. PubMed ID: 34793698 [TBL] [Abstract][Full Text] [Related]
6. Unsupervised Inference of Protein Fitness Landscape from Deep Mutational Scan. Fernandez-de-Cossio-Diaz J; Uguzzoni G; Pagnani A Mol Biol Evol; 2021 Jan; 38(1):318-328. PubMed ID: 32770229 [TBL] [Abstract][Full Text] [Related]
7. Inferring protein fitness landscapes from laboratory evolution experiments. D'Costa S; Hinds EC; Freschlin CR; Song H; Romero PA PLoS Comput Biol; 2023 Mar; 19(3):e1010956. PubMed ID: 36857380 [TBL] [Abstract][Full Text] [Related]
8. Predicting higher-order mutational effects in an RNA enzyme by machine learning of high-throughput experimental data. Beck JD; Roberts JM; Kitzhaber JM; Trapp A; Serra E; Spezzano F; Hayden EJ Front Mol Biosci; 2022; 9():893864. PubMed ID: 36046603 [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. AMaLa: Analysis of Directed Evolution Experiments via Annealed Mutational Approximated Landscape. Sesta L; Uguzzoni G; Fernandez-de-Cossio-Diaz J; Pagnani A Int J Mol Sci; 2021 Oct; 22(20):. PubMed ID: 34681569 [TBL] [Abstract][Full Text] [Related]
12. Biological fitness landscapes by deep mutational scanning. Mehlhoff JD; Ostermeier M Methods Enzymol; 2020; 643():203-224. PubMed ID: 32896282 [TBL] [Abstract][Full Text] [Related]
13. A continuous epistasis model for predicting growth rate given combinatorial variation in gene expression and environment. Otto RM; Turska-Nowak A; Brown PM; Reynolds KA Cell Syst; 2024 Feb; 15(2):134-148.e7. PubMed ID: 38340730 [TBL] [Abstract][Full Text] [Related]
14. Machine learning to navigate fitness landscapes for protein engineering. Freschlin CR; Fahlberg SA; Romero PA Curr Opin Biotechnol; 2022 Jun; 75():102713. PubMed ID: 35413604 [TBL] [Abstract][Full Text] [Related]
15. Machine learning-assisted directed protein evolution with combinatorial libraries. Wu Z; Kan SBJ; Lewis RD; Wittmann BJ; Arnold FH Proc Natl Acad Sci U S A; 2019 Apr; 116(18):8852-8858. PubMed ID: 30979809 [TBL] [Abstract][Full Text] [Related]
17. Impact of In Vivo Protein Folding Probability on Local Fitness Landscapes. Faber MS; Wrenbeck EE; Azouz LR; Steiner PJ; Whitehead TA Mol Biol Evol; 2019 Dec; 36(12):2764-2777. PubMed ID: 31400199 [TBL] [Abstract][Full Text] [Related]
18. On the (un)predictability of a large intragenic fitness landscape. Bank C; Matuszewski S; Hietpas RT; Jensen JD Proc Natl Acad Sci U S A; 2016 Dec; 113(49):14085-14090. PubMed ID: 27864516 [TBL] [Abstract][Full Text] [Related]
19. Molecular Fitness Landscapes from High-Coverage Sequence Profiling. Blanco C; Janzen E; Pressman A; Saha R; Chen IA Annu Rev Biophys; 2019 May; 48():1-18. PubMed ID: 30601678 [TBL] [Abstract][Full Text] [Related]
20. Rational evolutionary design: the theory of in vitro protein evolution. Voigt CA; Kauffman S; Wang ZG Adv Protein Chem; 2000; 55():79-160. PubMed ID: 11050933 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]