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292 related items for PubMed ID: 35622868

  • 1. Neural networks enable efficient and accurate simulation-based inference of evolutionary parameters from adaptation dynamics.
    Avecilla G, Chuong JN, Li F, Sherlock G, Gresham D, Ram Y.
    PLoS Biol; 2022 May; 20(5):e3001633. PubMed ID: 35622868
    [Abstract] [Full Text] [Related]

  • 2. Single-cell copy number variant detection reveals the dynamics and diversity of adaptation.
    Lauer S, Avecilla G, Spealman P, Sethia G, Brandt N, Levy SF, Gresham D.
    PLoS Biol; 2018 Dec; 16(12):e3000069. PubMed ID: 30562346
    [Abstract] [Full Text] [Related]

  • 3. An evolving view of copy number variants.
    Lauer S, Gresham D.
    Curr Genet; 2019 Dec; 65(6):1287-1295. PubMed ID: 31076843
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  • 4. Likelihood approximation networks (LANs) for fast inference of simulation models in cognitive neuroscience.
    Fengler A, Govindarajan LN, Chen T, Frank MJ.
    Elife; 2021 Apr 06; 10():. PubMed ID: 33821788
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  • 5. An improved algorithm for inferring mutational parameters from bar-seq evolution experiments.
    Li F, Mahadevan A, Sherlock G.
    BMC Genomics; 2023 May 06; 24(1):246. PubMed ID: 37149606
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  • 6. Estimating parameters of a stochastic cell invasion model with fluorescent cell cycle labelling using approximate Bayesian computation.
    Carr MJ, Simpson MJ, Drovandi C.
    J R Soc Interface; 2021 Sep 06; 18(182):20210362. PubMed ID: 34547212
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  • 7. Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems.
    Toni T, Welch D, Strelkowa N, Ipsen A, Stumpf MP.
    J R Soc Interface; 2009 Feb 06; 6(31):187-202. PubMed ID: 19205079
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  • 8. Bayesian inference of selection in the Wright-Fisher diffusion model.
    Gory JJ, Herbei R, Kubatko LS.
    Stat Appl Genet Mol Biol; 2018 Jun 06; 17(3):. PubMed ID: 29874197
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  • 9. Towards end-to-end likelihood-free inference with convolutional neural networks.
    Radev ST, Mertens UK, Voss A, Köthe U.
    Br J Math Stat Psychol; 2020 Feb 06; 73(1):23-43. PubMed ID: 30793299
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  • 10. Flexible and efficient simulation-based inference for models of decision-making.
    Boelts J, Lueckmann JM, Gao R, Macke JH.
    Elife; 2022 Jul 27; 11():. PubMed ID: 35894305
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  • 11. Molecular specificity, convergence and constraint shape adaptive evolution in nutrient-poor environments.
    Hong J, Gresham D.
    PLoS Genet; 2014 Jan 27; 10(1):e1004041. PubMed ID: 24415948
    [Abstract] [Full Text] [Related]

  • 12. Inferring the interaction rules of complex systems with graph neural networks and approximate Bayesian computation.
    Gaskell J, Campioni N, Morales JM, Husmeier D, Torney CJ.
    J R Soc Interface; 2023 Jan 27; 20(198):20220676. PubMed ID: 36596456
    [Abstract] [Full Text] [Related]

  • 13. Inference of gene networks from gene expression time series using recurrent neural networks and sparse MAP estimation.
    Chen CK.
    J Bioinform Comput Biol; 2018 Aug 27; 16(4):1850009. PubMed ID: 30051742
    [Abstract] [Full Text] [Related]

  • 14. Copy number variation alters local and global mutational tolerance.
    Avecilla G, Spealman P, Matthews J, Caudal E, Schacherer J, Gresham D.
    Genome Res; 2023 Aug 27; 33(8):1340-1353. PubMed ID: 37652668
    [Abstract] [Full Text] [Related]

  • 15. Best Practices in Microbial Experimental Evolution: Using Reporters and Long-Read Sequencing to Identify Copy Number Variation in Experimental Evolution.
    Spealman P, De T, Chuong JN, Gresham D.
    J Mol Evol; 2023 Jun 27; 91(3):356-368. PubMed ID: 37012421
    [Abstract] [Full Text] [Related]

  • 16. A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks.
    Mariño IP, Zaikin A, Míguez J.
    PLoS One; 2017 Jun 27; 12(8):e0182015. PubMed ID: 28797087
    [Abstract] [Full Text] [Related]

  • 17. A practical guide to pseudo-marginal methods for computational inference in systems biology.
    Warne DJ, Baker RE, Simpson MJ.
    J Theor Biol; 2020 Jul 07; 496():110255. PubMed ID: 32223995
    [Abstract] [Full Text] [Related]

  • 18. Mutation rate, selection, and epistasis inferred from RNA virus haplotypes via neural posterior estimation.
    Caspi I, Meir M, Ben Nun N, Abu Rass R, Yakhini U, Stern A, Ram Y.
    Virus Evol; 2023 Jul 07; 9(1):vead033. PubMed ID: 37305706
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  • 19. An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics.
    Wang L, Wang S, Bouchard-Côté A.
    Syst Biol; 2020 Jan 01; 69(1):155-183. PubMed ID: 31173141
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  • 20. Bayesian parameter inference and model selection by population annealing in systems biology.
    Murakami Y.
    PLoS One; 2014 Jan 01; 9(8):e104057. PubMed ID: 25089832
    [Abstract] [Full Text] [Related]

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