Efficient ancestry and mutation simulation with msprime 1.0 F Baumdicker, G Bisschop, D Goldstein, G Gower, AP Ragsdale, ... Genetics 220 (3), iyab229, 2022 | 172 | 2022 |
Multi-locus data distinguishes between population growth and multiple merger coalescents J Koskela Statistical applications in genetics and molecular biology 17 (3), 2018 | 25 | 2018 |
Asymptotic genealogies of interacting particle systems with an application to sequential Monte Carlo J Koskela, PA Jenkins, AM Johansen, D Spano | 21 | 2020 |
Sweepstakes reproductive success via pervasive and recurrent selective sweeps E Árnason, J Koskela, K Halldórsdóttir, B Eldon Elife 12, e80781, 2023 | 19 | 2023 |
Robust model selection between population growth and multiple merger coalescents J Koskela, MW Berenguer Mathematical biosciences 311, 1-12, 2019 | 19 | 2019 |
Computational inference beyond Kingman's coalescent J Koskela, PA Jenkins, D Spano Journal of Applied Probability 52 (2), 519-537, 2015 | 19 | 2015 |
Bayesian inference of ancestral recombination graphs A Mahmoudi, J Koskela, J Kelleher, Y Chan, D Balding PLOS Computational Biology 18 (3), e1009960, 2022 | 17 | 2022 |
Statistical tools for seed bank detection J Blath, E Buzzoni, J Koskela, MW Berenguer Theoretical Population Biology 132, 1-15, 2020 | 14 | 2020 |
Consistency of Bayesian nonparametric inference for discretely observed jump diffusions J Koskela, D Spano, PA Jenkins Bernoulli 25 (3), 2183-2205, 2019 | 12 | 2019 |
Zig-zag sampling for discrete structures and nonreversible phylogenetic MCMC J Koskela Journal of Computational and Graphical Statistics 31 (3), 684-694, 2022 | 11 | 2022 |
Inference and rare event simulation for stopped Markov processes via reverse-time sequential Monte Carlo J Koskela, D Spano, PA Jenkins Statistics and Computing 28 (1), 131-144, 2018 | 9 | 2018 |
A general and efficient representation of ancestral recombination graphs Y Wong, A Ignatieva, J Koskela, G Gorjanc, AW Wohns, J Kelleher BioRxiv, 2023 | 8 | 2023 |
Simple conditions for convergence of sequential Monte Carlo genealogies with applications S Brown, PA Jenkins, AM Johansen, J Koskela | 8 | 2021 |
Bayesian non-parametric inference for -coalescents: Posterior consistency and a parametric method J Koskela, PA Jenkins, D Spanò | 7 | 2018 |
The distribution of branch duration and detection of inversions in ancestral recombination graphs A Ignatieva, M Favero, J Koskela, J Sant, SR Myers BioRxiv, 2023.07. 11.548567, 2023 | 5 | 2023 |
Convergence of likelihood ratios and estimators for selection in nonneutral Wright–Fisher diffusions J Sant, P A. Jenkins, J Koskela, D Spanò Scandinavian Journal of Statistics 49 (4), 1728-1760, 2022 | 5* | 2022 |
EWF: simulating exact paths of the Wright–Fisher diffusion J Sant, PA Jenkins, J Koskela, D Spanò Bioinformatics 39 (1), btad017, 2023 | 4 | 2023 |
Weak convergence of non-neutral genealogies to Kingman’s coalescent S Brown, PA Jenkins, AM Johansen, J Koskela Stochastic Processes and their Applications 162, 76-105, 2023 | 3 | 2023 |
Bernoulli factories and duality in Wright–Fisher and Allen–Cahn models of population genetics J Koskela, K Łatuszyński, D Spanò Theoretical Population Biology 156, 40-45, 2024 | 2 | 2024 |
Inference of multiple mergers while dating a pathogen phylogeny D Helekal, J Koskela, X Didelot bioRxiv, 2023.09. 12.557403, 2023 | 1 | 2023 |