Jere Koskela
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Explore the profile of Jere Koskela including associated specialties, affiliations and a list of published articles.
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10
Citations
160
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Recent Articles
1.
Helekal D, Koskela J, Didelot X
Syst Biol
. 2025 Jan;
PMID: 39826137
The vast majority of pathogen phylogenetic studies do not consider the possibility of multiple merger events being present, where a single node of the tree leads to more than two...
2.
Wong Y, Ignatieva A, Koskela J, Gorjanc G, Wohns A, Kelleher J
Genetics
. 2024 Jul;
228(1).
PMID: 39013109
As a result of recombination, adjacent nucleotides can have different paths of genetic inheritance and therefore the genealogical trees for a sample of DNA sequences vary along the genome. The...
3.
Koskela J, Latuszynski K, Spano D
Theor Popul Biol
. 2024 Feb;
156:40-45.
PMID: 38301934
Mathematical models of genetic evolution often come in pairs, connected by a so-called duality relation. The most seminal example are the Wright-Fisher diffusion and the Kingman coalescent, where the former...
4.
Wong Y, Ignatieva A, Koskela J, Gorjanc G, Wohns A, Kelleher J
bioRxiv
. 2023 Nov;
PMID: 37961279
As a result of recombination, adjacent nucleotides can have different paths of genetic inheritance and therefore the genealogical trees for a sample of DNA sequences vary along the genome. The...
5.
Arnason E, Koskela J, Halldorsdottir K, Eldon B
Elife
. 2023 Feb;
12.
PMID: 36806325
Highly fecund natural populations characterized by high early mortality abound, yet our knowledge about their recruitment dynamics is somewhat rudimentary. This knowledge gap has implications for our understanding of genetic...
6.
Sant J, Jenkins P, Koskela J, Spano D
Bioinformatics
. 2023 Jan;
39(1).
PMID: 36629450
Motivation: The Wright-Fisher diffusion is important in population genetics in modelling the evolution of allele frequencies over time subject to the influence of biological phenomena such as selection, mutation and...
7.
Mahmoudi A, Koskela J, Kelleher J, Chan Y, Balding D
PLoS Comput Biol
. 2022 Mar;
18(3):e1009960.
PMID: 35263345
We present a novel algorithm, implemented in the software ARGinfer, for probabilistic inference of the Ancestral Recombination Graph under the Coalescent with Recombination. Our Markov Chain Monte Carlo algorithm takes...
8.
Baumdicker F, Bisschop G, Goldstein D, Gower G, Ragsdale A, Tsambos G, et al.
Genetics
. 2021 Dec;
220(3).
PMID: 34897427
Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate...
9.
Blath J, Buzzoni E, Koskela J, Wilke Berenguer M
Theor Popul Biol
. 2020 Jan;
132:1-15.
PMID: 31945384
We derive statistical tools to analyze the patterns of genetic variability produced by models related to seed banks; in particular the Kingman coalescent, its time-changed counterpart describing so-called weak seed...
10.
Koskela J, Wilke Berenguer M
Math Biosci
. 2019 Mar;
311:1-12.
PMID: 30851276
We study the effect of biological confounders on the model selection problem between Kingman coalescents with population growth, and Ξ-coalescents involving simultaneous multiple mergers. We use a low dimensional, computationally...