Publications

Stochastic models in population genetics and evolution:

Coalescent processes in subdivided populations subject to recurrent mass extinctions. Jay Taylor and A.V. (2009). Electron. J. Probab., 14: 242-288.

A new model for evolution in a spatial continuum. Nick Barton, Alison Etheridge and A.V. (2010). Electron. J. Probab., 15: 162-216.

The spatial Lambda-Fleming-Viot process on a large torus: genealogies in the presence of recombination. Alison Etheridge and A.V. (2012). Ann. Applied Probab., 22: 2165-2209.

Large scale behaviour of the spatial Lambda-Fleming-Viot process. N. Berestycki, A. Etheridge and A.V. (2013). Ann. Inst. H. Poincaré Probab. Statist., 49: 374-401.

Modelling evolution in a spatial continuum. N. Barton, A. Etheridge and A.V. (2013). Journal of Statistical Mechanics, P01002.

Genetic hitchhiking in spatially extended populations. N. Barton, A. Etheridge, J. Kelleher and A.V. (2013). Theor. Popul. Biol., 87: 75-89.

The spatial Lambda-Fleming-Viot process: an event-based construction and a lookdown representation. A.V. and A. Wakolbinger (2015). Ann. Inst. H. Poincaré Probab. Statist., 51: 570-598.

Ancestries of a recombining diploid population. R. Sainudiin, B. Thatte and A.V. (2016). J. Math. Biol., 72: 363-408.

Spread of pedigree versus genetic ancestry in spatially distributed populations. N. Barton, A. Etheridge, J. Kelleher and A.V. (2016). Theor. Popul. Biol., 108: 1-12.

A Beta-splitting model for evolutionary trees. R. Sainudiin and A.V. (2016). R. Soc. open sci., 3: 160016.

The infinitesimal model: definition, derivation and implications. N. Barton, A. Etheridge and A.V. (2017). Theor. Popul. Biol., 118: 50-73.

Rescaling limits of the spatial Lambda-Fleming-Viot process with selection. A. Etheridge, A.V. and F. Yu (2020). Electron. J. Probab., 25(120): 1-89.
Sheltering of deleterious mutations explains the stepwise extension of recombination suppression on sex chromosomes and other supergenes. P. Jay, E. Tezenas, A.V. and T. Giraud (2022). PLoS Biol, 20(7): e3001698. After the publication of our paper Jay et al. (2022) in PLOS Biology, part of our methodology was questioned in a bioRxiv preprint and in a subsequent review paper using the material presented in the bioRxiv preprint. In order to clarify the different points of misunderstanding that have led to these criticisms, in this document we provide a response that, we hope, will demonstrate the validity of our approach. This debate is grounded on the very interesting question of which control scenario is appropriate to assess the efficiency of the sheltering effect, and we hope to contribute to this discussion with sound logical arguments and relevant biological concepts. The document can now also be found on hal (hal-04763742). The preprint Jay, Véber and Giraud (2024) below also offers supplementary analyses which reinforce our conclusions.
The fate of recessive deleterious or overdominant mutations near mating-type loci under partial selfing. E. Tezenas, T. Giraud, A.V. and S. Billiard (2023). Peer Community Journal, 3: e14.
Drosophilids with darker cuticle have higher body temperature under light. L. Freoa, L.-M. Chevin, P. Christol, S. Méléard, M. Rera, A.V. and J.-M. Gibert (2023). Scientific Reports, 13: 3513, 2023.
The infinitesimal model with dominance. N. Barton, A. Etheridge and A.V. (2023). Genetics, 225(2): iyad133.
Measure-valued growth processes in continuous space and growth properties starting from an infinite interface. A. Louvet and A.V. (2024). Stochastic Process. Appl., 170: 104291.
Why do sex chromosomes progressively lose recombination? P. Jay, D. Jeffries, F. E. Hartmann, A.V. and T. Giraud (2024). Trends in Genetics, 40(7): 564-579.
The impact of environmental fluctuations, sexual dimorphism, dominance reversal and plasticity on the pigmentation-related genetic and phenotypic variation in D. melanogaster populations – A modelling study. L. Freoa, J.-M. Gibert and A.V. (2024). Preprint, hal-04597232.
Deleterious mutations can contribute to the evolution of recombination suppression between sex chromosomes. P. Jay, A. Véber and T. Giraud (2024). Preprint, bioRxiv.

Statistical inference for population genetics models:

Inference in two dimensions: allele frequencies versus lengths of shared sequence blocks. N. Barton, A. Etheridge, J. Kelleher and A.V. (2013). Theor. Popul. Biol., 87: 105-119.

Finding the best resolution for the Kingman-Tajima coalescent: theory and applications. R. Sainudiin, T. Stadler and A.V. (2015). J. Math. Biol., 70: 1207-1247.

Full likelihood inference from the site frequency spectrum based on the optimal tree resolution (and Supplementary material). R. Sainudiin and A.V. (2018). Theor. Popul. Biol., 124: 1-15.

Bayesian estimation of population size changes by sampling Tajima's trees, with J.A. Palacios, A.V., L. Cappello, Z. Wang, J. Wakeley and S. Ramachandran (2019). Genetics, 213: 967-986.

An efficient coalescent model for heterochronously sampled molecular data. L. Cappello, A.V. and J. Palacios (2024). Journal of the American Statistical Association, 1-13.

Branching processes and other population models:

Quenched convergence of a sequence of superprocesses in Rd among Poissonian obstacles. A.V. (2009). Stochastic Process. Appl., 119: 2598-2624.

Escape probabilities for branching Brownian motion among mild obstacles. Jean-François Le Gall and A.V. (2012). J. Theor. Probab., 25: 505-535.

Graph-Theoretic Algorithms for the Isomorphism of Polynomials Problem. C. Bouillaguet, P.-A. Fouque and A.V. (2013). Eurocrypt.

Hyphal network whole field imaging allows for accurate estimation of anastomosis rates and branching dynamics of the filamentous fungus Podospora anserina. J. Dikec, A. Olivier, C. Bobée, Y. D'Angelo, R. Catellier, P. David, F. Filaine, S. Herbert, C. Lalanne, H. Lalucque, L. Monasse, M. Rieu, G. Ruprich-Robert, A.V., F. Chapeland-Leclerc and E. Herbert (2020). Scientific Reports, 10: 3131.

The role of mode switching in a population of actin polymers with constraints. François Robin, Anne Van Gorp and A.V. (2021). J. Math. Biol., 82(3): 1-43.

Ergodic behaviour of a multi-type growth-fragmentation process modelling the mycelial network of a filamentous fungus. Milica Tomasevic, Vincent Bansaye and A.V. (2022). ESAIM: P & S, 26: 397-435.
A spatial measure-valued model for chemical reaction networks in heterogeneous systems. Lea Popovic and A.V. (2023). Ann. Applied Probab., 33(5): 3706-3754.

Communication networks:

On the fluid limits of a resource sharing algorithm with logarithmic weights. P. Robert and A.V. (2015). Ann. Applied Probab., 25: 2626-2670.

A scaling analysis of a star network with logarithmic weights. P. Robert and A.V. (2019). Stochastic Process. Appl., 129: 1749-1781.

Popularisation papers (maths):

Théorèmes limites pour des processus de branchement et de coalescence spatiaux. A.V. (2010). Thesis summary, MATAPLI, 92: 53-60.

Les différentes échelles de temps de l'évolution. V. Bansaye, S. Méléard and A.V. (2013). MATAPLI, 100: 101-116.
Decision-making tools for healthcare structures in times of pandemic. T. Garaix, S. Gaubert, J. Josse, N. Vayatis and A.V. (2022). Anaesth. Crit. Care Pain Med, 41: 101052.
Promouvoir les interactions entre mathématiques et sciences du vivant, de la Terre et de l'Homme. A. Guillin, L. Saint-Raymond and A. Véber (2024). La lettre de CNRS Sciences humaines & sociales, 89: 24-26 (juillet 2024).