Stochastische biologische Evolution

TH. Dickhaus, Simultaneous Statistical Inference, Springer, Berlin et al., 2014, 180 pages, (Monograph Published).

J. Kern, B. Wiederhold, A Lambda-Fleming--Viot type model with intrinsically varying population size, Electronic Journal of Probability, 29 (2024), pp. 125/1--125/28, DOI 10.1214/24-EJP1185 .
Abstract
We propose an extension of the classical ?-Fleming-Viot model to intrinsically varying pop- ulation sizes. During events, instead of replacing a proportion of the population, a random mass dies and a, possibly different, random mass of new individuals is added. The model can also incorporate a drift term, representing infinitesimally small, but frequent events. We investigate el- ementary properties of the model, analyse its relation to the Λ-Fleming-Viot model and describe a duality relationship. Through the lookdown framework, we provide a forward-in-time analysis of fixation and coming down from infinity. Furthermore, we present a new duality argument allowing one to deduce well-posedness of the measure-valued process without the necessity of proving uniqueness of the associated lookdown martingale problem.

B. Jahnel, Ch. Külske, Gibbsianness and non-Gibbsianness for Bernoulli lattice fields under removal of isolated sites, Bernoulli. Official Journal of the Bernoulli Society for Mathematical Statistics and Probability, 29 (2023), pp. 3013--3032, DOI 10.3150/22-BEJ1572 .
Abstract
We consider the i.i.d. Bernoulli field μ _p on Z ^d with occupation density p ∈ [0,1]. To each realization of the set of occupied sites we apply a thinning map that removes all occupied sites that are isolated in graph distance. We show that, while this map seems non-invasive for large p, as it changes only a small fraction p(1-p)^2d of sites, there is p(d) <1 such that for all p ∈ (p(d), 1) the resulting measure is a non-Gibbsian measure, i.e., it does not possess a continuous version of its finite-volume conditional probabilities. On the other hand, for small p, the Gibbs property is preserved.

N. Fountoulakis, T. Iyer, Condensation phenomena in preferential attachment trees with neighbourhood influence, Electronic Journal of Probability, 27 (2022), pp. 76/1--76/49, DOI 10.1214/22-EJP787 .
Abstract
We introduce a model of evolving preferential attachment trees where vertices are assigned weights, and the evolution of a vertex depends not only on its own weight, but also on the weights of its neighbours. We study the distribution of edges with endpoints having certain weights, and the distribution of degrees of vertices having a given weight. We show that the former exhibits a condensation phenomenon under a certain critical condition, whereas the latter converges almost surely to a distribution that resembles a power law distribution. Moreover, in the absence of condensation, we prove almost-sure setwise convergence of the related quantities. This generalises existing results on the Bianconi-Barabási tree as well as on an evolving tree model introduced by the second author.

A. Caiazzo, F. Caforio, G. Montecinos, L.O. Müller, P.J. Blanco, E.F. Toro, Assessment of reduced order Kalman filter for parameter identification in one-dimensional blood flow models using experimental data, International Journal of Numerical Methods in Biomedical Engineering, 33 (2017), pp. e2843/1--e2843/26, DOI 10.1002/cnm.2843 .
Abstract
This work presents a detailed investigation of a parameter estimation approach based on the reduced order unscented Kalman filter (ROUKF) in the context of one-dimensional blood flow models. In particular, the main aims of this study are (i) to investigate the effect of using real measurements vs. synthetic data (i.e., numerical results of the same in silico model, perturbed with white noise) for the estimation and (ii) to identify potential difficulties and limitations of the approach in clinically realistic applications in order to assess the applicability of the filter to such setups. For these purposes, our numerical study is based on the in vitro model of the arterial network described by [Alastruey et al. 2011, J. Biomech. bf 44], for which experimental flow and pressure measurements are available at few selected locations. In order to mimic clinically relevant situations, we focus on the estimation of terminal resistances and arterial wall parameters related to vessel mechanics (Young's modulus and thickness) using few experimental observations (at most a single pressure or flow measurement per vessel). In all cases, we first perform a theoretical identifiability analysis based on the generalized sensitivity function, comparing then the results obtained with the ROUKF, using either synthetic or experimental data, to results obtained using reference parameters and to available measurements.

O. Gün, A. Yilmaz, The stochastic encounter-mating model, Acta Applicandae Mathematicae. An International Survey Journal on Applying Mathematics and Mathematical Applications, 148 (2017), pp. 71--102.

A. González Casanova Soberón, N. Kurt, A. Wakolbinger, L. Yuan, An individual-based mathematical model for the Lenski experiment, and the deceleration of the relative fitness, Stochastic Processes and their Applications, 126 (2016), pp. 2211--2252.

J. Blath, A. González Casanova Soberón, N. Kurt, M. Wilke-Berenguer, A new coalescent for seed-bank models, The Annals of Applied Probability, 26 (2016), pp. 857--891.

K. Schildknecht, S. Olek, Th. Dickhaus, Simultaneous statistical inference for epigenetic data, PLOS ONE, 10 (2015), pp. e0125587/1--e0125587/15.
Abstract
Epigenetic research leads to complex data structures. Since parametric model assumptions for the distribution of epigenetic data are hard to verify we introduce in the present work a nonparametric statistical framework for two-group comparisons. Furthermore, epigenetic analyses are often performed at various genetic loci simultaneously. Hence, in order to be able to draw valid conclusions for specific loci, an appropriate multiple testing correction is necessary. Finally, with technologies available for the simultaneous assessment of many interrelated biological parameters (such as gene arrays), statistical approaches also need to deal with a possibly unknown dependency structure in the data. Our statistical approach to the nonparametric comparison of two samples with independent multivariate observables is based on recently developed multivariate multiple permutation tests. We adapt their theory in order to cope with families of hypotheses regarding relative effects. Our results indicate that the multivariate multiple permutation test keeps the pre-assigned type I error level for the global null hypothesis. In combination with the closure principle, the family-wise error rate for the simultaneous test of the corresponding locus/parameter-specific null hypotheses can be controlled. In applications we demonstrate that group differences in epigenetic data can be detected reliably with our methodology.

J. Blath, A. González Casanova Soberón, B. Eldon, N. Kurt, M. Wilke-Berenguer, Genetic variability under the seedbank coalescent, Genetics, 200 (2015), pp. 921--934.
Abstract
We analyze patterns of genetic variability of populations in the presence of a large seedbank with the help of a new coalescent structure called the seedbank coalescent. This ancestral process appears naturally as a scaling limit of the genealogy of large populations that sustain seedbanks, if the seedbank size and individual dormancy times are of the same order as those of the active population. Mutations appear as Poisson processes on the active lineages and potentially at reduced rate also on the dormant lineages. The presence of "dormant" lineages leads to qualitatively altered times to the most recent common ancestor and nonclassical patterns of genetic diversity. To illustrate this we provide a Wright-Fisher model with a seedbank component and mutation, motivated from recent models of microbial dormancy, whose genealogy can be described by the seedbank coalescent. Based on our coalescent model, we derive recursions for the expectation and variance of the time to most recent common ancestor, number of segregating sites, pairwise differences, and singletons. Estimates (obtained by simulations) of the distributions of commonly employed distance statistics, in the presence and absence of a seedbank, are compared. The effect of a seedbank on the expected site-frequency spectrum is also investigated using simulations. Our results indicate that the presence of a large seedbank considerably alters the distribution of some distance statistics, as well as the site-frequency spectrum. Thus, one should be able to detect from genetic data the presence of a large seedbank in natural populations.

TH. Dickhaus, Th. Royen, On multivariate chi-square distributions and their applications in testing multiple hypotheses, Statistics. A Journal of Theoretical and Applied Statistics, (2015), pp. 427--454.
Abstract
We are considered with three different types of multivariate chi-square distributions. Their members play important roles as limiting distributions of vectors of test statistics in several applications of multiple hypotheses testing. We explain these applications and provide formulas for computing multiplicity-adjusted $p$-values under the respective global hypothesis.

M. Hesse, A. Kyprianou, The total mass of super-Brownian motion upon exiting balls and Sheu's compact support condition, Stochastic Processes and their Applications, 124 (2014), pp. 2003--2022.
Abstract
We study the total mass of a d-dimensional super-Brownian motion as it first exits an increasing sequence of balls. The total mass process is a time-inhomogeneous continuous-state branching process, where the increasing radii of the balls are taken as the time-parameter. We characterise its time-dependent branching mechanism and show that it converges, as time goes to infinity, towards the branching mechanism of the total mass of a one-dimensional super-Brownian motion as it first crosses above an increasing sequence of levels.

Our results identify the compact support criterion in Sheu (1994) as Grey's condition (1974) for the aforementioned limiting branching mechanism.

V. Heinrich, T. Kamphans, J. Stange, D. Parkhomchuk, Th. Dickhaus, J. Hecht, P.N. Robinson, P.M. Krawitz, Estimating exome genotyping accuracy by comparing to data from large scale sequencing projects, Genome Medicine, 5 (2013), pp. 69/1--69/11.

I. Türbachova, T. Schwachula, I. Vasconcelos, A. Mustea, T. Baldinger, K.A. Jones, H. Bujard, A. Olek, K. Olek, K. Gellhaus, I. Braicu, D. Könsgen, Ch. Fryer, E. Ravot, A. Hellwag, N. Westerfeld, J.O. Gruss, M. Meissner, M. Hassan, M. Weber, U. Hofmüller, S. Zimmermann, Ch. Loddenkemper, S. Mahner, N. Babel, E. Berns, R. Adams, R. Zeilinger, U. Baron, I. Vergote, T. Maughan, F. Marme, Th. Dickhaus, J. Sehouli, S. Olek, The cellular ratio of immune tolerance (immunoCRIT) is a definite marker for aggressiveness of solid tumors and may explain tumor dissemination patterns, Epigenetics, 8 (2013), pp. 1226--1235.

M. Schreuder, J. Höhne, B. Blankertz, S. Haufe, Th. Dickhaus, M. Tangermann, Optimizing event-related potential based brain-computer interfaces: A systematic evaluation of dynamic stopping methods, Journal of Neural Engineering, 10 (2013), pp. 036025/1--036025/13.

TH. Dickhaus, J. Stange, Multiple point hypothesis test problems and effective numbers of tests for control of the family-wise error rate, Calcutta Statistical Association Bulletin, 65 (2013), pp. 123--144.

J. Blath, E. Bjarki, A. González Casanova Soberón, N. Kurt, Genealogy of a Wright--Fisher model with strong seedbank component, in: XI Symposium of Probability and Stochastic Processes, R.H. Mena, J.C. Pardo, V. Rivero, G. Uribe Bravo, eds., 69 of Birkhäuser Progress in Probability, Springer International Publishing, Switzerland, 2015, pp. 81--100.

H.-J. Mucha, H.-G. Bartel, Resampling techniques in cluster analysis: Is subsampling better than bootstrapping?, in: Data Science, Learning by Latent Structures, and Knowledge Discovery, B. Lausen, S. Krolak-Schwerdt, M. Böhmer, eds., Studies in Classification, Data Analysis and Knowledge Organization, Springer, Berlin et al., 2015, pp. 113--122.

B. Jahnel, First-passage percolation and chase-escape dynamics on random geometric graphs, Stochastic Geometry Days, November 15 - 19, 2021, Dunkerque, France, November 17, 2021.

B. Jahnel, Stochastic geometry for epidemiology (online talk), Monday Biostatistics Roundtable, Institute of Biometry and Clinical Epidemiology (Online Event), Campus Charité, June 14, 2021.

A. González Casanova Soberón, An individual-based model for the Lenski experiment, and the deceleration of the relative fitness, Workshop on Probabilistic Models in Biology, October 24 - 30, 2015, Playa del Carmen, Mexico, October 28, 2015.

A. González Casanova Soberón, Modeling the Lenski experiment, Genealogies in Evolution: Looking Backward and Forward, Workshop of the Priority Program (SPP) 1590 ``Probabilistic Structures in Evolution'', October 5 - 6, 2015, Goethe-Universität Frankfurt, October 6, 2015.

O. Gün, Stochastic encounter-mating model, Mathematical Model in Ecology and Evolution (MMEE 2015), July 7 - 13, 2015, Collège de France, Paris, France, July 8, 2015.

M. Hesse, Asymptotic growth of a branching random walk in a random environment on the hypercube, Friedrich-Alexander-Universität Erlangen-Nürnberg, Department Mathematik, December 4, 2014.

TH. Dickhaus, Simultaneous Bayesian analysis of contingency tables in genetic association studies, Bayesian Biostatistics 2014, July 2 - 5, 2014, University of Zurich, Switzerland, July 2, 2014.

TH. Dickhaus, Simultaneous Bayesian analysis of contingency tables in genetic association studies, International Workshop ``Advances in Optimization and Statistics'', May 15 - 16, 2014, Russian Academy of Sciences, Institute of Information Transmission Problems (Kharkevich Institute), Moscow, May 15, 2014.