Zobrazeno 1 - 10
of 162
pro vyhledávání: '"Matsen IV, Frederick A"'
Reconstructing the evolutionary history relating a collection of molecular sequences is the main subject of modern Bayesian phylogenetic inference. However, the commonly used Markov chain Monte Carlo methods can be inefficient due to the complicated
Externí odkaz:
http://arxiv.org/abs/2408.05058
Autor:
Fourment, Mathieu, Macaulay, Matthew, Swanepoel, Christiaan J, Ji, Xiang, Suchard, Marc A, Matsen IV, Frederick A
Bayesian inference has predominantly relied on the Markov chain Monte Carlo (MCMC) algorithm for many years. However, MCMC is computationally laborious, especially for complex phylogenetic models of time trees. This bottleneck has led to the search f
Externí odkaz:
http://arxiv.org/abs/2406.18044
Autor:
Brusselmans, Marius, Carvalho, Luiz Max, Hong, Samuel L., Gao, Jiansi, Matsen IV, Frederick A., Rambaut, Andrew, Lemey, Philippe, Suchard, Marc A., Dudas, Gytis, Baele, Guy
Modern phylogenetics research is often performed within a Bayesian framework, using sampling algorithms such as Markov chain Monte Carlo (MCMC) to approximate the posterior distribution. These algorithms require careful evaluation of the quality of t
Externí odkaz:
http://arxiv.org/abs/2402.11657
Autor:
Howard-Snyder, William, Dumm, Will, Barker, Mary, Milanov, Ognian, Winston, Claris, Rich, David H., Matsen IV, Frederick A
Why do phylogenetic algorithms fail when they return incorrect answers? This simple question has not been answered in detail, even for maximum parsimony (MP), the simplest phylogenetic criterion. Understanding MP has recently gained relevance in the
Externí odkaz:
http://arxiv.org/abs/2311.10913
Autor:
Dumm, Will, Barker, Mary, Howard-Snyder, William, DeWitt, William S., Matsen IV, Frederick A.
In many situations, it would be useful to know not just the best phylogenetic tree for a given data set, but the collection of high-quality trees. This goal is typically addressed using Bayesian techniques, however, current Bayesian methods do not sc
Externí odkaz:
http://arxiv.org/abs/2310.07919
Autor:
Gangavarapu, Karthik, Ji, Xiang, Baele, Guy, Fourment, Mathieu, Lemey, Philippe, Matsen IV, Frederick A., Suchard, Marc A.
The rapid growth in genomic pathogen data spurs the need for efficient inference techniques, such as Hamiltonian Monte Carlo (HMC) in a Bayesian framework, to estimate parameters of these phylogenetic models where the dimensions of the parameters inc
Externí odkaz:
http://arxiv.org/abs/2303.04390
Autor:
Swanepoel, Christiaan, Fourment, Mathieu, Ji, Xiang, Nasif, Hassan, Suchard, Marc A, Matsen IV, Frederick A, Drummond, Alexei
Probabilistic programming frameworks are powerful tools for statistical modelling and inference. They are not immediately generalisable to phylogenetic problems due to the particular computational properties of the phylogenetic tree object. TreeFlow
Externí odkaz:
http://arxiv.org/abs/2211.05220
Autor:
Fourment, Mathieu, Swanepoel, Christiaan J., Galloway, Jared G., Ji, Xiang, Gangavarapu, Karthik, Suchard, Marc A., Matsen IV, Frederick A.
Gradients of probabilistic model likelihoods with respect to their parameters are essential for modern computational statistics and machine learning. These calculations are readily available for arbitrary models via automatic differentiation implemen
Externí odkaz:
http://arxiv.org/abs/2211.02168
Autor:
Zhang, Cheng, Matsen IV, Frederick A.
Bayesian phylogenetic inference is currently done via Markov chain Monte Carlo (MCMC) with simple proposal mechanisms. This hinders exploration efficiency and often requires long runs to deliver accurate posterior estimates. In this paper, we present
Externí odkaz:
http://arxiv.org/abs/2204.07747
Next generation sequencing of B cell receptor (BCR) repertoires has become a ubiquitous tool for understanding the antibody-mediated immune response: it is now common to have large volumes of sequence data coding for both the heavy and light chain su
Externí odkaz:
http://arxiv.org/abs/2203.11367