1 code implementation • 9 Aug 2024 • Tianyu Xie, Frederick A. Matsen IV, Marc A. Suchard, Cheng Zhang
Reconstructing the evolutionary history relating a collection of molecular sequences is the main subject of modern Bayesian phylogenetic inference.
no code implementations • 18 Feb 2024 • Marius Brusselmans, Luiz Max Carvalho, Samuel L. Hong, Jiansi Gao, Frederick A. Matsen IV, Andrew Rambaut, Philippe Lemey, Marc A. Suchard, Gytis Dudas, Guy Baele
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.
2 code implementations • 23 Mar 2023 • Andrew F. Magee, Andrew J. Holbrook, Jonathan E. Pekar, Itzue W. Caviedes-Solis, Fredrick A. Matsen IV, Guy Baele, Joel O. Wertheim, Xiang Ji, Philippe Lemey, Marc A. Suchard
Phylogenetic and discrete-trait evolutionary inference depend heavily on an appropriate characterization of the underlying character substitution process.
2 code implementations • 3 Nov 2022 • Mathieu Fourment, Christiaan J. Swanepoel, Jared G. Galloway, Xiang Ji, Karthik Gangavarapu, Marc A. Suchard, Frederick A. Matsen IV
Gradients of probabilistic model likelihoods with respect to their parameters are essential for modern computational statistics and machine learning.
1 code implementation • 25 Oct 2021 • Xiang Ji, Alexander A. Fisher, Shuo Su, Jeffrey L. Thorne, Barney Potter, Philippe Lemey, Guy Baele, Marc A. Suchard
Divergence time estimation is crucial to provide temporal signals for dating biologically important events, from species divergence to viral transmissions in space and time.
2 code implementations • 2 Jul 2021 • Gabriel W. Hassler, Brigida Gallone, Leandro Aristide, William L. Allen, Max R. Tolkoff, Andrew J. Holbrook, Guy Baele, Philippe Lemey, Marc A. Suchard
Even in the presence of non-trivial phylogenetic model constraints, we show that one may analytically address latent factor uncertainty in a way that (a) aids model flexibility, (b) accelerates computation (by as much as 500-fold) and (c) decreases required tuning.
no code implementations • 3 Mar 2021 • Andrew J. Holbrook, Xiang Ji, Marc A. Suchard
Mutations sometimes increase contagiousness for evolving pathogens.
no code implementations • 5 Jan 2021 • Martijn J. Schuemie, Yong Chen, David Madigan, Marc A. Suchard
Studies of the effects of medical interventions increasingly take place in distributed research settings using data from multiple clinical data sources including electronic health records and administrative claims.
Methodology
2 code implementations • 6 Nov 2019 • Akihiko Nishimura, Marc A. Suchard
Use of continuous shrinkage priors -- with a "spike" near zero and heavy-tails towards infinity -- is an increasingly popular approach to induce sparsity in parameter estimates.
Methodology Statistics Theory Statistics Theory
1 code implementation • 29 May 2019 • Xiang Ji, Zhen-Yu Zhang, Andrew Holbrook, Akihiko Nishimura, Guy Baele, Andrew Rambaut, Philippe Lemey, Marc A. Suchard
To make this tractable, we present a linear-time algorithm for ${\cal O}\hspace{-0. 2em}\left( N \right)$-dimensional gradient evaluation and apply it to general continuous-time Markov processes of sequence substitution on a phylogenetic tree without a need to assume either stationarity or reversibility.
Computation Populations and Evolution Methodology
1 code implementation • 29 Oct 2018 • Akihiko Nishimura, Marc A. Suchard
We can then solve the linear system by the conjugate gradient (CG) algorithm through matrix-vector multiplications by $\Phi$; this involves no explicit factorization or calculation of $\Phi$ itself.
1 code implementation • 5 May 2015 • Luiz Max Carvalho, Nuno Rodrigues Faria, Andres M. Perez, Marc A. Suchard, Philippe Lemey, Waldemir de Castro Silveira, Andrew Rambaut, Guy Baele
Although foot-and-mouth disease virus (FMDV) incidence has decreased in South America over the last years, the pathogen still circulates in the region and the risk of re-emergence in previously FMDV-free areas is a veterinary public health concern.