On the importance of assessing topological convergence in Bayesian phylogenetic inference

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

Demographics of sources of HIV-1 transmission in Zambia: a molecular epidemiology analysis in the HPTN 071 PopART study

Autor: Agyei, Yaw, Beyers, Nulda, Bock, Peter, Bond, Virginia, Bwalya, Justin, Cori, Anne, Deventer, Anneen, Dunbar, Rory, El-Sadr, Wafaa, Emel, Lynda, Floyd, Sian, Griffith, Sam, Hargreaves, James, Hauck, Katharina, Headen, Tanette, Hoddinott, Graeme, James, Anelet, Jennings, Karen, Kanema, Sarah, Kosloff, Barry, Kruger, James, Kumar, Ramya, Macleod, David, Makola, Nozizwe, Mandla, Nomtha, Miller, Eric, Moore, Ayana, Mwenge, Lawrence, Noble, Heather, Phiri, Mwelwa, Pickles, Michael, Sabapathy, Kalpana, Sakala, Ephraim, Sauter, Rafael, Shanaube, Kwame, Silumesi, Andrew, Sista, Nirupama, Skalland, Tim, Smith, Peter, Thomas, Ranjeeta, Vermund, Sten, White, Rhonda, Wilson, Ethan, Yang, Blia, Yuhas, Krista, Bowden, Rory, Calvez, Vincent, Essex, Max, Grabowski, Kate, Gupta, Ravindra, Herbeck, Joshua, Kagaayi, Joseph, Kaleebu, Pontiano, Lingappa, Jairam, Moyo, Sikhulile, Novitsky, Vladimir, Ndung’u, Thumbi, Pillay, Deenan, Quinn, Thomas, Rambaut, Andrew, Seeley, Janet, Ssemwanga, Deogratius, Tanser, Frank, Wawer, Maria, Hall, Matthew, Golubchik, Tanya, Bonsall, David, Abeler-Dörner, Lucie, Limbada, Mohammed, Schaap, Ab, de Cesare, Mariateresa, MacIntyre-Cockett, George, Otecko, Newton, Probert, William, Ratmann, Oliver, Bulas Cruz, Ana, Piwowar-Manning, Estelle, Burns, David N, Cohen, Myron S, Donnell, Deborah J, Eshleman, Susan H, Simwinga, Musonda, Fidler, Sarah, Hayes, Richard, Ayles, Helen, Fraser, Christophe

Publikováno v: In The Lancet Microbe January 2024 5(1):e62-e71

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Massive parallelization boosts big Bayesian multidimensional scaling

Autor: Holbrook, Andrew, Lemey, Philippe, Baele, Guy, Dellicour, Simon, Brockmann, Dirk, Rambaut, Andrew, Suchard, Marc

Big Bayes is the computationally intensive co-application of big data and large, expressive Bayesian models for the analysis of complex phenomena in scientific inference and statistical learning. Standing as an example, Bayesian multidimensional scal

Externí odkaz: http://arxiv.org/abs/1905.04582

SARS-CoV-2-specific nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination

Autor: Baillie, J. 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Publikováno v: In eBioMedicine January 2023 87