First use of probabilistic programming for hard problems in statistical phylogenetics

Project Information

PhyPPL

Grant agreement ID: 898120

DOI

10.3030/898120

Project closed

EC signature date 8 April 2020

Start date 4 May 2020

End date 24 August 2022

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 203 852,16

EU contribution

€ 203 852,16

Coordinated by

NATURHISTORISKA RIKSMUSEET
Sweden

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Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Other (2)

Seroepidemiologic study to detect antibody-mediated immunity against SARS-CoV-2 among residents and healthcare workers in the city of Plovdiv, Bulgaria, weeks 21-24, 2020

Author(s): Angel Kunchev. Savina Stoitsova, Viktor Senderov, Siyka Dimcheva, Vanya Rangelova, Ralitsa Raycheva, Meri Hristamyan, Ani Kevorkian, Jordanka Stoilova, Maria Atanasova, Atanaska Petrova, Marianna Murdjeva, Todor Kantardjiev
Published in: European Scientific Conference on Applied Infectious Disease Epidemiology (ESCAIDE), 2020
Publisher: ESCAIDE
DOI: 10.5281/zenodo.7759891

Probabilistic Modeling of Bursts and Gradual Changes of DiversificationRates in Bird Evolution

Author(s): Viktor Senderov, Jan Kudlicka, Nicolas Lartillot, Daniel Lundén, Ignacio Quintero, Hélène Morlon, David Broman, Fredrik Ronquist
Published in: Congress of European Society of Evolutionary Biology, 2022
Publisher: ESEB
DOI: 10.5281/zenodo.7759914

Peer reviewed articles (1)

Universal probabilistic programming offers a powerful approach to statistical phylogenetics

Author(s): Viktor Senderov, Fredrik Ronquist, Johannes Borgström, Nicolas Lartillot, Daniel Lundén, Lawrence Murray, Thomas B. Schön, David Broman
Published in: Communications Biology, Issue 4, 2021, Page(s) 244, ISSN 2399-3642
Publisher: Nature
DOI: 10.1038/s42003-021-01753-7

Conference proceedings (1)

Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference

Author(s): Daniel Lundén, Joey Öhman, Jan Kudlicka, Viktor Senderov, Fredrik Ronquist, David Broman
Published in: Programming Languages and Systems, Issue ESOP 2022, 2022, Page(s) vol 13240, ISBN 978-3-030-99336-8
Publisher: Springer, Cham
DOI: 10.1007/978-3-030-99336-8_2