Applications of machine learning in phylogenetics
Abstract Machine learning has increasingly been applied to a wide range of questions in
phylogenetic inference. Supervised machine learning approaches that rely on simulated …
phylogenetic inference. Supervised machine learning approaches that rely on simulated …
Deep learning from phylogenies for diversification analyses
Birth–death (BD) models are widely used in combination with species phylogenies to study
past diversification dynamics. Current inference approaches typically rely on likelihood …
past diversification dynamics. Current inference approaches typically rely on likelihood …
DeepDive: estimating global biodiversity patterns through time using deep learning
RB Cooper, JT Flannery-Sutherland… - Nature …, 2024 - nature.com
Understanding how biodiversity has changed through time is a central goal of evolutionary
biology. However, estimates of past biodiversity are challenged by the inherent …
biology. However, estimates of past biodiversity are challenged by the inherent …
Recent evolutionary origin and localized diversity hotspots of mammalian coronaviruses
Several coronaviruses infect humans, with three, including the SARS-CoV2, causing
diseases. While coronaviruses are especially prone to induce pandemics, we know little …
diseases. While coronaviruses are especially prone to induce pandemics, we know little …
Performance and robustness of parameter estimation from phylogenetic trees using neural networks
Species diversification is characterized by speciation and extinction, the rates of which can,
under some assumptions, be estimated from time-calibrated phylogenies. However …
under some assumptions, be estimated from time-calibrated phylogenies. However …
PhyloCNN: Improving tree representation and neural network architecture for deep learning from trees in phylodynamics and diversification studies
Phylodynamics and diversification studies using complex evolutionary models can be
challenging, especially with traditional likelihood-based approaches. As an alternative …
challenging, especially with traditional likelihood-based approaches. As an alternative …
A critical evaluation of deep-learning based phylogenetic inference programs using simulated data sets
Y Zhu, Y Li, C Li, XX Shen… - Journal of genetics and …, 2025 - pubmed.ncbi.nlm.nih.gov
A critical evaluation of deep-learning based phylogenetic inference programs using simulated
data sets A critical evaluation of deep-learning based phylogenetic inference programs using …
data sets A critical evaluation of deep-learning based phylogenetic inference programs using …
Dissecting Factors Underlying Phylogenetic Uncertainty Using Machine Learning Models
U Rosas-Puchuri, E Duarte-Ribeiro… - bioRxiv, 2023 - biorxiv.org
Phylogenetic inference can be influenced by both underlying biological processes and
methodological factors. While biological processes can be modeled, these models …
methodological factors. While biological processes can be modeled, these models …