Artificial neural networks can learn to estimate extinction rates from molecular phylogenies-Reference-Cited by-同舟云学术

Artificial neural networks can learn to estimate extinction rates from molecular phylogenies

Published:2006-12 Issue:3 Volume:243 Page:449-454
ISSN:0022-5193
Container-title:Journal of Theoretical Biology
language:en
Short-container-title:Journal of Theoretical Biology

Author:

Bokma Folmer

Publisher

Elsevier BV

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modelling and Simulation,General Medicine,Statistics and Probability

Reference16 articles.

1. Branching Processes;Athreya,1972

2. The Elements of Stochastic Processes with Applications to the Natural Sciences, first ed.;Bailey,1964

3. Testing for equal rates of cladogenesis in diverse taxa;Bokma;Evolution,2003

4. Phylogenies without fossils;Harvey;Evolution,1994

5. Neural Networks: A Comprehensive Foundation;Haykin,1999

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. phyddle: software for phylogenetic model exploration with deep learning;2024-08-08

2. Deep Learning and Likelihood Approaches for Viral Phylogeography Converge on the Same Answers Whether the Inference Model Is Right or Wrong;Systematic Biology;2024-01-01

3. Deep Learning from Phylogenies for Diversification Analyses;Systematic Biology;2023-08-09

4. Deep learning and likelihood approaches for viral phylogeography converge on the same answers whether the inference model is right or wrong;2023-02-10

5. Deep Learning from Phylogenies for Diversification Analyses;2022-09-28