Keyword search (4,163 papers available)

"Popovic L" Authored Publications:

Title Authors PubMed ID
1 Asymmetric autocatalytic reactions and their stationary distribution Gallinger C; Popovic L; 39679357
MATHSTATS
2 Pushed to the edge: Spatial sorting can slow down invasions Shaw AK; Lutscher F; Popovic L; 37198882
BIOLOGY
3 Diffusion dynamics on the coexistence subspace in a stochastic evolutionary game Popovic L; Peuckert L; 32025789
MATHSTATS
4 How spatial heterogeneity shapes multiscale biochemical reaction network dynamics. Pfaffelhuber P, Popovic L 25652460
MATHSTATS
5 Topology and inference for Yule trees with multiple states. Popovic L, Rivas M 27009067
MATHSTATS

 

Title:Topology and inference for Yule trees with multiple states.
Authors:Popovic LRivas M
Link:https://www.ncbi.nlm.nih.gov/pubmed/27009067?dopt=Abstract
DOI:10.1007/s00285-016-0992-6
Publication:Journal of mathematical biology
Keywords:Ancestral treeBinary search treeMulti-type branching processParameter reconstructionTree topologyYule tree
PMID:27009067 Category:J Math Biol Date Added:2019-06-07
Dept Affiliation: MATHSTATS
1 Department of Mathematics and Statistics, Concordia University, Montreal, QC, H3G 1M8, Canada. lea.popovic@concordia.ca.
2 Department of Mathematics and Statistics, Concordia University, Montreal, QC, H3G 1M8, Canada.

Description:

Topology and inference for Yule trees with multiple states.

J Math Biol. 2016 11;73(5):1251-1291

Authors: Popovic L, Rivas M

Abstract

We introduce two models for random trees with multiple states motivated by studies of trait dependence in the evolution of species. Our discrete time model, the multiple state ERM tree, is a generalization of Markov propagation models on a random tree generated by a binary search or 'equal rates Markov' mechanism. Our continuous time model, the multiple state Yule tree, is a generalization of the tree generated by a pure birth or Yule process to the tree generated by multi-type branching processes. We study state dependent topological properties of these two random tree models. We derive asymptotic results that allow one to infer model parameters from data on states at the leaves and at branch-points that are one step away from the leaves.

PMID: 27009067 [PubMed - indexed for MEDLINE]





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