Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Tracing the genealogy origin of geographic populations based on genomic variation and deep learning.

Molecular phylogenetics and evolution - 1 Sept 2024

Yang Bing, Zhou Xin, Liu Shanlin

Abstract excerpt

Assigning a query individual animal or plant to its derived population is a prime task in diverse applications related to organismal genealogy. Such endeavors have conventionally relied on short DNA sequences under a phylogenetic framework. These methods naturally show constraints when the inferred population sources are ambiguously phylogenetically structured, a scenario demanding substantially more informative...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Ants
Share to Bees
Share to Chickens

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Deep Learning

Share to Genetics, Population

Share to Genomics

Share to Phylogeny

Share to Polymorphism, Single Nucleotide

Source

Identifiers

PMID: 38964594
DOI: 10.1016/j.ympev.2024.108142

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Tracing the genealogy origin of geographic populations based on genomic variation and deep learning.PMID 38964594Read ↗

Predicting Geographic Location from Genetic Variation with Deep Neural NetworksSemantic proximity Read ↗

Predicting geographic location from genetic variation with deep neural networks.Semantic proximity Read ↗

Local Ancestry Inference for Complex Population HistoriesSemantic proximity Read ↗

Analyses of genetic ancestry enable key insights for molecular ecology.Semantic proximity Read ↗

Deep estimation of the intensity and timing of natural selection from ancient genomes.Semantic proximity Read ↗

Inferring the geographic origin of a range expansion: Latitudinal and longitudinal coordinates inferred from genomic data in an ABC framework with the program x-origin.Semantic proximity Read ↗

Inference of population splits and mixtures from genome-wide allele frequency data.Semantic proximity Read ↗

disperseNN2: a neural network for estimating dispersal distance from georeferenced polymorphism data.Semantic proximity Read ↗

Dispersal inference from population genetic variation using a convolutional neural network.Semantic proximity Read ↗

Geographical range size and latitude predict population genetic structure in a global survey.Semantic proximity Read ↗

A likelihood-based framework for demographic inference from genealogical treesSemantic proximity Read ↗

Hyperbolic geometry-based deep learning methods to produce population trees from genotype dataSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.