AIMC Topic: Genetic Speciation

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Trait-mediated speciation and human-driven extinctions in proboscideans revealed by unsupervised Bayesian neural networks.

Science advances Jul 24, 2024
Species life-history traits, paleoenvironment, and biotic interactions likely influence speciation and extinction rates, affecting species richness over time. Birth-death models inferring the impact of these factors typically assume monotonic relatio...
Humans Neural Networks, Computer Genetic Speciation Fossils Extinction, Biological Animals Bayes Theorem Biodiversity
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Quartet Based Gene Tree Imputation Using Deep Learning Improves Phylogenomic Analyses Despite Missing Data.

Journal of computational biology : a journal of computational molecular cell biology Sep 1, 2022
Species tree estimation is frequently based on phylogenomic approaches that use multiple genes from throughout the genome. However, for a combination of reasons (ranging from sampling biases to more biological causes, as in gene birth and loss), gene...
Models, Genetic Computer Simulation Genome Genetic Speciation Phylogeny Deep Learning
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An approach using ddRADseq and machine learning for understanding speciation in Antarctic Antarctophilinidae gastropods.

Scientific reports Apr 19, 2021
Sampling impediments and paucity of suitable material for molecular analyses have precluded the study of speciation and radiation of deep-sea species in Antarctica. We analyzed barcodes together with genome-wide single nucleotide polymorphisms obtain...
Machine Learning Animals Sequence Analysis, DNA Gene Expression Regulation Gastropoda Ecosystem Phylogeny Gene Expression Profiling Antarctic Regions Genetic Speciation
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Impacts of speciation and extinction measured by an evolutionary decay clock.

Nature Dec 9, 2020
The hypothesis that destructive mass extinctions enable creative evolutionary radiations (creative destruction) is central to classic concepts of macroevolution. However, the relative impacts of extinction and radiation on the co-occurrence of specie...
Extinction, Biological Genetic Speciation Fossils Machine Learning Animals Time Factors Plants History, Ancient
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Machine learning-based analyses support the existence of species complexes for and .

Parasitology Jun 16, 2020
Human strongyloidiasis is a serious disease mostly attributable to Strongyloides stercoralis and to a lesser extent Strongyloides fuelleborni, a parasite mainly of non-human primates. The role of animals as reservoirs of human-infecting Strongyloides...
Strongyloides Strongyloides stercoralis Strongyloidiasis Electron Transport Complex IV Genes, Helminth Haplotypes RNA, Ribosomal, 18S Multilocus Sequence Typing Machine Learning Humans Disease Reservoirs Animals Primates Phylogeny Feces Genetic Speciation Genotype Computational Biology Dogs Dog Diseases
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Supervised machine learning reveals introgressed loci in the genomes of Drosophila simulans and D. sechellia.

PLoS genetics Apr 23, 2018
Hybridization and gene flow between species appears to be common. Even though it is clear that hybridization is widespread across all surveyed taxonomic groups, the magnitude and consequences of introgression are still largely unknown. Thus it is cru...
Drosophila simulans Software Gene Flow Computer Simulation Animals Genetics, Population Drosophila Genetic Variation Models, Genetic Genome, Insect Haplotypes Evolution, Molecular Genetic Speciation Species Specificity Hybridization, Genetic Supervised Machine Learning
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WORMHOLE: Novel Least Diverged Ortholog Prediction through Machine Learning.

PLoS computational biology Nov 3, 2016
The rapid advancement of technology in genomics and targeted genetic manipulation has made comparative biology an increasingly prominent strategy to model human disease processes. Predicting orthology relationships between species is a vital componen...
Sequence Homology, Amino Acid Genetic Speciation Evolution, Molecular Software Genetic Variation Humans Proteins Algorithms High-Throughput Nucleotide Sequencing Machine Learning Animals Pattern Recognition, Automated
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Deep Learning from Phylogenies for Diversification Analyses.

Systematic biology Dec 30, 2023
Birth-death (BD) models are widely used in combination with species phylogenies to study past diversification dynamics. Current inference approaches typically rely on likelihood-based methods. These methods are not generalizable, as a new likelihood ...
Genetic Speciation Animals Phylogeny Likelihood Functions Deep Learning Primates
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