AIMC Topic: Phylogeny

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Microbiome Preprocessing Machine Learning Pipeline.

Frontiers in immunology Jun 18, 2021
BACKGROUND: 16S sequencing results are often used for Machine Learning (ML) tasks. 16S gene sequences are represented as feature counts, which are associated with taxonomic representation. Raw feature counts may not be the optimal representation for ...
Mucositis Animals Phylogeny Hematopoietic Stem Cell Transplantation Mice Pregnancy Interleukin-1alpha Female Gastrointestinal Microbiome Colitis Adult RNA, Ribosomal, 16S Humans Bacteria Neural Networks, Computer Progesterone Machine Learning
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Machine-learning predicts genomic determinants of meiosis-driven structural variation in a eukaryotic pathogen.

Nature communications Jun 10, 2021
Species harbor extensive structural variation underpinning recent adaptive evolution. However, the causality between genomic features and the induction of new rearrangements is poorly established. Here, we analyze a global set of telomere-to-telomere...
Pedigree Meiosis Eukaryota Genome Genetic Variation Polymorphism, Genetic Ascomycota Retroelements Crossing Over, Genetic Genes, Duplicate Sequence Inversion INDEL Mutation Chromosomes Arabidopsis Computer Simulation Phylogeny Genome-Wide Association Study Models, Genetic Evolution, Molecular Genomics Polymorphism, Single Nucleotide Machine Learning
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Predicting direct and indirect non-target impacts of biocontrol agents using machine-learning approaches.

PloS one Jun 1, 2021
Biological pest control (i.e. 'biocontrol') agents can have direct and indirect non-target impacts, and predicting these effects (especially indirect impacts) remains a central challenge in biocontrol risk assessment. The analysis of ecological netwo...
Host-Parasite Interactions Hymenoptera Machine Learning Animals Lepidoptera Food Chain Introduced Species Pest Control, Biological Phylogeny Forests Diptera
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SPASOS 1.1: a program for the inference of ancestral shape ontogenies.

Cladistics : the international journal of the Willi Hennig Society May 28, 2021
We recently published a method to infer ancestral landmark-based shape ontogenies that takes into account the possible existence of changes in developmental timing. Here we describe SPASOS, a software to perform that analysis. SPASOS is an open-sourc...
Software Species Specificity Biological Evolution Algorithms Phylogeny Biological Ontologies
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Predicting the animal hosts of coronaviruses from compositional biases of spike protein and whole genome sequences through machine learning.

PLoS pathogens Apr 20, 2021
The COVID-19 pandemic has demonstrated the serious potential for novel zoonotic coronaviruses to emerge and cause major outbreaks. The immediate animal origin of the causative virus, SARS-CoV-2, remains unknown, a notoriously challenging task for eme...
Coronaviridae Coronaviridae Infections Machine Learning Animals Genome, Viral Biological Evolution Phylogeny Spike Glycoprotein, Coronavirus
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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...
Animals Ecosystem Phylogeny Machine Learning Gastropoda Antarctic Regions Genetic Speciation Gene Expression Profiling Sequence Analysis, DNA Gene Expression Regulation
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Harnessing machine learning to guide phylogenetic-tree search algorithms.

Nature communications Mar 31, 2021
Inferring a phylogenetic tree is a fundamental challenge in evolutionary studies. Current paradigms for phylogenetic tree reconstruction rely on performing costly likelihood optimizations. With the aim of making tree inference feasible for problems i...
Phylogeny Models, Genetic Databases, Genetic Evolution, Molecular Databases, Protein Machine Learning Algorithms Animals Humans
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MSA-Regularized Protein Sequence Transformer toward Predicting Genome-Wide Chemical-Protein Interactions: Application to GPCRome Deorphanization.

Journal of chemical information and modeling Mar 23, 2021
Small molecules play a critical role in modulating biological systems. Knowledge of chemical-protein interactions helps address fundamental and practical questions in biology and medicine. However, with the rapid emergence of newly sequenced genes, t...
Humans Machine Learning Ligands Sequence Alignment Phylogeny Computational Biology Amino Acid Sequence
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Using neural networks to mine text and predict metabolic traits for thousands of microbes.

PLoS computational biology Mar 2, 2021
Microbes can metabolize more chemical compounds than any other group of organisms. As a result, their metabolism is of interest to investigators across biology. Despite the interest, information on metabolism of specific microbes is hard to access. I...
Phylogeny Bacteria Computational Biology Fermentation Archaea Acetates Data Mining Neural Networks, Computer Databases, Factual
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Analysis of protein determinants of host-specific infection properties of polyomaviruses using machine learning.

Genes & genomics Mar 1, 2021
BACKGROUND: The large tumor antigen (LT-Ag) and major capsid protein VP1 are known to play important roles in determining the host-specific infection properties of polyomaviruses (PyVs).
Polyomavirus Capsid Proteins Host Specificity Antigens, Polyomavirus Transforming Machine Learning Phylogeny Amino Acids
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