AIMC Topic: Phylogeny

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Microbiome determinants of productivity in aquaculture of whiteleg shrimp.

Applied and environmental microbiology Apr 15, 2025
UNLABELLED: Aquaculture holds immense promise for addressing the food needs of our growing global population. Yet, a quantitative understanding of the factors that control its efficiency and productivity has remained elusive. In this study, we addres...
Animals Aquaculture Microbiota Penaeidae Phylogeny Larva Bacteria
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aurora: a machine learning gwas tool for analyzing microbial habitat adaptation.

Genome biology Mar 23, 2025
A primary goal of microbial genome-wide association studies is identifying genomic variants associated with a particular habitat. Existing tools fail to identify known causal variants if the analyzed trait shaped the phylogeny. Furthermore, due to in...
Machine Learning Software Ecosystem Adaptation, Physiological Phylogeny Genome-Wide Association Study Bacteria
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Equitable machine learning counteracts ancestral bias in precision medicine.

Nature communications Mar 10, 2025
Gold standard genomic datasets severely under-represent non-European populations, leading to inequities and a limited understanding of human disease. Therapeutics and outcomes remain hidden because we lack insights that could be gained from analyzing...
Precision Medicine Female Breast Neoplasms Neoplasms Phylogeny Genomics Humans Machine Learning
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Machine learning models accurately predict clades of proteocephalidean tapeworms (Onchoproteocephalidea) based on host and biogeographical data.

Cladistics : the international journal of the Willi Hennig Society Mar 6, 2025
Proteocephalids are a cosmopolitan and diverse group of tapeworms (Cestoda) that have colonized vertebrate hosts in freshwater and terrestrial environments. Despite the ubiquity of the group, key macroevolutionary processes that have driven the group...
Phylogeography Cestoda Machine Learning Animals Phylogeny
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Decoding the blueprint of receptor binding by filoviruses through large-scale binding assays and machine learning.

Cell host & microbe Jan 15, 2025
Evidence suggests that bats are important hosts of filoviruses, yet the specific species involved remain largely unidentified. Niemann-Pick C1 (NPC1) is an essential entry receptor, with amino acid variations influencing viral susceptibility and spec...
Chiroptera Hemorrhagic Fever, Ebola Receptors, Virus Protein Binding Glycoproteins Ebolavirus Filoviridae Niemann-Pick C1 Protein Filoviridae Infections Humans Machine Learning Animals Phylogeny
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Identifying human activities causing water pollution based on microbial community sequencing and source classifier machine learning.

Environment international Dec 24, 2024
Identifying and differentiating human activities is crucial for effectively preventing the threats posed by environmental pollution to aquatic ecosystems and human health. Machine learning (ML) is a powerful analytical tool for tracking human impacts...
Machine Learning China Water Microbiology Ecosystem Environmental Monitoring Phylogeny Microbiota Human Activities RNA, Ribosomal, 16S Humans Water Pollution Rivers
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Comparative analysis of the human microbiome from four different regions of China and machine learning-based geographical inference.

mSphere Dec 19, 2024
The human microbiome, the community of microorganisms that reside on and inside the human body, is critically important for health and disease. However, it is influenced by various factors and may vary among individuals residing in distinct geographi...
Mouth Nasal Cavity Skin Hand Microbiota DNA, Bacterial RNA, Ribosomal, 16S Sequence Analysis, DNA Adult Phylogeny Machine Learning Male China Female Middle Aged Humans Bacteria Young Adult
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Neural network-based predictions of antimicrobial resistance phenotypes in multidrug-resistant from whole genome sequencing and gene expression.

Antimicrobial agents and chemotherapy Nov 14, 2024
Whole genome sequencing (WGS) potentially represents a rapid approach for antimicrobial resistance genotype-to-phenotype prediction. However, the challenge still exists to predict fully minimum inhibitory concentrations (MICs) and antimicrobial susce...
Microbial Sensitivity Tests Drug Resistance, Multiple, Bacterial Genotype Whole Genome Sequencing Acinetobacter Infections Multilocus Sequence Typing Anti-Bacterial Agents Acinetobacter baumannii Genome, Bacterial Phenotype Humans Phylogeny Neural Networks, Computer
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Phylogenomics and phylogeographic model testing using convolutional neural networks reveal a history of recent admixture in the Canarian Kleinia neriifolia.

Molecular ecology Oct 19, 2024
Multiple-island endemics (MIE) are considered ideal natural subjects to study patterns of island colonization that involve recent population-level genetic processes. Kleinia neriifolia is a Canarian MIE widespread across the archipelago, which exhibi...
Phylogeny Polymorphism, Single Nucleotide Phylogeography Neural Networks, Computer Genetics, Population Islands Plastids
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Deep learning to capture leaf shape in plant images: Validation by geometric morphometrics.

The Plant journal : for cell and molecular biology Oct 9, 2024
Plant leaves play a pivotal role in automated species identification using deep learning (DL). However, achieving reproducible capture of leaf variation remains challenging due to the inherent "black box" problem of DL models. To evaluate the effecti...
Image Processing, Computer-Assisted Plant Leaves Neural Networks, Computer Phylogeny Deep Learning
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