AIMC Topic: Phylogeny
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Learning From an Artificial Neural Network in Phylogenetics.
IEEE/ACM transactions on computational biology and bioinformatics
Apr 3, 2024
We show that an iterative ansatz of deep learning and human intelligence guided simplification may lead to surprisingly simple solutions for a difficult problem in phylogenetics. Distinguishing Farris and Felsenstein trees is a longstanding problem i...
Applications of machine learning in phylogenetics.
Molecular phylogenetics and evolution
Mar 31, 2024
Machine learning has increasingly been applied to a wide range of questions in phylogenetic inference. Supervised machine learning approaches that rely on simulated training data have been used to infer tree topologies and branch lengths, to select s...
Utilizing genomic signatures to gain insights into the dynamics of SARS-CoV-2 through Machine and Deep Learning techniques.
BMC bioinformatics
Mar 27, 2024
The global spread of the SARS-CoV-2 pandemic, originating in Wuhan, China, has had profound consequences on both health and the economy. Traditional alignment-based phylogenetic tree methods for tracking epidemic dynamics demand substantial computati...
Identification of B cell subsets based on antigen receptor sequences using deep learning.
Frontiers in immunology
Mar 21, 2024
B cell receptors (BCRs) denote antigen specificity, while corresponding cell subsets indicate B cell functionality. Since each B cell uniquely encodes this combination, physical isolation and subsequent processing of individual B cells become indispe...
Multi-armed bandits, Thomson sampling and unsupervised machine learning in phylogenetic graph search.
Cladistics : the international journal of the Willi Hennig Society
Feb 28, 2024
A phylogenetic graph search relies on a large number of highly parameterized search procedures (e.g. branch-swapping, perturbation, simulated annealing, genetic algorithm). These procedures vary in effectiveness over datasets and at alternative point...
Novel antimicrobial peptides against Cutibacterium acnes designed by deep learning.
Scientific reports
Feb 24, 2024
The increasing prevalence of antibiotic resistance in Cutibacterium acnes (C. acnes) requires the search for alternative therapeutic strategies. Antimicrobial peptides (AMPs) offer a promising avenue for the development of new treatments targeting C....
Taxonomy, biological characterization and fungicide sensitivity assays of Hypomyces cornea sp. nov. causing cobweb disease on Auricularia cornea.
Fungal biology
Dec 31, 2023
Auricularia cornea is an important edible mushroom crop in China but the occurrence of cobweb disease has cause significance economic loss in its production. The rate of disease occurrence is 16.65% all over the country. In the present study, a new p...
Parsing 20 Years of Public Data by AI Maps Trends in Proteomics and Forecasts Technology.
Journal of proteome research
Dec 14, 2023
The trends of the last 20 years in biotechnology were revealed using artificial intelligence and natural language processing (NLP) of publicly available data. Implementing this "science-of-science" approach, we capture convergent trends in the field ...
A novel method for identifying key genes in macroevolution based on deep learning with attention mechanism.
Scientific reports
Nov 13, 2023
Macroevolution can be regarded as the result of evolutionary changes of synergistically acting genes. Unfortunately, the importance of these genes in macroevolution is difficult to assess and hence the identification of macroevolutionary key genes is...
Unsupervised machine learning for species delimitation, integrative taxonomy, and biodiversity conservation.
Molecular phylogenetics and evolution
Oct 5, 2023
Integrative taxonomy, combining data from multiple axes of biologically relevant variation, is a major goal of systematics. Ideally, such taxonomies will derive from similarly integrative species-delimitation analyses. Yet, most current methods rely ...
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