AIMC Topic: Evolution, Molecular
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Deep mutational learning for the selection of therapeutic antibodies resistant to the evolution of Omicron variants of SARS-CoV-2.
Nature biomedical engineering
Mar 5, 2025
Most antibodies for treating COVID-19 rely on binding the receptor-binding domain (RBD) of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). However, Omicron and its sub-lineages, as well as other heavily mutated variants, have rendered m...
A compendium of human gene functions derived from evolutionary modelling.
Nature
Feb 26, 2025
A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this g...
Pathogen genomic surveillance and the AI revolution.
Journal of virology
Jan 29, 2025
The unprecedented sequencing efforts during the COVID-19 pandemic paved the way for genomic surveillance to become a powerful tool for monitoring the evolution of circulating viruses. Herein, we discuss how a state-of-the-art artificial intelligence ...
Tailoring industrial enzymes for thermostability and activity evolution by the machine learning-based iCASE strategy.
Nature communications
Jan 11, 2025
The pursuit of obtaining enzymes with high activity and stability remains a grail in enzyme evolution due to the stability-activity trade-off. Here, we develop an isothermal compressibility-assisted dynamic squeezing index perturbation engineering (i...
Site-specific prediction of O-GlcNAc modification in proteins using evolutionary scale model.
PloS one
Dec 31, 2024
Protein glycosylation, a vital post-translational modification, is pivotal in various biological processes and disease pathogenesis. Computational approaches, including protein language models and machine learning algorithms, have emerged as valuable...
FluPMT: Prediction of Predominant Strains of Influenza A Viruses via Multi-Task Learning.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 9, 2024
Seasonal influenza vaccines play a crucial role in saving numerous lives annually. However, the constant evolution of the influenza A virus necessitates frequent vaccine updates to ensure its ongoing effectiveness. The decision to develop a new vacci...
CSEL-BGC: A Bioinformatics Framework Integrating Machine Learning for Defining the Biosynthetic Evolutionary Landscape of Uncharacterized Antibacterial Natural Products.
Interdisciplinary sciences, computational life sciences
Sep 30, 2024
The sluggish pace of new antibacterial drug development reflects a vulnerability in the face of the current severe threat posed by bacterial resistance. Microbial natural products (NPs), as a reservoir of immense chemical potential, have emerged as t...
Machine learning can be as good as maximum likelihood when reconstructing phylogenetic trees and determining the best evolutionary model on four taxon alignments.
Molecular phylogenetics and evolution
Aug 30, 2024
Phylogenetic tree reconstruction with molecular data is important in many fields of life science research. The gold standard in this discipline is the phylogenetic tree reconstruction based on the Maximum Likelihood method. In this study, we present ...
Deep learning can predict subgenome dominance in ancient but not in neo/synthetic polyploidized genomes.
The Plant journal : for cell and molecular biology
Aug 12, 2024
Deep learning offers new approaches to investigate the mechanisms underlying complex biological phenomena, such as subgenome dominance. Subgenome dominance refers to the dominant expression and/or biased fractionation of genes in one subgenome of all...
Reliable estimation of tree branch lengths using deep neural networks.
PLoS computational biology
Aug 5, 2024
A phylogenetic tree represents hypothesized evolutionary history for a set of taxa. Besides the branching patterns (i.e., tree topology), phylogenies contain information about the evolutionary distances (i.e. branch lengths) between all taxa in the t...
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