Public Health

T-SCAPE: T-cell Immunogenicity Scoring via Cross-domain Aided Predictive Engine

T-cell immunogenicity, the ability of peptide fragments to elicit T-cell responses, is a critical determinant of the safety and efficacy of protein therapeutics and vaccines. While deep learning shows promise for in silico prediction, the scarcity of comprehensive immunogenicity data is a major challenge. We present T-SCAPE, a novel multi-domain deep learning framework that leverages adversarial d...

Mapping Risk and Conservation Potential Across the Indo-Pacific with Reefshark Genomescapes

Overfishing has severely depleted marine populations worldwide, including within protected areas. Illegal and unreported fishing are major contributors to this decline. Large-bodied apex predators such as sharks are among the most affected, with overfishing causing dramatic species declines and ecosystem destabilization due to trophic downgrading. Key barriers to effective marine conservation and ...

Machine Learning Enables Viral Genome-Agnostic Classification of RNA Virus Infections from Host Transcriptomes

Targeted PCR diagnosis of RNA viruses is sequence dependent, meaning that the accuracy of the assay depends on the identity of the viral sequence. How...

Species-agnostic and Salmonella-specific Models for Antimicrobial Resistance Prediction Using FCGR and ResNet-18

Antimicrobial resistance (AMR) prediction from bacterial genomes remains a major challenge for clinical microbiology and surveillance. We developed de...

Recovery of human upper airway epithelium after smoking cessation is driven by a slow-cycling stem cell population and immune surveillance

The upper airway epithelium in humans is maintained in homeostasis by a resident population of basal stem cells. In the presence of tobacco smoke thes...

Hollow-fibre biomanufacturing and cell-free engineering of HEK293 extracellular vesicles

Extracellular vesicles (EVs) are lipid-delineated nanoparticles that are produced by most cell types. EVs contain complex molecular cargoes that can h...

Machine learning based lineage prediction from AMR phenotypes for Escherichia coli ST131 clade C surveillance across infection types

Rising antimicrobial resistance (AMR) in Escherichia coli bloodstream infections (BSIs) in high-income settings has typically been dominated by one cl...

An AI for an AI: identifying zoonotic potential of avian influenza viruses via genomic machine learning

Avian influenza remains a serious risk to human health via zoonotic transmission, as well as a feasible pandemic threat. Although limited zoonotic cas...

Predicting Risk of Transfusion-Induced Red Blood Cell Alloimmunization Using Statistical and Machine Learning Approaches in the Recipient Epidemiology and Donor Evaluation Study (REDS-III) Database

Red blood cell (RBC) alloimmunization is a common complication from blood transfusion, often resulting in accelerated donor RBC destruction. Patients ...

Structurally Informed Fitness Landscapes for Surveillance of Emerging PRRSV Variants

Antibodies play a central role in neutralizing pathogens through direct interference with viral entry and recruitment of effector immune cells. Howeve...

peleke-1: A Suite of Protein Language Models Fine-Tuned for Targeted Antibody Sequence Generation

The discovery of therapeutic antibodies is a traditionally arduous process. Today, the lab-based process of antibody discovery consists of several tim...

An Immuno-Linguistic Transformer for Multi-Scale Modeling of T-Cell Spatiotemporal Dynamics

Understanding the spatiotemporal dynamics of T-cell clones is a critical challenge in immunology and immunotherapy, with direct implications for cance...

Hybrid Epidemic–Neuronal Dynamics: A SEIR–FitzHugh–Nagumo Model for Information Flow in Complex Neural Networks

Information transfer in neural systems is often modeled through diffusive or synaptic mechanisms that fail to capture the contagion-like propagation o...

Deciphering the Antigenic Evolution of Seasonal Influenza A Viruses with PREDAC-Transformer: From Antigenic Clustering to Key Site Identification

Seasonal influenza viruses undergo continuous antigenic drift due to mutations in the hemagglutinin (HA) protein, rendering vaccines ineffective and p...

A study on edge devices for image classification of the Tasmanian devil (Sarcophilus harrisii) for vaccine delivery

A target-specific bait dispenser is required for oral bait vaccination of the endangered Tasmanian devil (Sarcophilus harrisii) against the deadly dev...

Machine learning–assisted selection of informative loci for strain-level phylogenetics of Neisseria gonorrhoeae

Epidemiological surveillance of Neisseria gonorrhoeae is hindered by the limitations of existing molecular typing methods, such as NG-MAST and MLST, w...

Multivariate analysis of glycogenes reveals coordinated regulation of immunoglobulin glycosylation in an immortalized human B cell system

While neutralizing ability has traditionally been considered the most important antibody function, appreciation has grown for Fc-mediated ‘extra-neutr...

What kind of birds are more susceptible to avian malaria? A global analysis based on interpretable machine learning approach

Avian malaria (genus Plasmodium) is a mosquito-transmitted parasitic disease of birds. It has a wide distribution across the world, infecting more tha...

Lab-in-the-loop therapeutic antibody design with deep learning

Therapeutic antibody design is a complex multi-property optimization problem with substantial promise for improvement with the application of machine-...

Iterative immunogen optimization to focus immune responses on a conserved, subdominant viral epitope

Designing effective vaccination strategies against genetically diverse viruses, such as HIV or influenza, is hindered by the ability of these pathogen...