Infectious Disease

Museum collections and machine learning guide discovery of novel coronaviruses and paramyxoviruses

Natural history museum collections are valuable but underutilized resources for viral discovery, offering opportunities to test hypotheses about viral occurrence across space, time, and taxonomic groups. We developed machine learning models of bat host suitability to guide coronavirus and paramyxovirus screening of 1330 and 491 tissues, respectively, in a museum collection. For the first time, we ...

Fusing Sequence Motifs and Pan-Genomic Features: Antimicrobial Resistance Prediction using an Explainable Lightweight 1D CNN - XGBoost Ensemble

Antimicrobial Resistance (AMR) is a rapidly escalating global health crisis. While genomic sequencing enables rapid prediction of resistance phenotypes, current computational methods have limitations. Standard machine learning models treat the genome as an unordered collection of features, ignoring the sequential context of Single Nucleotide Polymorphisms (SNPs). State-of-the-art sequence models l...

Synthetic community Hi-C benchmarking provides a baseline for virus-host inferences

Microbiomes influence diverse ecosystems, and viruses increasingly appear to impose key constraints. While viromics has expanded genomic catalogs, hos...

A Generative Foundation Model for Antibody Design

Antibodies are indispensable components of the immune system, yet the design of high-affinity antibodies remains a time-consuming and experimentally i...

An Improved Dataset for Predicting Mammal Infecting Viruses from Genetic Sequence Information

There have been several attempts to develop machine learning (ML) models to identify human infecting viruses from their genomic sequences, with varyin...

SoluProtMut: Siamese Deep Learning for Predicting Solubility Effects of Protein Mutations with Experimental Validation

Protein solubility is an attractive engineering target because it is a critical property influencing the scalability of protein production and the suc...

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 th...

PhageAI: a new approach to predicting the lifestyle of bacteriophages using proteinBERT and convolutional neural networks

Bacteriophages are viruses that infect bacteria, including temperate, virulent and chronic phages. In the current times of increasing resistance to an...

Geno2pheno[bNAbs]: Interpretable and accurate HIV antibody resistance prediction

Antiretroviral therapy (ART) is a life saving option for people living with HIV-1 (PLWH) and is effective against many viral strains. The most common ...

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...

Context-Aware Synthetic Promoter Design Using Neural Networks Enables Rewiring of Eukaryotic Transcriptional Networks

Gene regulation through promoter engineering is a cornerstone of synthetic biology, enabling precise control over transcriptional networks. However, e...

scAgeClock: a single-cell transcriptome based human aging clock model using gated multi-head attention neural networks

Aging Clock models have emerged as a crucial tool for measuring biological age, with significant implications for anti-aging interventions and disease...

Partial Inhibition of Viral Replication Machinery Enhances Recombination in Herpes Simplex Viruses

Herpes simplex viruses (HSV-1 and HSV-2) are widespread human pathogens, most commonly causing oral and genital lesions. These DNA viruses use recombi...

BIOTIA-DX RESISTANCE Achieved the Best Antimicrobial Resistance Phenotype Prediction Accuracy at CAMDA 2025

We have developed BIOTIA-DX RESISTANCE (BDXR), a bioinformatic tool for predicting antimicrobial resistance (AMR) from whole genome sequencing of micr...

Predicting Clinical Outcomes in Helicobacter pylori-positive Patients using Supervised Learning through the Integration of Demographic and Genomic Features

Helicobacter pylori (H. pylori) infection is widespread globally and is linked to outcomes ranging from chronic gastritis to gastric cancer. However, ...

Augmented prediction of multi-species protein–RNA interactions using evolutionary conservation of RNA-binding proteins

RNA-binding proteins (RBPs) play critical roles in gene expression regulation. Recent studies have begun to detail the RNA recognition mechanisms of d...

Automating Candidate Gene Prioritization with Large Language Models: From Naive Scoring to Literature-Grounded Validation

Identifying promising therapeutic targets from thousands of genes in transcriptomic studies remains a major bottleneck in biomedical research. While l...

How many crystal structures do you need to trust your docking results?

Structure-based drug discovery technologies generally require the prediction of putative bound poses of protein:small molecule complexes to prioritize...

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...