Infectious Disease

Latest AI and machine learning research in infectious disease for healthcare professionals.

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WormSpot: a machine learning-powered viability scoring platform in C. elegans for Candida pathogenicity studies

Invasive Candida infections pose a critical health challenge, exacerbated by emerging antifungal resistance. Caenorhabditis elegans (C. elegans) offers a genetically tractable and scalable model for studying Candida pathogenicity, yet conventional viability assays remain labor-intensive, limiting high-throughput applications. In this study, we developed a machine learning-driven worm viability sco...

AI-driven discovery and optimization of antimicrobial peptides from extreme environments on global scale

The escalating crisis of global antimicrobial resistance (AMR) necessitates the discovery of novel antibiotics. Antimicrobial peptides (AMPs), particularly those from under-explored extreme environments, represent a promising therapeutic class. Here, we introduce SEGMA (Structure-aware Extremophile Genome Mining for Antimicrobial peptides), a computational framework that integrates structure infor...

Phylogeny-agnostic strain-level prediction of phage-host interactions from genomes

Bacteriophages offer promising alternatives to antibiotics for treating drug-resistant infections and engineering microbiomes, but applications are li...

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...

A Multi-Agent Approach to Generating Context-Rich Gene Sets

Gene sets are collections of genes that share a common biological function, process, or component that can be used to get insight into the biological ...

Decoding pathogen ecological memory from chemical-stress phenotypes

Can standardized chemical stress reveal an ecological “memory” of host origin in plant pathogens? We profiled six coffee-associated Colletotrichum iso...

PanSpace: Fast and Scalable Indexing for Massive Bacterial Databases

Species identification is a critical task in agriculture, food processing, and health-care. The rapid growth of genomic databases — driven in part by ...

Design of multimodal antibiotics using deep learning

The rise of antimicrobial resistance has rendered many treatments ineffective, posing serious public health challenges. Intracellular infections are p...

SignalGen: A Protein Language Model Based AI Agent For Optimal Signal Peptide Prediction

Signal peptides are short amino acid sequences attached to the N-termini of mature proteins. They play determinant roles in protein expression as well...

SARS-CoV-2 Variant-Dependent Alterations in Nasopharyngeal Microbiota and Host Inflammatory Response

The SARS-CoV-2 pandemic saw multiple outbreaks occur over short periods. This was linked to the virus’s high infectivity and rapid mutation rate, whic...

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-...

H3BERTa: A CDR-H3 specific language model for antibody repertoire analysis

Antibodies are central to immune defense and therapeutic design, yet predicting which sequences confer functional activity remains challenging. Deep l...

BudFinder: A Masked Auto-Encoder Vision Transformer Framework for Yeast Budding Detection

Yeast replicative lifespan is a crucial part of aging research, yet its quantification remains labor-intensive and time-consuming, particularly when u...

Sequence-aware Prediction of Point Mutation-induced Effects on Protein-Protein Binding Affinity using Deep Learning

Amino acid mutations may lead to significant changes in the binding affinity of protein complexes, thereby causing a series of cellular dysfunctions. ...

Predicting strain-specific metabolic capabilities in the Genus Pseudomonas using a Flux-to-AI approach unravels hidden cell envelope properties

Bacteria from the Pseudomonas genus are omnipresent in air, soil, and water. They have been widely studied for their broad metabolic versatility and p...

Adapting CRISPR-associated transposons for rapid and high-throughput reverse genetics

CRISPR-associated transposons (CAST) use guide RNAs to direct their transposition and are being harnessed as tools for programmable genome engineering...

Reinforcement learning for adaptive control of phenotypically heterogeneous bacterial populations

Bacterial populations display extraordinary resilience to antibiotic stress, driven by diverse physiological states that allow some cells to persist a...

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...

Cross-Molecular Active Learning for the Discovery of Antimicrobial Polyacrylamides

Antimicrobial resistance poses an urgent and increasing threat to global health. The development of new antimicrobials is crucial. Synthetic copolymer...

Ultrahigh throughput screening to train generative protein models for engineering specificity into unspecific peroxygenases

Enzyme engineering is central to developing biocatalysts with improved activity and specificity, yet traditional approaches are often limited by the s...

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