Latest AI and machine learning research in infectious disease for healthcare professionals.
The escalating crisis of antibiotic resistance underscores the urgent need for innovative anti-infective agents, such as antimicrobial peptides (AMPs), though their discovery and optimization remain challenging. To address this, we introduce AMP-D3, a comprehensive framework that integrates AMP generation, identification, and screening into a cohesive workflow. Central to AMP-D3 is PACD, an advanc...
Molecular simulations have become indispensable in biological research. Their accuracy continues to improve, but directly modelling biochemical reactions – central to all life processes – remains computationally challenging. Here, we present a biomolecular reaction emulator that models reactions across conformational ensembles using kinetic Monte Carlo. Our method, KIMMDY, is capable of handling d...
Computational tools are frequently used to describe pathogen evolutionary dynamics either within infected hosts or at the population level. However, t...
Emerging viruses pose an ongoing threat to human health. While certain viral families are common sources of outbreaks, predicting the specific virus w...
Since ancient hepatitis B virus (HBV) sequencing data are scarce and incomplete, the evolutionary dynamics of HBV have long remained enigmatic. This d...
Increasing concerns regarding prolonged antibiotic usage have spurred the search for alternative treatments. Antimicrobial peptides (AMPs), first disc...
Given that influenza vaccine effectiveness depends on a good antigenic match between the vaccine and circulating viruses, it is important to assess th...
The design of novel proteins with tailored functionalities, particularly in drug discovery and vaccine development, presents a transformative approach...
Accurately and robustly representing drug molecule features, prediction of drug-target biomacromolecule interactions, and determining drug molecule ph...
Canola blackleg is a fungal disease that causes significant yield loss and plant death of infected canola (Brassica napus L., Brassica rapa L., Brassi...
The COVID-19 pandemic has generated a vast volume of research, yet much of it focuses on individual diseases, overlooking complex comorbidity relation...
Recent advances in deep learning, particularly transformer architectures, have improved computational approaches for biological sequence analysis. Des...
Since the emergence of SARS-CoV-2, numerous studies have investigated antibody interactions with viral variants in vitro, and several datasets have be...
Influenza A virus (IAV) poses a significant threat to animal health globally, with its ability to overcome species barriers and cause pandemics. Rapid...
Morphological switching in response to environmental stimuli is a well-known phenomenon in fungi, leading to diverse morphotypes. Microscopic observat...
Phospholipidosis is a cellular condition characterized by the excessive accumulation of phospholipids within cells, that also can be induced by medica...
Accurate genome annotation is fundamental to decoding viral diversity and understanding bacteriophage biology; yet, the majority of bacteriophage gene...
Information on causal relationships is essential to many sciences, including biomedical science, and beneficial (e.g., causative rather than merely as...
Bacteriocins offer a promising solution to antibiotic resistance, possessing the ability to target a wide range of bacteria with precision. Thus, ther...
Pre-trained large models have emerged as a pivotal technological approach for foundational cell modeling. However, existing deep learning-based founda...