Latest AI and machine learning research in covid-19 for healthcare professionals.
Identifying effective neoantigen sequences is essential for enhancing anti-tumor immunity. However, the vast sequence space (>109 possible peptides) and limited accuracy of existing immunogenicity predictors hinder efficient vaccine design for patient-specific human leukocyte antigens (HLAs). We present AlphaVacc, a deep reinforcement learning framework that integrates Monte Carlo Tree Search with...
Recent advances in diffusion models have shown remarkable potential for antibody design, yet existing approaches apply uniform generation strategies that cannot adapt to each antigen’s unique requirements. Inspired by B cell affinity maturation—where antibodies evolve through multi-objective optimization balancing affinity, stability, and self-avoidance—we propose the first biologically-motivated ...
Computational antibody design has seen many recent advances pioneered via the use of language models and advanced structure prediction tools. Developi...
RNA language models have achieved strong performances across diverse down-stream tasks by leveraging large-scale sequence data. However, RNA function ...
Broadly neutralizing antibodies (bNAbs) that target the envelope glycoprotein (Env) of human immunodeficiency virus-1 (HIV-1) have been utilized in cl...
Therapeutic antibody development faces persistent immunogenicity challenges from anti-drug antibodies (ADA). Identifying peptide fragments presented b...
Helicobacter pylori is a significant risk factor for gastric cancer, peptic ulcers, and MALT lymphoma. Rising antibiotic resistance rates complicate t...
Pneumocystis jirovecii is a fungal pathogen causing Pneumocystis pneumonia in humans, mainly in immunocompromised individuals. Infections by P. jirove...
Predictive processing theories propose that the brain supervises itself, to build an internal model of its environment. This internal model emerges by...
B-cells get activated through interaction with B-cell epitopes, a specific portion of the antigen. Identification of B-cell epitopes is crucial for a ...
The bacterial pan-genome consists of core genes shared by all members of a taxonomy and accessory genes found in only a subset. The correlation among ...
Missense variants play a key role in the diagnosis of genetic disorders and in disease risk prediction. Existing methods focus primarily on the predic...
Molecular diffusion models suffer from systematic sampling biases that prevent optimal structure formation, resulting in chemically suboptimal molecul...
Humans spend approximately 90% of their lives in built environments, making virus transmission indoors a key determinant of health. Environmental samp...
Scientific discovery in the life sciences remains hindered by fragmented workflows, narrow-scope computational models, and inefficient links between i...
In precision oncology, researchers often use public knowledgebases to check somatic variant frequencies against their cohort data. Large language mode...
Natural history museum collections are valuable but underutilized resources for viral discovery, offering opportunities to test hypotheses about viral...
Advancements in whole genome sequencing have increased the number of variants of uncertain significance (VUS) identified in patient genomes. This has ...
MicroRNAs (miRNAs) serve critical regulatory roles in gene expression and are valuable biomarkers for early disease detection. However, their inherent...
Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, yet the majority lie in noncoding regions...