Latest AI and machine learning research in genetics for healthcare professionals.
Quantitative genetic approaches such as genome-wide association studies and genomic prediction are widely used to identify favourable genetic variation, but they have limited resolution due to linkage disequilibrium. Comparative genomics approaches, especially Protein Language Models (PLMs), have emerged as powerful alternatives, by detecting phylogenetic residue conservation (PRC) across evolutio...
Drug-resistant tuberculosis (TB), characterized by prolonged treatment regimens and suboptimal treatment outcomes, remains a major obstacle to global TB elimination. Advances in sequencing technologies have enabled the development of machine-learning (ML) approaches, including deep-learning (DL) methods, to predict drug resistance directly from genomic data. However, a significant gap remains in t...
The cost of genomic sequencing has fallen by several orders of magnitude, yet data analysis remains a bottleneck concentrated among researchers with s...
As interest in RNA-based therapeutics expands, there is a growing demand for RNA structure elucidation and RNA-RNA interactions in both academic and c...
Tokens serve as the basic units of representation in DNA language models (DNALMs), yet their design remains underexplored. Unlike natural language, DN...
Pathology foundation models (FMs) have become central to computational histopathology, offering strong transfer performance across a wide range of dia...
For applications on the extreme edge, minimal networks of only a few dozen artificial neurons for event detection and classification in discrete time ...
Genomic language models (gLMs) have transformed computational biology, achieving state-of-the-art performance across genomic tasks. Yet a fundamental ...
Extrachromosomal DNA (ecDNA) represents one of the most pressing challenges in cancer biology: circular DNA structures that amplify oncogenes, evade t...
Immune checkpoint inhibitors (ICIs) have transformed cancer therapy; yet substantial proportion of patients exhibit intrinsic or acquired resistance, ...
Despite tremendous recent progress in human video generation, generative video diffusion models still struggle to capture the dynamics and physics of ...
N4-acetylcytidine (ac4C) is an ancient and highly conserved chemical marker found in all domains of life. Recent advancements in sequencing techniques...
The success of COVID-19 mRNA vaccines has made the in-solution stability optimization of mRNAs a key objective. However, we still lack a complete unde...
We study high-dimensional mediation analysis in which exposures, mediators, and outcomes are all multivariate, and both exposures and mediators may be...
Lateral gene transfer (LGT) has contributed to the genetic makeup of various eukaryotic lineages, yet its prevalence and long-term significance remain...
Modern recruitment platforms operate under severe information imbalance: job seekers must search over massive, rapidly changing collections of posting...
Background: Accurate preoperative prediction of lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) remains challenging, particularly in ...
Reliable, minimally invasive biomarkers for predicting immunotherapy response in head and neck squamous cell carcinoma (HNSCC) remain an unmet clinica...
Accurate prediction of drug-target binding affinity across multiple pharmacological endpoints remains challenging, as most deep learning methodologies...
The aging clock paradigm has yielded dozens of specialist models that can estimate chronological age or mortality from virtually any biodata type. Yet...