COVID-19

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 therapeutics and vaccines. While deep learning shows promise for in silico prediction, the scarcity of comprehensive immunogenicity data is a major challenge. We present T-SCAPE, a novel multi-domain deep learning framework that leverages adversarial d...

Beyond Sequence Similarity: ML-Powered Identification of pHLA Off-Targets for TCR-Mimic Antibodies Using High Throughput Binding Kinetics

T-cell receptor mimic (TCRm) antibodies are an emerging class of tumor-targeting agents used in advanced immunother-apies such as bispecific T-cell engagers and CAR-T cells. Unlike conventional antibodies, TCRms are designed to recognize peptide–human leukocyte antigen (pHLA) complexes that present intracellular tumor-derived peptides on the cell surface. Due to the typically low surface abundance...

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...

FAST: Filamentous Actin Segmentation Tool for quantifying cytoskeletal organization

Studying how actin filaments are assembled into different subcellular structures can provide insights into both physiological processes and the mechan...

A comparative study of plant phenotyping workflows based on three-dimensional reconstruction from multi-view images

With the world facing escalating food demand, limited agricultural land, and environmental change, there is a growing need for data-driven sustainable...

Generation of a global freshwater algal taxonomic database by application of PCR-free rbcL gene detection and machine-learning-based taxonomic classification to public metagenome datasets

While it has become increasingly evident that microalgae are critical components of aquatic ecosystems, comprehensive taxonomic analysis of the microa...

Pocket Restraints Guided by B-Cell Epitope Prediction Improves Chai-1 Antibody-Antigen Structure Modeling

The accurate prediction of antibody-antigen (AbAg) complexes is a key challenge for computational immunology, with applications in therapeutic antibod...

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...

A Biosecurity Agent for Lifecycle LLM Biosecurity Alignment

Large language models (LLMs) are increasingly integrated into biomedical re-search workflows-from literature triage and hypothesis generation to exper...

Iterative improvement of deep learning models using synthetic regulatory genomics

Deep learning models can accurately reconstruct genome-wide epigenetic tracks from the reference genome sequence alone. But it is unclear what predict...

Unveiling the Human Nasopharyngeal Microbiome Compendium: Systematic Characterization of Community Architecture and Function Through a Comprehensive Meta-Analysis

The nasopharyngeal microbiome acts as a dynamic interface between the human body and environmental exposures, modulating immune responses and helping ...

Fine-tuning sequence to function deep learning models on large-scale proteomic data improves the accuracy of variant effect prediction

Fine-tuning sequence to function models has shown promise for variant effect prediction, but accuracy and generalization to unseen genes and unseen in...

Aging diminishes interlaminar functional connectivity in the mouse cortical V1 and CA1 hippocampal regions

Aging disrupts brain network integration and is a significant risk factor for cognitive decline and neurological diseases, yet the circuit-level mecha...

mBER: Controllable de novo antibody design with million-scale experimental screening

Recent machine learning approaches have achieved high success rates in designing protein binders that demonstrate in vitro binding to their targets. W...

LoFT-TCR: A LoRA-based Fine-tuning Framework for TCR-Antigen Binding Prediction

T cells recognize and eliminate diseased cells by binding their T cell receptors (TCRs) to short endogenous peptides (antigens) presented on the cell ...

Non-Invasive Diagnostic Evaluation of Urinary Exosomal Let-7c Cluster Expression in Bladder Cancer Using Machine Learning Approaches

Bladder cancer (BCa) diagnosis typically relies on invasive cystoscopy, which is effective but costly and uncomfortable. Urinary microRNAs (miRNAs), e...

A Benchmark of Evo2 Genomic AI Models for Efficient and Practical Deployment

The rapid advancement of DNA foundation language models has brought about a transformative shift in genomics, allowing for the deciphering of intricat...

A Systematic Comparison of Single-Cell Perturbation Response Prediction Models

Predicting single-cell transcriptional responses to perturbations is central to dissecting gene regulation and accelerating therapeutic design, yet th...

RPEGENE-Net: A Multi-Resolution Deep Learning Framework for Predicting Gene Expression from Microscopy Images of Retinal Pigment Epithelium (RPE) Cells

To develop a deep learning framework, RPEGENE-Net, capable of predicting gene expression profiles of retinal pigment epithelium (RPE) cells using live...