Genetics

Qimai: a multi-agent framework for zero-shot DNA-protein interaction prediction

Accurate prediction of DNA-protein interactions, a fundamental task in genomics, is limited by the poor generalization of existing models to novel proteins not seen during training. To address this challenge, we introduce Qimai, a modular AI agent framework that integrates deep learning predictions with biological evidence using Large Language Model (LLM) as reasoning engine. Qimai combines direct...

A validated set of neural gene reporter mice and chemical tracers tools for mapping knee innervating neurons

Joint pain is an increasing concern for our aging population, as current therapies to slow joint disease progression or reduce pain are largely ineffective and often carry significant health and dependency risks. Age and joint disease induce changes to all tissues that make up the joint, including the dense neural network that innervates the joint. Several studies have correlated some joint innerv...

Structural constraints acting on the SARS-CoV-2 spike protein reveal limited space for viral adaptation

The SARS-CoV-2 pandemic resulted in an unprecedented scientific response. The enormous scale of global genome sequencing, protein structural determina...

PARSEbp: Pairwise Agreement-based RNA Scoring with Emphasis on Base Pairings

High-fidelity scoring of RNA 3D structures remains a major challenge in RNA structure prediction and conformational sampling. While single-model metho...

TRUHiC: A TRansformer-embedded U-2 Net to enhance Hi-C data for 3D chromatin structure characterization

High-throughput chromosome conformation capture sequencing (Hi-C) is a key technology for studying the three-dimensional (3D) structure of genomes and...

Single-cell RNA sequencing and large-scale bulk combination with machine learning reveal gastric cancer-related macrophage heterogeneity

The tumor microenvironment (TME) significantly impacts cancer progression and overall patient survival. However, the complexity of tumor cell-TME inte...

Genotype-phenotype modeling of light ecotypes in Prochlorococcus reveals genomic signatures of ecotypic divergence

Prochlorococcus is a cyanobacterial genus that exhibits photosynthetic capacity and remarkable genetic diversity. We analyze how Prochlorococcus genom...

Deep Learning Bridges Histology and Transcriptomics to Predict Molecular Subtypes and Outcomes in Muscle-Invasive Bladder Cancer

Muscle-Invasive Bladder Cancer (MIBC) is a heterogeneous disease with distinct molecular subtypes influencing prognosis and therapeutic response. Howe...

Agent SPI-WSI: In context learning for computationally spatial pathway inferring on whole slide histopathology images conditioned on bulk RNA sequencing using pathologist in the loop

Bulk RNA sequencing, while cost-effective compared to high-resolution spatial transcriptomics, averages gene expression across heterogeneous cell popu...

Simulation and empirical evaluation of biologically-informed neural network performance

Biologically-informed neural networks (BiNNs) offer interpretable deep learning models for biological data, but the dataset characteristics required f...

Control of gene output by intron RNA structure

Intron removal through pre-mRNA splicing is a central step in gene expression across Eukarya. The process initiates with the recognition of intronic s...

Multi-Dimensional Spatiotemporal Attention Neural Network for Next Generation Sequencing Basecalling

Next-generation sequencing (NGS) remains the most used sequencing technique in the field of genomics. Traditional basecall methods face significant ch...

From Circles to Signals: Representation Learning on Ultra-Long Extrachromosomal Circular DNA

Extrachromosomal circular DNA (eccDNA) is a covalently closed circular DNA molecule that plays an important role in cancer biology. Genomic foundation...

A deep learning framework for building INDEL mutation rate maps

Germline short insertions and deletions (INDELs) are pervasive genetic variants that shape genome evolution and contribute to human disease. However, ...

Morphology-Guided Deep Learning for Nanoparticle Agglomeration Diagnostic Assays

Affordable, accurate, and rapid point-of-care diagnostic tests remain elusive due to inherent trade-offs between performance and cost. Conventional nu...

USP-ddG: A Unified Structural Paradigm with Data Efficacy and Mixture-of-Experts for Predicting Mutational Effects on Protein-Protein Interactions

Accurately estimating changes in binding free energy (ΔΔG) is essential for understanding protein-protein interactions (PPIs) and guiding rational pro...

An Enhanced Variant-Aware Deep Learning Model for Individual Gene Expression Prediction

Accurate prediction of gene expression from individual whole-genome sequences is critical for understanding disease mechanisms and advancing precision...

A machine learning framework for supervised treatment response prediction from tumor transcriptomics: A large-scale pan-cancer study

Precision oncology aims to guide treatment decisions using biomarkers. While DNA-based panels are increasingly applied, RNA transcriptomics remain und...

Integrative spatial multi-omics reveals prognostic tumor niches in female genital tumors

Female genital tumors (FGTs), including ovarian, endometrial, and cervical cancers, pose a major global health challenge, yet their spatial and molecu...

Covary: A translation-aware framework for alignment-free phylogenetics using machine learning

In large-scale phylogenetic analysis, incorporating translation awareness is critical to account for the genotypic and phenotypic dimensions underlyin...