Genetics

dnaHNet: A Scalable and Hierarchical Foundation Model for Genomic Sequence Learning

Genomic foundation models have the potential to decode DNA syntax, yet face a fundamental tradeoff in their input representation. Standard fixed-vocabulary tokenizers fragment biologically meaningful motifs such as codons and regulatory elements, while nucleotide-level models preserve biological coherence but incur prohibitive computational costs for long contexts. We introduce dnaHNet, a state-of...

Interpretable machine learning model for predicting kidney failure among CAKUT children in multicenter large-scale study

Congenital anomalies of the kidney and urinary tract (CAKUT) are the leading cause of pediatric kidney failure, but predicting individual progression remains challenging. This multicenter study developed and validated POCC, a machine learning model for predicting kidney failure risk at 1, 3, and 5 years post-diagnosis in CAKUT patients. Two versions were created using data from 2,249 children. The...

Structural phenotypes of osteoarthritis are clinically and genetically distinct: findings from 59,539 UK Biobank participants

OBJECTIVES Osteoarthritis is a heterogeneous disease, with diverse structural patterns likely reflecting distinct genetic drivers. Robust, data-driven...

Multi-omics Analyses of Facial Skin in Acne Identify Distinct Microbial and Metabolic Features at Lesional and Non-lesional Sites

The microbial and biochemical landscape of clinically normal-appearing skin in individuals with acne remains uncharacterized. Here, we performed longi...

Leveraging Foundation Models for the Characterisation of Small RNA Properties

ABSTRACT Small interfering RNAs (siRNAs) provide a promising therapeutic approach capable of selectively silencing disease-associated genes; however, ...

Autoregressive forecasting of future single-cell state transitions

Existing methods for dynamic analysis of static single-cell RNA-sequencing data can reconstruct temporal structures covered by observed cells, but can...

SERPINA3 and NDRG1 are critical diagnostic immune genes associated with macrophages in preeclampsia

Objective: The immune system plays a role in the occurrence and progression of numerous pregnancy complications, particularly preeclampsia (PE). This ...

Single-Cell and Spatial Transcriptomics Integration Identifies Mural Cell Oxidative Stress Genes Clu and Gria2 as Key Biomarkers in Ischemic Stroke

Oxidative stress (OS) is a key factor in ischemic stroke (IS), but the characterization of OS-related genes in IS remains largely unexplored. Identify...

STRAND: Sequence-Conditioned Transport for Single-Cell Perturbations

Predicting how genetic perturbations change cellular state is a core problem for building controllable models of gene regulation. Perturbations target...

Deep Learning-Based Screening for POLE mutations on Histopathology Slides in Endometrial Cancer

POLE sequencing for somatic mutations (POLEmut) guides adjuvant therapy in endometrial cancer (EC), but cost and infrastructural considerations lead t...

EpiExpr: Predicting gene expression using epigenetic data and chromatin interactions

Decoding gene expression from epigenomic landscapes remains a fundamental challenge in genomics. We introduce EpiExpr, a flexible deep learning framew...

A Large-Scale Cryo-EM RNA Motif Dataset and Benchmark for Machine Learning-Based Structure Modeling

Motivation: RNA molecules play critical roles in gene regulation, viral replication, and cellular control, with their functions tightly coupled to thr...

HiCInterpolate: 4D Spatiotemporal Interpolation of Hi-C Data for Genome Architecture Analysis.

Motivation: Studying the three-dimensional (3D) structure of a genome, including chromatin loops and Topologically Associating Domains (TADs), is esse...

seq2ribo: Structure-aware integration of machine learning and simulation to predict ribosome location profiles from RNA sequences

Motivation: Ribosome dynamics are vital in the process of protein expression. Current methods rely on ribosome profiling (Ribo-seq), RNA-seq profiles,...

SpliceRead: Improving Canonical and Non-Canonical Splice Site Prediction with Residual Blocks and Synthetic Data Augmentation

Accurate splice site prediction is fundamental to understanding gene expression and its associated disorders. However, most existing models are biased...

Preserved Embedding of Neural Population Activity for Brain Computer Interfaces

Inferring stable neural representations of motor cortical dynamics is essential for brain-computer interface (BCI) control. However, neural recordings...

Designing AI-programmable therapeutics with the EDEN family of foundation models

The ability to interpret, modify, and design DNA has driven many of the most significant advances in modern medicine, from diagnostics, biologics, and...

A high-fat hypertensive diet induces a coordinated perturbation signature across cell types in thoracic perivascular adipose tissue

Perivascular adipose tissue (PVAT), an intriguing layer of fat surrounding blood vessels, regulates vascular tone and mediates vascular dysfunction th...

Central Dogma Transformer II: An AI Microscope for Understanding Cellular Regulatory Mechanisms

Current biological AI models lack interpretability -- their internal representations do not correspond to biological relationships that researchers ...

Identification of Novel mRNA Biomarkers with Improved Performance for Colorectal Cancer Screening from a Multicenter Large Gene Screen

Abstract Background: Colorectal cancer (CRC) is a leading cause of cancer mortality. While early detection improves outcomes, current non-invasive tes...