Genetics

Integrative Single-Cell Epigenomic Atlas Annotates the Regulatory Genome of the Adult Mouse Brain

Histone modifications underpin the cell-type-specific gene regulatory networks that drive the remarkable cellular heterogeneity of the adult mammalian brain. Here, we profiled four histone modifications jointly with transcriptome in 2.5 million nuclei across multiple adult mouse brain regions. By integrating these data with existing maps of chromatin accessibility, DNA methylation, and 3D genome o...

Accurate somatic variant detection from formalin fixed, paraffin embedded tissue (FFPE) derived WES and WGS by DeepOmicsFFPE-PLUS, a sequence context-based transformer

Formalin-fixed paraffin-embedded (FFPE) tissues represent a vast archival resource for genomic studies, yet their utility remains constrained by fixation-induced DNA damage and subsequent sequencing artifacts. To comprehensively characterize and address this challenge, we analyzed matched FFPE and fresh-frozen tumor samples from two institutions, spanning different storage durations, DNA qualities...

Characterizing yield through wheat's perception of chronological progression: a multi-omics plant-time warping approach

To address challenges in food security, a better understanding of crop performance under varying and changing environmental conditions is required. Pl...

Quantitative RNA pseudouridine landscape reveals dynamic modification patterns and evolutionary conservation across bacterial species

Pseudouridine ({Psi}) modifications are the most abundant RNA modifications; however, their distribution and functional significance in bacteria remai...

An Interpretable Vision Transformer as a Fingerprint-Based Diagnostic Aid for Kabuki and Wiedemann-Steiner Syndromes

Kabuki syndrome (KS) and Wiedemann-Steiner syndrome (WSS) are rare but distinct developmental disorders that share overlapping clinical features, incl...

Accelerating Vision Transformers on Brain Processing Unit

With the advancement of deep learning technologies, specialized neural processing hardware such as Brain Processing Units (BPUs) have emerged as dedic...

Universal Anti-forensics Attack against Image Forgery Detection via Multi-modal Guidance

The rapid advancement of AI-Generated Content (AIGC) technologies poses significant challenges for authenticity assessment. However, existing evaluati...

RAIGen: Rare Attribute Identification in Text-to-Image Generative Models

Text-to-image diffusion models achieve impressive generation quality but inherit and amplify training-data biases, skewing coverage of semantic attrib...

Single-cell machine learning uncovers genetically anchored, cell-type specific programs of Alzheimer's disease

Aging and genetic risk shape the molecular programs that confer cellular vulnerability in Alzheimer's disease (AD), but whether these programs differ ...

Delphi: Deep Learning for Polygenic Risk Prediction

Polygenic scores (PGS) are relative measures of an individual's genetic propensity to a particular trait or disease. Most PGS methods use a regression...

Practical utility of sequence-to-omics models for improving the reproducibility of genetic fine-mapping

Recent advances in deep learning have led to the development of sequence-to-omics (S2O) models that predict molecular phenotypes directly from DNA seq...

Mapping trans-eQTLs at single-cell resolution using Latent Interaction Variational Inference.

Single-cell expression quantitative trait loci (eQTL) studies hold promise for linking genetic variants to changes in gene expression in individual ce...

Unified imputation of missing data modalities and features in multi-omic data via shared representation learning

Multi-omic studies promise a more comprehensive view of biological systems by jointly measuring multiple molecular layers. In practice, however, such ...

Predictive Modeling of COVID-19 Variant Peak Prevalence and Duration Using GISAID Data Across 15 Countries

BackgroundRapid emergence and replacement of SARS-CoV-2 variants underscore the need for early and reliable indicators of variant dominance to guide t...

Inheritance Between Feedforward and Convolutional Networks via Model Projection

Techniques for feedforward networks (FFNs) and convolutional networks (CNNs) are frequently reused across families, but the relationship between the u...

Dataset Distillation via Relative Distribution Matching and Cognitive Heritage

Dataset distillation seeks to synthesize a highly compact dataset that achieves performance comparable to the original dataset on downstream tasks. Fo...

CLIP-Map: Structured Matrix Mapping for Parameter-Efficient CLIP Compression

Contrastive Language-Image Pre-training (CLIP) has achieved widely applications in various computer vision tasks, e.g., text-to-image generation, Imag...

Better Source, Better Flow: Learning Condition-Dependent Source Distribution for Flow Matching

Flow matching has recently emerged as a promising alternative to diffusion-based generative models, particularly for text-to-image generation. Despite...

Deconvolving mutation effects on protein stability and function with disentangled protein language models

Understanding how evolutionary constraints shape protein sequences is fundamental to deciphering the molecular mechanisms underlying protein stability...

Hierarchical Representation Learning for Drug Mechanism-of-Action Prediction from Gene Expression Data

Deciphering drug mechanisms of action (MoAs) from transcriptional responses is key for discovery and repurposing. While recent machine learning approa...