Genetics

MemNovo: Look Back at the Spectrum for Balanced De Novo Peptide Sequencing from Mass Spectrometry

De novo peptide sequencing from tandem mass spectrometry is pivotal in proteomics, enabling identification of novel peptides without reference databases. While recent Transformer-based encoder-decoder models have achieved remarkable performance, we uncover a critical pathology in their inference dynamics. Through comprehensive feature scaling experiments, we demonstrate that existing auto-regressi...

Seeing Below the Limit of Detection: A Censored-Poisson Bayesian Latent-Growth Change-Point Detector (the Span Detector) for Serial ctDNA in HR+/HER2- Metastatic Breast Cancer

Circulating-tumour DNA (ctDNA) carries evidence of drug resistance months before imaging shows it, but the earliest evidence lives below the assay's limit of detection (LoD): a nascent subclone is detected only intermittently, producing a flickering sequence of faint detects and non-detects. Commercial liquid biopsies treat each draw as an independent snapshot and a non-detect as nothing. We argue...

Candidate Molecular Subtypes of Cognitive Resilience in Alzheimers Disease: A Multi-Cohort Machine Learning and Neuroimaging Study

Background: Cognitive resilience (CR) in Alzheimers disease (AD) refers to preserved cognitive function despite substantial AD pathology. Diverse biol...

Functional Continuum of GABAergic Synaptic Dynamics Reflects Genetic Identities

The language of the brain is articulated by temporal patterns of neuronal activity, which individual synapses interpret through distinct forms of syna...

Loss Landscape Diagnosis for Gradient-Based Gray-Scott System Inversion: Disentangling the Roles of PINN Components

Gradient-based inversion of reaction-diffusion systems is typically approached via surrogate models or physics-informed neural networks (PINNs), while...

Topological Deep Learning Identifies Polygenic Variant Clusters Across Familial Multimorbid Disorders

Whole-genome sequencing comprehensively captures coding, non-coding and structural variation in families with suspected inherited disorders, yet its c...

The nascent transcriptome delineates the regulatory landscape in human health and disease

Transcriptional regulatory elements (TREs) orchestrate gene expression programs fundamental to cellular identity and transitions across physiological ...

SHERLOC: An interpretable deep learning model for longitudinal circulating tumor DNA data in survival analysis

Longitudinal circulating tumor DNA (ctDNA) measurements offer a noninvasive means to monitor treatment response, but clinical trial data present subst...

OncoTraj: a public benchmark for longitudinal resistance prediction in EGFR-mutant non-small-cell lung cancer on osimertinib

Resistance to first-line osimertinib in EGFR-mutant non-small-cell lung cancer (NSCLC) is the canonical example of predictable clonal evolution under ...

Next-Generation Skin Cancer Detection Using Efficient Fuzzy Fusion of Genomic and Imaging Data

Skin cancer requires early detection for improved survival rates. Most existing methods rely on deep learning based image classification, which is aff...

C1qa⁺ muscularis macrophages maintain enteric synaptic homeostasis to regulate gastrointestinal motility

The enteric nervous system (ENS) is a complex peripheral neural network that coordinates gastrointestinal motility through highly organized synaptic c...

Multi-feature Classification to Improve Colorimetric Loop-Mediated Isothermal Amplification Fidelity

Loop-mediated isothermal amplification (LAMP) is a cost-effective and portable assay technique for performing nucleic acid-based diagnostics in the fi...

Leveraging NeRF-Rendered Images for 3D Gaussian Splatting

Neural radiance field (NeRF) and 3D Gaussian splatting (3DGS) are two mainstream approaches for novel view synthesis. They often show complementary pe...

Late-Layer Fusion is Enough: Dual-Path Vision Token Routing for Multimodal Large Language Models under Visual Saturation

Multimodal large language models (MLLMs) commonly inherit the deep, symmetric Transformer backbone designed for unimodal text modeling, and apply the ...

Integrating gene regulatory priors into Transformer attention with scTransformer for interpretable scRNA-seq analysis

Motivation: Transformer-based models are increasingly applied to large-scale single-cell transcriptomics, showing strong performance through self-supe...

Overestimating zero-shot fitness prediction: Broad benchmarks mask local failures and practical limitations

Deep learning models have emerged as promising tools for navigating mutational landscapes in protein engineering. These models can be used to predict ...

Epigenetic conditioning improves sequence-based modeling of gene regulation across cell types and alleles

Epigenetic state modulates gene regulation in a manner not always predictable from DNA sequence alone, yet current genomic deep learning models do not...

Single-cell gene regulatory network reconstruction and key regulator identification using a dual-channel fusion graph convolutional network

Background and objective: Gene regulatory networks are formed by complex regulatory relationships between transcription factors and their target genes...

CytoGem-XAI:A Hypergraph Neural Network Framework for Genome-Scale Metabolic Modeling and Interpretable Analysis

Genome-scale metabolic models are essential for understanding cellular metabolism, yet existing deep learning approaches remain black boxes, and tradi...

CREP: Cis-Regulatory Element Predictor Based on Fine-Tuned Enformer

A substantial fraction of disease-associated genetic variants reside in non-coding regions of the genome, where they act by perturbing cis-regulatory ...