Genetics

Enformer-Based Phylogenetic Tree Reconstruction

Enformer is a deep learning model trained on human and mouse genomes to predict regulatory activity from 196,608 bp DNA windows. Its trunk embeddings capture long-range cis-regulatory interactions, but whether this signal generalises across the tree of life has not been assessed. We embed universal single-copy orthologous groups (OGs) from OrthoDB v12 across three taxonomic scales and evaluate rec...

Single-Cell Multi-Omics Dissection of Malignant Evolutionary Mechanisms and Construction of a Prognostic Model for Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) exhibits pronounced heterogeneity across WHO histological grades, yet systematic single-cell multi-omics studies characterizing these transitions remain limited. We integrated scRNA-seq and scATAC-seq data across ccRCC WHO grades to establish a multi-omics framework encompassing tumor cells and immune populations. Using pseudotime trajectory analysis and mac...

DRIFT: From Robustness Gaps to Invariance Manifolds for AI-Generated Image Detection

The rapid evolution of generative image models challenges existing AI-generated image detectors, particularly in open-world settings with unseen gener...

Robust Multi-Mutant Protein Stability Prediction from a Fine-Tuned Evolutionary Scale Model

Recently, high-throughput experimental techniques have propelled improvements in deep learning-based prediction of mutation effects on protein stabili...

MultiAge: A New Multidimensional Biomarker of Biological Age Derived from Comprehensive Phenotypic and Molecular Profiling

Background: It is an everyday observation that people of the same chronological age differ with respect to their physical and mental capacity. However...

Genosolver: Rare Disease Diagnosis through Holistic Integration of Unstructured Clinical Narratives Using Large Language and Reasoning Models

Background: Molecular medicine has made genetic diagnostics crucial for rare diseases, but the majority of patients remains without diagnosis even aft...

Let It Be Simple: One-Step Action Generation for Vision-Language-Action Models

Diffusion-based vision-language-action (VLA) models often inherit the image-generation view: actions are generated by iterative denoising. We argue th...

$p$-adic Bi-Filtrations for Topological Machine Learning on Genomic Sequences

We introduce pVR, a topological machine learning framework for alignment-free genomic sequence classification that combines $p$-adic numbers with topo...

In-Context Multiple Instance Learning

Multiple Instance Learning (MIL) addresses problems where supervision is available at the level of bags of instances and has been successfully applied...

Vibe Coding Specificity Foundation Models

Molecular recognition - the determination of which agent binds which target - governs adaptive immunity, gene regulation, signal transduction, RNA sil...

R-loop Prediction Reveals Generalization Limits of DNA Foundation Models Beyond Regulatory Genomics

DNA foundation models are increasingly proposed as general-purpose representations for genomic prediction and design, yet their evaluation remains lar...

Learning residue-level context for modeling protein-protein interactions

Protein language models (PLMs) enable prediction of protein properties by learning residue-level features from sequence, yet most PLM-based approaches...

An interpretable machine learning framework for dog breed inference and ancestry decomposition

The over 300 currently recognized breeds of domesticated dogs are the culmination of centuries of intense artificial selection and recurrent populatio...

Simple cumulative weighting of routine surveillance data identifies epidemic wave origins more accurately than a large language model: evidence from eight COVID-19 waves in Japan

Identifying the origin of an emerging epidemic wave within days of onset could enable targeted response before national spread, yet current methods re...

Convergent genome- and gene-level constraints shape repeated environmental adaptation in grasses

Grasses (Poaceae) dominate terrestrial ecosystems and sustain global food security, yet the genomic principles enabling their repeated adaptation to e...

The machine-learning classifier ALLCatchR2 identifies 20 T-ALL subtypes across cohorts and age groups

T-cell acute lymphoblastic leukemia (T-ALL) comprises molecularly diverse subtypes, but robust cross-cohort validations and operational gene-expressio...

MAGI: Mechanistic Consequences of Genetic Variants via Genomic Foundation Models

Clinical variant interpretation requires mechanism-aware evidence to guide diagnosis and clarify the biological consequences of mutations. However, ex...

Knowledge-Driven Neuro-Symbolic Reasoning for Personalized Oncology Treatment Recommendation Based on Multi-Modal Medical Knowledge Graph

Personalized oncology treatment recommendation is a critical clinical task that requires in-tegrating complex, multi-modal patient data with establish...

SNV and indel error modeling of deep targeted cell-free DNA sequencing data for sensitive detection of circulating tumor DNA in colorectal cancer

Circulating tumor DNA (ctDNA) is a promising biomarker for cancer detection, but low tumor burden makes it difficult to distinguish true signal from b...

Hierarchical refinements of cis-regulatory inputs improve scalable gene expression prediction

Deciphering the relationships between cis-regulatory elements (CREs) and target gene expression has long been a challenging problem in molecular biolo...