Genetics

Testing the mutation accumulation hypothesis in aging with AlphaGenome

The mutation accumulation (MA) hypothesis posits that somatic mutations progressively escape selection and degrade tissue function during aging. Direct tests of this idea have been limited by the difficulty of predicting, at scale, the molecular consequences of individual somatic variants. Here I use AlphaGenome, a sequence-to-function deep learning model, to systematically score the predicted tra...

Benchmarking long-context genome language models on biosynthetic gene clusters

Recent advances in language models for natural language processing have spread to the field of genomics, driving the development of genome language models (gLMs) to decipher genomic information. Cutting-edge long-context gLMs are promising approaches for understanding and designing biological complexity, but their evaluation remains underdeveloped. In this study, we introduce BGCs-Bench, a unified...

Bio-BLIP: A Multimodal Architecture for Transferable Reasoning in Genomic Variant Interpretation

Developing scientific hypotheses in biology requires integrating heterogeneous evidence across DNA sequence, gene context, protein function, and prior...

MethylCurate: Tool For Dataset Curation and Epigenetic Aging Clock Evaluation

SummaryDNA methylation datasets from public repositories such as NCBI Gene Expression Omnibus are central to the development and evaluation of epigene...

Mechanistic Dissection of Conformational Transition of Bicyclic Peptide via Molecular Modeling and Deep Learning

Molecular conformations play a critical role in determining molecular properties, such as membrane permeability, binding affinity, and ultimately ther...

A multi-omic, spatial, and whole-slide image dataset of lung neuroendocrine tumours from the lungNENomics cohort

Lung neuroendocrine tumours (lung NETs) are rare neoplasms comprising approximately 2% of lung cancers. Recent studies have identified distinct molecu...

Pathway-Centric Integration of CRISPR Fitness with Molecular Features Draws Cancer State Maps

Cancer cells display heterogeneous pathway activity that shapes therapeutic vulnerability, but mapping it remains challenging. Transcriptomic scores d...

Classic machine learning on top of multiple position weight matrices improves genomic prediction of transcription factor binding sites

Motivation: DNA motifs recognised by transcription factors are typically represented as position weight matrices (PWMs), assuming independent contribu...

Using Deep Learning Models of Gene Regulation to Guide Drug Prioritization

Drug repurposing offers a cost-effective strategy to accelerate therapeutic discovery, but most computational approaches fail to model noncoding genet...

PXN Unlocks the Power of Public Gene Expression Data Through Cross-Technology Integration

The immense value of public gene expression repositories is constrained by the lack of compatibility among datasets generated from diverse experimenta...

SIGNAL: A Scalable, Real-World Model for Rapid Intraoperative Molecular Classification of Gliomas Using Stimulated Raman Histology

Background: Previous machine learning models to intraoperatively predict the molecular status of gliomas using stimulated Raman histology (SRH), such ...

Molecular Methods to Detect Vibrio cholerae and Associated Bacteriophages among Diarrheal Patients in Bangladesh

Molecular diagnostics to detect Vibrio cholerae (Vc) may be negatively impacted by pathogen-specific lytic bacteriophage (phage) predation. To address...

A Blood-Based Transcriptomic Signature for PTSD Classification Using Machine Learning

Post-traumatic stress disorder (PTSD) remains a significant psychiatric burden; despite growing biomarker research, no blood-based molecular diagnosti...

Morphological fingerprints enable machine learning based inference of neuroblastoma cell states without transcriptomics

Inference of cancer cell states is essential for understanding oncogenic mechanisms and predicting clinical outcomes, yet current reliance on transcri...

Genomic Foundation Models Reveal Chromatin-Domain-Scale Transposable Element Impacts on Rice Genome Architecture

Alignment-based detection of transposable element (TE) insertion polymorphisms suffers from reference bias and multi-mapping errors in repetitive geno...

LPDP: Inference-Time Reward Control for Variable-Length DNA Generation with Edit Flows

We study the application of recent Edit Flows for inference-time reward control for DNA sequence generation. Unlike most reward-guided DNA generation ...

Efficient Adjoint Matching for Fine-tuning Diffusion Models

Reward fine-tuning has become a common approach for aligning pretrained diffusion and flow models with human preferences in text-to-image generation. ...

RNA-FM: Flow-Matching Generative Model for Genome-wide RNA-Seq Prediction

Histopathology whole-slide images (WSIs) are routinely acquired in clinical practice and contain rich tissue morphology but lack direct molecular arch...

Improving Diffusion Posterior Samplers with Lagged Temporal Corrections for Image Restoration

Diffusion-based posterior sampling (PS) is a leading framework for imaging inverse problems, combining learned priors with measurement constraints. Ye...

TMRL: Diffusion Timestep-Modulated Pretraining Enables Exploration for Efficient Policy Finetuning

Fine-tuning pre-trained robot policies with reinforcement learning (RL) often inherits the bottlenecks introduced by pre-training with behavioral clon...