Discover, rate, and discuss biology preprints.

DESpace2 identifies differential spatial patterns in spatial omics data by comparing gene expression across experimental conditions.

The paper introduces a model explaining the transcriptional gradient in NNSVs through polymerase parameters, enabling genotype-based prediction of transcriptional behavior.

fastQpick generates bootstrap replicates of FASTQ reads for uncertainty quantification in sequencing data.

The paper introduces a multi-omics integration framework that learns patient-specific embeddings from incomplete data using a variational autoencoder with a data-driven prior, achieving better performance on downstream tasks.

Navigo models mouse embryogenesis to predict cell fates and disease by learning developmental trajectories from scRNA-seq data.

This paper introduces a stochastic model of tumor evolution that integrates genetic and environmental factors to simulate clonal dynamics and demonstrates how ecological feedbacks shape cancer progression.

ASMS detects allele-specific methylation without phasing by analyzing methylation data directly, offering a faster approach for studying gene regulation and imprinting.

This paper introduces SIMBA, a transformer-based model that learns interpretable structural similarity from tandem mass spectra to improve small molecule analog discovery.

The paper introduces RECoDe, a relation extraction dataset for diet, disease, and biomarker associations, and benchmarks NLP models on it, achieving high classification performance.

SPIRAL curates RNA-small molecule structures and identifies binding modes and predictors of affinity, aiding RNA-targeted therapeutic design.

The paper evaluates peptide-MHC generalization to unseen alleles and introduces a benchmark and model that improves prediction accuracy for rare HLA alleles.

HoloCell is a generative foundation model that integrates epigenomics, transcriptomics, and proteomics data across single-cell multi-omics modalities, demonstrating superior performance in representation learning and cross-modal generation.

This paper compares output-head designs for predicting diabetes and myocardial infarction complications, finding that symmetric CRF outperformed others in diabetes but no single method dominated in myocardial infarction.

FFixR filters artefactual mutations in FFPE RNA-seq data, improving accuracy for somatic variant calling in cancer.

This study uses computational methods to analyze the binding of three withanolide derivatives to Plasmodium falciparum DNA gyrase, showing their potential as antimalarial drug candidates.

FateLimit quantifies when future cell identities become predictable from current molecular states across multiple developmental systems.

OmniCell integrates single-cell and spatial transcriptomics to model tissue context, revealing how gene programs operate in different anatomical environments.

biomeStat automates genomic epidemiology analysis of 1,000 Dengue virus genomes, revealing immune escape sites and conserved drug targets in under 24 hours.

This paper develops a deep learning framework to predict protein flexibility from static structural data, achieving moderate accuracy and identifying key structural features associated with flexibility.

VCBench evaluates single-cell foundation models across seven dimensions, finding baselines often outperform models, with TranscriptFormer showing unique strengths but tradeoffs.