Discover, rate, and discuss biology preprints.

The paper introduces RAIDS, a tool for inferring genetic ancestry from various molecular data types, including sequencing and RNA-Seq, without requiring cohort data.

The paper quantifies hubness in T cell receptor distance spaces and evaluates local scaling as a correction, showing improvements in retrieval accuracy but no universal solution.

BioMod introduces biological modules as intermediate units for single-cell foundation modeling, achieving state-of-the-art performance in cell-type annotation and drug-response prediction.

This study examines the low adoption of computational gene-panel-selection tools in targeted spatial transcriptomics, finding that most researchers still use manual or vendor panels.

SQUALL integrates histology and spatial transcriptomics to enable virtual spatial gene expression profiling and clinical prediction across cancers and platforms.

PanTEon provides a cross-kingdom framework for reproducible TE classification, benchmarking machine learning methods and highlighting performance variations across TE superfamilies and lineages.

PRICE 2 improves detection of short and overlapping ORFs using group LASSO regularization, outperforming existing tools and enabling discovery of more cryptic MHC-I peptides.

The paper evaluates whether label-free morphology can replace targeted cellular measurements by analyzing paired phase-reporter data across gene knockouts and screens.

VirtualSkin predicts intervention responses in skin cells by integrating transcriptomic data with biological descriptions across multiple datasets.

This study evaluates if language models improve combinatorial molecular search for ionizable lipids compared to classical methods under budget constraints, finding no significant improvement.

ALBIS generates synthetic spatial transcriptomics data across multiple resolutions and dimensions to enable benchmarking of computational methods.

The paper predicts cyanobacterial diazotrophy using protein-family content and prioritizes candidate protein families for experimental validation.

tRNAZAP is a deep learning toolkit for analyzing nanopore tRNA sequencing data, achieving high accuracy in segmentation and classification tasks.

This study shows that surrogate variable analysis (SVA) can lead to overfitting and reduced cross-cohort reproducibility in neuropsychiatric gene expression analyses.

broadSeq benchmarks differential gene expression methods and shows DELocal identifies distinct genes by considering genomic neighbourhood, particularly for highly expressed genes.

scGSCA analyzes single-cell RNA sequencing data to detect differential gene-set co-expression across phenotypes, identifying pathway changes missed by bulk methods.

The paper introduces an adaptive minibatch approach for approximate Bayesian inference, improving speed-precision tradeoffs for large, heterogeneous biological datasets.

phyloDS identifies differentially used orthologous splice junctions across species by improving orthology definition, statistical testing, and sequence-level validation.

STARgrid is an open-source pipeline that processes Visium HD sequencing data to generate count matrices, showing high agreement with Space Ranger while improving efficiency and resolution.

AnnZarro enables interactive exploration of cell-by-cell and gene-by-gene relationships in single-cell data through a browser-based viewer linked to AnnData objects.