Discover, rate, and discuss biology preprints.

Nailpolish reduces error rates and improves deduplication of UMI-tagged long reads across multiple sequencing technologies and protocols.

The paper introduces CauNagi, a causal machine learning tool, to identify causal drivers of VEXAS syndrome using single-cell transcriptomic data, revealing key regulatory hubs involved in myeloid dysfunction.

This study uses single-cell RNA sequencing to analyze arterial and venous remodeling in a porcine arteriovenous fistula model, revealing arterial venification and vessel-selective gene expression changes.

This study shows that predicted virus-human protein-protein interactions can better predict viral phenotypes like infectivity and virulence than genomic or sequence-based methods.

This paper introduces RF-PepTune, a method that improves cyclic peptide design by preserving binding geometry while optimizing multiple properties, achieving higher success rates in structural and functional criteria.

The paper evaluates how different biological representations affect drug combination prediction across varying cellular contexts and finds that regulons improve performance on some tasks but not all.

The paper designs proteins using reduced amino acid alphabets and shows that 8 amino acids can form stable proteins, while smaller alphabets fail in experimental validation.

ScProteoAgent translates natural-language requests into single-cell proteomics analyses, preserving analytical state and enabling follow-up queries with high benchmark performance.

PRIORITI uses language models to predict target-indication success in drug discovery, achieving high accuracy and robustness across different benchmarks.

This study links TP53 status to morphology and metaplastic programs in CRC organoids, showing P2 promoter usage reflects p53 activity beyond genotype in some cases.

SpatialTRACE extends anatomical annotations from a few structures to tissue-wide maps using graph and image-based models in spatial transcriptomics and microscopy.

The paper identifies KRAS upregulation in senescent CD8+ T cells as linked to premature coronary artery disease through single-cell and bulk transcriptomic analyses.

BFWalk is a network propagation algorithm that avoids bias toward highly connected proteins, outperforming existing methods in identifying phenotype-associated genes across four human diseases.

The paper evaluates the ability of ODE models to infer causal relationships from time-series omics data using a synthetic benchmark based on real biological data.

The paper establishes a framework for designing splicing experiments in deep 3'-biased single-cell RNA sequencing by analyzing depth requirements and benchmarking against bulk RNA sequencing.

The paper uses a protein language model to analyze proteomic data and shows that underrepresented protein families in reference databases are strongly coupled to oceanographic conditions.

The paper screens dsRNA constructs for off-target effects on beneficial fungi and finds many have perfect 21-nt matches, highlighting a regulatory gap.

The paper integrates holo-omic data from porcine hosts and gut microbiomes to predict host-microbiome interactions, identifying both known and novel relationships.

vep-rs is a Rust reimplementation of Ensembl VEP with high concordance and significantly improved throughput for variant annotation.

ProcessNets efficiently analyzes ensembles of biological networks by leveraging their similarities, achieving significant space and time savings in network property computations.