Discover, rate, and discuss biology preprints.

RPI-Zero predicts RNA-protein interactions without prior data by using a sequence-only model trained on a large benchmark of CLIP experiments.

The paper evaluates how handling identical dengue genome records affects inferred envelope-protein variation in a Bangladesh DENV-3 dataset, showing that exclusion strategies can lead to loss of variation.

BacLLM improves protein sequence representations for AMR analysis by integrating functional knowledge, enhancing resistance-gene identification and mechanism prediction.

memVar links human membrane protein variants to molecular contexts and disease, revealing enrichment of pathogenic variants in transmembrane regions and interaction sites.

This study benchmarks 12 methods for differential composition analysis in scRNA-seq data, finding LOCOM performs best in controlling false discovery rate and maintaining power.

AlphaEnzyme improves enzyme discovery by predicting catalytic properties and prioritizing sequence changes, achieving higher success rates in catalyst retrieval and fitness enhancement.

OncoSpot benchmarks cancer spatial transcriptomics methods across tumor evolutionary modes by simulating realistic cancer data with known subclonal and copy-number features.

SwiftLD, a faster alternative to vcftools for computing LD, shows European LD proxies poorly tag 43% of GWAS leads in African populations.

PALM, a protein language model, predicts domain, functional site, and variant effects with high accuracy using curated sequence data and outperforms existing models in multiple benchmarks.

The paper provides per-gene evidence tables from public resources for retrospective gene prioritization, including dates and leakage risk grades for four disease areas.

SPECHTacle efficiently identifies and visualizes cell-specific regulatory changes in single-cell experiments using optimal transport and entropy analysis.

The paper improves kinase activity inference by refining kinase-substrate relationships with protein-association evidence, enhancing accuracy and coverage in phosphoproteomic data.

This paper introduces CAISL, a framework for improving survival prediction in lung adenocarcinoma by integrating clinical and molecular data with stability constraints, achieving better performance than clinical and molecular-only models.

MorphoProt predicts spatial protein abundance using RNA expression, multiscale histology, and tissue neighborhoods, outperforming baselines in human and mouse tissues.

This paper introduces HHRM, a hierarchical model for tumor subtype classification, achieving high accuracy in pan-cancer and breast cancer subtyping with interpretable biomarker identification.

TIGRdisco identifies TIGR arrays and Tas proteins from nucleotide sequences, recovering most array units and uncovering unannotated loci across datasets.

Earl Grey ParTEA annotates transposable elements across multiple genomes, revealing shared and private TE families and improving annotation consistency.

FeatureMAP improves interpretation of untargeted metabolomics data by integrating annotation, network refinement, and functional analysis, revealing metabolic patterns in Alzheimer's disease.

PartiDesign is a structure-sequence co-design model that generates molecular structures and sequences for proteins, nucleic acids, and small molecules, achieving high design throughput across benchmarks.

FoldAbS repurposes protein folding models as foundation encoders to improve antibody screening by evaluating specificity, affinity, and developability in a unified framework.