Discover, rate, and discuss biology preprints.

DUET is a sequence-only ensemble model for RNA-small molecule binding-site prediction that outperforms existing methods on benchmark datasets.

The paper evaluates AI models for predicting pathogenic variants, finding that performance is inflated by genomic heterogeneity in pathogenic variant prevalence.

Fox predicts host-symbiont co-evolution event rates directly from sequence alignments without tree reconstruction, achieving high accuracy and speed compared to existing methods.

This paper introduces MMRL, a framework for learning representations of somatic missense mutations across cancer types, showing improved prognostic discrimination and identification of mutation subtypes.

The paper uses computational methods to model structural and functional impacts of TPR domain deletions and amino acid substitutions in OGT linked to X-Linked Intellectual Disability.

RankMap improves cell type annotation in spatial and single-cell transcriptomics by using rank-based representations and multinomial regression, achieving competitive accuracy and faster runtime.

SiSaNA provides a command line interface for single-sample regulatory network analysis without requiring programming experience.

The paper evaluates 25 electrospun PVP fiber formulations for regenerative endodontics, using machine learning to identify constraints and release risks, finding carrier-limited release and recommending further testing.

The paper evaluates how negative sampling affects synthetic-lethality prediction models, showing that benchmark performance does not reliably predict experimental retrieval success.

Kontext identifies spatial domains and cell-cell communication by integrating ligand-receptor interactions, outperforming existing methods in spatial transcriptomics.

PatHoST reconstructs pathogen spatial distributions from host transcriptomes using weakly supervised learning, showing improved detection in both experimental and human SARS-CoV-2 data.

VoroTIDE segments protein domains using Voronoi contact areas and self-containment scores, achieving strong performance on benchmark datasets.

The paper identifies seven subtypes of ALS motor cortex with distinct molecular programs and shows they are organized by genetic and clinical factors rather than disease duration.

The paper introduces bowside, a neural model for trajectory inference and gene regulatory network reconstruction in single-cell RNA sequencing data, showing it recovers known regulatory motifs in hematopoiesis and reprogramming.

smoothclust provides a framework for spatial domain analysis in spatial transcriptomics, including a clustering workflow and a boundary density metric to summarize tissue architecture.

mock-fastq-generator creates synthetic FASTQ files for testing bioinformatics pipelines without using biological data.

The paper identifies environmental factors and growth stages affecting fibre yield and quality in rain-grown cotton using statistical models and field data.

The paper identifies converging molecular pathways in genetic epilepsies through network analysis of epilepsy-associated genes and highlights potential therapeutic targets.

This study identifies age-associated k-mer signals in canine buccal and cell-free DNA using alignment-free k-mer analysis and ridge regression models.

The paper introduces PANIMaSTA, a method to construct minimally fragmented metagenomic pangenome graphs for highly diverse viral genomes, improving graph topology for comparative analysis.