Discover, rate, and discuss biology preprints.

The paper introduces a method to interpolate and extrapolate node counts in colored compacted de Bruijn graphs to compare pangenomes while accounting for genome number variability and rare sequence influence.

Crumblr is a statistical method for analyzing changes in cell type composition across studies, showing increased power over existing methods in simulations and applied to multiple single-cell RNA-seq datasets.

AptViralDB is a manually curated database of 1,768 experimentally validated antiviral aptamers against 40 viruses and 104 targets, offering annotations, predicted structures, and search tools.

The paper compares single-cell and aggregated morphological profiling to identify programmed cell death mechanisms, finding aggregated data performs better in supervised models.

NoroScope uses context-aware machine learning to prioritize amino-acid substitutions in the norovirus capsid protein, achieving high precision in predicting mutation effects with limited data.

miRstring decodes mature miRNA boundaries from precursor context across species and designs artificial miRNAs effectively.

This paper introduces PLABench, a benchmarking framework for protein-ligand binding affinity prediction, revealing that structural input and training scale alone do not ensure cross-target generalization.

This paper introduces Leff, a spectral measure to quantify effective information in multiple sequence alignments, showing evolutionary constraints reduce sequence diversity in RNA and proteins.

The paper addresses volumetric cell segmentation challenges due to limited labelled data by using synthetic 3D objects to generate unlimited training data, achieving accurate segmentations of real biological data.

The paper introduces DYNAM-O, a toolbox for analyzing sleep EEG to identify individualized transient oscillations, finding sex differences in oscillatory activity.

Kmask reduces misclassifications in metagenomics by masking low-complexity regions, improving accuracy in bacterial, archaeal, viral, and fungal classification.

PANDA analyzes targeted bisulfite amplicon sequencing data to assess methylation patterns and heterogeneity at the read level.

RKMR identifies predictive marker panels in spatial omics data using a scalable framework that integrates kernel modeling and spatial dependence.

This study uses spatial transcriptomics and snRNA-seq to identify 25 forebrain regions and characterize dynamic changes in the human fetal cortex and striatum during late first and early second trimesters.

MIRCID improves drug mechanism modeling by integrating inferred hub miRNAs with gene expression and TF activity, showing better performance than TF activity alone.

The paper identifies the chromatoid body as a dynamic RNA sorting center in spermatogenesis, revealing its role in RNA surveillance and transcript regulation through sequence and structural features.

FourC identifies significant and differential contacts in 4C-seq data using a Bayesian model and Gaussian processes to address duplication and model spatial patterns.

The paper introduces REAL-SWIT, a generative framework for ultra-large virtual screening that efficiently explores chemical space by generating molecules with favorable docking scores.

This paper proposes a structurally constrained message-passing framework for brain decoding on small datasets, achieving competitive performance while maintaining interpretability.

The paper evaluates multi-view gene representations under a matched contract, showing condition-dependent fusion operator rankings across different view combinations and tasks.