Discover, rate, and discuss biology preprints.

The paper applies the QTY code with AlphaFold 3 to design water-soluble analogs of four human aquaporins while preserving their structure and function.

CyStainer imputes markers in high-parameter cytometry data without shared markers, outperforming existing methods in panel merging and dataset integration.

The paper uses a hyperbolic topological atlas to analyze Arabidopsis rosette development under different polyamine and nutrient conditions, revealing how these factors influence developmental trajectories.

This study identifies transcriptomic signatures in sPTB placentas, revealing suppressed metabolic and immune pathways, upregulated inflammatory and hypoxic pathways, and circadian dysregulation linked to preterm birth.

The paper predicts pMHC-I binding stability using a protein language model, showing improved performance over existing methods and demonstrating its utility in immunogenicity and antigen-presentation modeling.

eRNAformer maps enhancer-derived RNA loci genome-wide using deep learning, identifying new eRNA loci linked to disease risk and cancer therapy.

The paper evaluates KAN variants and protein embeddings for enzyme classification, showing improved performance with ESM-2 embeddings.

This paper introduces SOCS, a trajectory inference method for time-series spatial transcriptomics that preserves structural coherence of biological units over time, improving accuracy compared to existing approaches.

G-LATO infers spatial gradients using deep Gaussian processes, revealing known and novel spatial organization in liver and glioblastoma data.

This paper investigates how pooling data from different biological populations affects gene co-expression network analysis and finds that it disrupts module structure and is undetectable by common metrics.

The paper shows that pooled correlations in transcriptomic data often reverse sign when analyzed within specific contexts, highlighting the need for context-aware reporting of correlations.

OracleScreen-LILRB4 identifies small molecule binders of LILRB4 using machine learning, achieving high hit rates and validating compounds in patient-derived cells.

The paper reanalyzes a public single-cell RNA sequencing dataset to identify chondrocyte state transitions and ECM remodeling in osteoarthritis, finding collagen network hubs as potential targets.

MBIOME provides an open-source workflow for amplicon-based microbiome analysis, validated across sequencing platforms and showing improved flexibility and taxonomic resolution.

Prot2Prop predicts six protein developability properties using a multitask framework with a frozen ProstT5 encoder and task-specific adapters, achieving strong performance on both classification and regression tasks.

The paper identifies a mutation that improves PET degradation efficiency in enzyme variants through computational design and experimental validation.

This paper introduces a two-stage framework combining 3D UNet and 3D GCN for accurate Couinaud segmentation in tumor-affected livers, achieving a mean Dice score of 0.828 on blind testing.

This paper introduces a computational framework to quantify transcriptomic damage across tissues and conditions, revealing age-associated increases and demonstrating that interventions can alter tDamAge.

This paper evaluates agentic AI systems on three scientific tasks, finding that human-led AI-assisted work outperforms autonomous systems, with one AI matching human performance in property prediction.

This study develops a machine learning framework to predict CRC stage transitions using tissue-derived transcriptomic signatures and evaluates their performance in blood-based datasets.