Discover, rate, and discuss biology preprints.

DynamicDemiLog (DDL) is a unified sketch that estimates cardinality, similarity, frequency, and composition efficiently, outperforming existing methods in speed and accuracy.

SCALLOPS improves processing of optical pooled screens by enabling efficient alignment and analysis of large-scale image data, demonstrating superior performance over existing methods.

DMcloud improves fitting of molecular models into cryo-EM maps by local structure fitting, achieving higher accuracy and coverage than existing methods.

scIsoAgent improves long-read single-cell RNA-seq analysis by creating reproducible, isoform-resolved workflows and linking sequence data to functional hypotheses.

The paper identifies novel membrane-bound transcriptional regulators by analyzing rare, evolutionarily conserved domain combinations in membrane proteins.

This paper introduces DeepUI, a physics-driven framework that reconstructs isotropic 3D fluorescence images from undersampled axial data, achieving high performance even under challenging conditions.

The paper introduces ITN, a deep learning model that improves subgroup-specific prediction by integrating multiple outcomes and subgroups in biomedical datasets.

The paper presents tools to harmonize viral genomic data across repositories and mask lab-specific artifacts, improving phylogenetic analysis accuracy.

GnnDebugger uses Graph Neural Networks to correct errors in De Bruijn Graphs, improving genome assembly accuracy for diploid genomes with low coverage.

Pillbox predicts cancer drug response using foundation models and evaluates lineage ceiling through residual correlation analysis.

This paper introduces a Transformer-derived transcriptomic score to identify drug-tolerant persister-like states in AML, showing external association with ex-vivo drug response.

The paper benchmarks biomarker identification and prognostic modeling methods on censored survival data, finding that CoxBoost and Adaptive LASSO perform best across multiple metrics.

The paper identifies recombination events in dengue virus genomes using multiple methods and introduces a new tool for improved detection.

This study uses Super Learner ensemble modeling on CPTAC proteomic data to predict survival in HNSCC, finding that the ensemble method performs stably with high C-index values.

LucaVirus predicts viral evolution and function using a unified nucleotide-protein language model, achieving state-of-the-art results in key virology tasks.

The paper introduces FLOWSATATE, a trajectory inference method using time-resolved RNA labeling data to model cell fate dynamics and predict future states.

This study reassesses human mitochondrial DNA methylation using multiple platforms and finds signals likely due to technical artifacts rather than biological methylation.

AliceDB is a database of over 7 million natural protein variants for Homo sapiens, improving proteomic data interpretation by accounting for natural variation.

oxo-flow is a Rust-based workflow engine that compiles to a native binary, offering faster execution and lower memory usage compared to existing tools like Snakemake and Nextflow.

This paper integrates metabolomics data with machine learning techniques to improve cancer detection and biomarker discovery by comparing multiple integration strategies.