bioRxiv: Bioinformatics Preprints

DModE: An end-to-end framework for Differential Modification and Expression Analysis of Nanopore direct RNA sequencing data

biorxiv.org·

DyMoTree decodes early cell state transitions and drivers from single-cell transcriptomes using a tree-structured neural network

biorxiv.org·

A systematic imputation framework for sparse, multimodal space biology datasets: application to retinal imaging and omics from the RR9 mission

biorxiv.org·

OMIO: A policy-driven Python library for reproducible microscopy image I/O

biorxiv.org·

Tumour evolution as ground truth for cancer whole-genome sequencing

biorxiv.org·

A Deep Hypergraph Learning Model for Predicting Antimicrobial Combination Effects Across Bacterial Targets

biorxiv.org·

Amylo-Pipe: an integrated web server for mechanistic and kinetic prediction of protein and peptide aggregation

biorxiv.org·

PhyloZoo: a unified framework for phylogenetic network analysis in Python

biorxiv.org·

A quantitative coordinate system for developmental dynamics

biorxiv.org·

DeePEn - A Depth sensitive benchmark for Protein Engineering

biorxiv.org·

inquiSTR: a toolkit for accurate and efficient population-scale tandem repeat genotyping and analysis

biorxiv.org·

Hyper3D-lite: count-preserving representation auditing for long-read multi-contact genome data

biorxiv.org·

GeroEngine: Generative single-cell aging trajectories reveal a bidirectionally traversable identity core and direction-specific inflammatory remodeling

biorxiv.org·

SPARK: A Systems-level Computational Framework for Reconstructing Transcriptomic State Organisation in Lung Adenocarcinoma

biorxiv.org·

AGZArank: Investigating epitope-conditioned antibody binder ranking with structure-derived synthetic supervision

biorxiv.org·

GermRL: Alleviating The Germline Bias In Autoregressive Antibody Language Models Through Reinforcement Learning

biorxiv.org·

Integrating Spatially Adjusted Protein Summaries for Survival Prediction in Spatial Proteomics

biorxiv.org·

Machine Learning-Guided Discovery of Bacterial-Selective Membrane-Active Compounds Reveals Mechanistic Bias in Antibiotic Training Datasets

biorxiv.org·

DLDN-Bench: A Benchmark Framework for Deep Learning de Novo Peptide Sequencing in Proteomics

DModE: An end-to-end framework for Differential Modification and Expression Analysis of Nanopore direct RNA sequencing data

DyMoTree decodes early cell state transitions and drivers from single-cell transcriptomes using a tree-structured neural network

A systematic imputation framework for sparse, multimodal space biology datasets: application to retinal imaging and omics from the RR9 mission

OMIO: A policy-driven Python library for reproducible microscopy image I/O

Tumour evolution as ground truth for cancer whole-genome sequencing

A Deep Hypergraph Learning Model for Predicting Antimicrobial Combination Effects Across Bacterial Targets

Amylo-Pipe: an integrated web server for mechanistic and kinetic prediction of protein and peptide aggregation

PhyloZoo: a unified framework for phylogenetic network analysis in Python

A quantitative coordinate system for developmental dynamics

DeePEn - A Depth sensitive benchmark for Protein Engineering

inquiSTR: a toolkit for accurate and efficient population-scale tandem repeat genotyping and analysis

Hyper3D-lite: count-preserving representation auditing for long-read multi-contact genome data

GeroEngine: Generative single-cell aging trajectories reveal a bidirectionally traversable identity core and direction-specific inflammatory remodeling

SPARK: A Systems-level Computational Framework for Reconstructing Transcriptomic State Organisation in Lung Adenocarcinoma

AGZArank: Investigating epitope-conditioned antibody binder ranking with structure-derived synthetic supervision

GermRL: Alleviating The Germline Bias In Autoregressive Antibody Language Models Through Reinforcement Learning

Integrating Spatially Adjusted Protein Summaries for Survival Prediction in Spatial Proteomics

Machine Learning-Guided Discovery of Bacterial-Selective Membrane-Active Compounds Reveals Mechanistic Bias in Antibiotic Training Datasets

EditorForge: An Active-Site-Aware Framework for Inverse-Folding-Based Protein Redesign