Björn Andreas Grüning

Microbiology Galaxy Lab: The first community-driven gateway for reproducible and FAIR analysis of microbial data

The paper introduces the Microbiology Galaxy Lab, a community-driven platform for reproducible and FAIR microbial data analysis, offering tools for various omics data types and use cases.

Verifiable Agentic Science on Public Infrastructure

This paper demonstrates agentic science on public infrastructure to ensure reproducibility by making all agent actions and workflows publicly accessible.

SIMORGH: Ensemble-Aware Geometric Deep Learning for Apo-State and Cryptic Ligand Binding Site Prediction

SIMORGH predicts ligand binding sites from apo proteins by integrating conformational ensembles, outperforming existing methods in ligand-free settings and identifying cryptic pockets.

Machine learning-based prediction of memory requirements for metagenomic assembly in high-performance computing environments

This study develops a machine learning framework to predict memory requirements for metagenomic assembly, improving efficiency in high-performance computing environments.

Prioritizing DNA methylation biomarkers using graph neural networks and explainable AI

The paper introduces GraphMeX-plain, a graph neural network with explainable AI to prioritize disease-specific CpG sites as potential biomarkers in breast cancer and acute myeloid leukemia.

Standardizing RNA-seq Analysis of Fungal Pathogens Using BRC-Analytics and Agentic AI: A Candidozyma auris Case Study

The paper demonstrates a framework using BRC-Analytics and agentic AI to standardize RNA-seq analysis of fungal pathogens, achieving reproducible results across studies with differing annotations.

From data to publication in a browser with BRC-Analytics: Evolutionary dynamics of coding overlaps in measles virus

The paper introduces BRC-Analytics, a browser-based platform for pathogen genomics, demonstrating its use in analyzing measles virus evolutionary dynamics and revealing asymmetric frame evolution under selective pressures.

PathoGFAIR: a collection of FAIR and adaptable (meta)genomics workflows for (foodborne) pathogens detection and tracking

PathoGFAIR provides FAIR and adaptable metagenomics workflows for detecting and tracking pathogens from Nanopore sequencing data, achieving species-level detection in most tested samples.

The European Reference Genome Atlas: piloting a decentralised approach to equitable biodiversity genomics

The paper describes the European Reference Genome Atlas (ERGA) pilot project, which tests a decentralized model for producing high-quality reference genomes across 98 European species.

varVAMP: automated pan-specific primer design for tiled full genome sequencing and qPCR of highly diverse viral pathogens.

varVAMP designs pan-specific primers for tiled sequencing and qPCR of diverse viruses, ensuring specificity through minimal variability regions and degenerate nucleotides.

Mobilisation and analyses of publicly available SARS-CoV-2 data for pandemic responses

The paper describes open data sharing, analysis tools, and lessons learned from the European COVID-19 Data Platform's SARS-CoV-2 data collection and analysis efforts.

Scalable, accessible, and reproducible reference genome assembly and evaluation in Galaxy

The paper presents a scalable pipeline for reference genome assembly and evaluation, demonstrating its effectiveness across 51 vertebrate species using Galaxy.

Transformer-based tool recommendation system in Galaxy

This paper develops a Transformer-based tool recommender system for Galaxy, achieving faster convergence and better generalization than a previous RNN-based system.

Activator-blocker model of transcriptional regulation by pioneer-like factors

The paper investigates how Pou5f3 and Nanog regulate enhancer types during zygotic genome activation through an activator-blocker mechanism.

Planemo: a command-line toolkit for developing, deploying, and executing scientific data analyses

Planemo is a command-line toolkit for developing, deploying, and executing Galaxy tools and workflows, promoting best practices in scientific data analysis.

Galaxy Training: A Powerful Framework for Teaching!

The paper introduces Galaxy Training Network (GTN) as a framework for creating and sharing FAIR training materials for data analysis, with recent improvements to support educators and expand its use in various learning environments.

An accessible infrastructure for artificial intelligence using a docker-based Jupyterlab in Galaxy

The paper presents a docker-based Jupyterlab infrastructure in Galaxy for AI development, enabling remote training and management of AI projects with GPU support and version control.

Training Infrastructure as a Service

TIaaS provides scalable infrastructure for efficient bioinformatics training, enabling remote and in-person classes with minimal delays and administrative overhead.

A Web-based Software Resource for Interactive Analysis of Multiplex Tissue Imaging Datasets

Galaxy-ME is a web-based software hub for analyzing and visualizing multiplex tissue imaging datasets, demonstrating its utility on normal and cancerous tissue data.

Pou5f3 and Sox19b determine gene expression repertoire at Zygotic Genome Activation

The paper shows Pou5f3 and Sox19b independently regulate enhancer chromatin accessibility, affecting zygotic gene expression in zebrafish embryos.

Loop detection using Hi-C data with HiCExplorer

The paper introduces a chromatin loop detection algorithm using Hi-C data with strict candidate selection and statistical testing.

Expanding the Galaxy's reference data

The paper describes integrating refgenie into Galaxy to manage and share reference datasets, with tools for retrieval and a global repository for easy access.

Democratizing Data-Independent Acquisition Proteomics Analysis on Public Cloud Infrastructures Via The Galaxy Framework

The paper provides a Galaxy-based pipeline for DIA proteomics analysis, enabling reproducible and accessible processing through a web interface.

A proteomics sample metadata representation for multiomics integration, and big data analysis.

The paper introduces a standardized metadata format for proteomics datasets to improve reusability and integration across public repositories.

Accessible, Reproducible, and Scalable Machine Learning for Biomedicine

The paper introduces Galaxy-ML, a web-based platform for reproducible and scalable supervised machine learning in biomedicine, extending the Galaxy computational workbench.

User-friendly, scalable tools and workflows for single-cell analysis

The paper introduces an interactive scRNA-Seq analysis environment based on Galaxy, integrating ~70 functions for scalable and accessible single-cell data analysis.

Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring

The paper presents a global, community-maintained platform for analyzing SARS-CoV-2 genomic data, demonstrating its utility in variant detection and reanalysis of existing datasets.

BioContainers Registry: searching for bioinformatics tools, packages and containers

The paper introduces the BioContainers Registry and API to improve the findability, accessibility, interoperability, and reusability of bioinformatics tools and containers.

Tool recommender system in Galaxy using deep learning

The paper develops a deep learning model to recommend Galaxy tools based on workflow analysis, achieving 97% accuracy in tool prediction.

Adding software to package management systems can increase their citation by 280%

This study shows that publishing software in package management systems increases its cited scholarly papers by 280%.