Registry Catalogue

The European Galaxy Server is a publicly available, web-based analysis platform that enables researchers to perform complex data analyses without the need for local software installation or advanced programming skills. It provides access to a wide range of bioinformatics tools and workflows in a reproducible, transparent, and user-friendly environment, running on the de.NBI Cloud infrastructure and operated as part of the European Galaxy ecosystem. Key Benefits: Web-based access to bioinformatics tools without local installation. Reproducible analyses through recorded workflows and histories. Free access to substantial computational resources for research use. User-friendly graphical interface suitable for beginners and experts. Integrated data management and sharing capabilities. Features: Large collection of tools covering genomics, transcriptomics, proteomics, metagenomics, and more. Workflow editor for building, reusing, and sharing analysis pipelines. History tracking to ensure transparency and reproducibility. Support for data upload, visualization, and result export. Integration with training materials and community workflows. Applications: Data analysis in genomics, transcriptomics, proteomics, and metagenomics. Teaching and training in bioinformatics and data analysis. Rapid prototyping and testing of analysis workflows. Collaborative research through shared datasets and workflows. Intended Use: The European Galaxy Server is intended for life-science researchers, educators, and students who want to analyze biological data in a reproducible way using a web-based platform, without requiring command-line expertise or local computing infrastructure. While its primary focus within de.NBI is the life sciences, Galaxy is also used in other domains such as the humanities and astrophysics. Help us improve our de.NBI services – take 2 minutes to fill in our survey (https://de.surveymonkey.com/r/denbi-service?sc=rbc&tool=EuropeanGalaxyServer). Thank you!

The FAIRDOMHub is a publicly available repository managed and supported by the FAIRDOM consortium (https://fair-dom.org/). It’s build using the FAIRDOM-SEEK software (http://fairdomseek.org), an open source web platform for storing, sharing and publishing research assets of biology projects. The assets include FAIR (Findable, Accessible, Interoperable and Reusable) Data, Operating procedures and Models. FAIRDOMHub enables researchers to organize, share and publish data, models and protocols, interlink them in the context of the biology investigations that produced them, and to interrogate them via API interfaces. By using the FAIRDOMHub, researchers can achieve more effective exchange with geographically distributed collaborators during projects, ensure results are sustained and preserved and generate reproducible publications that adhere to the FAIR guiding principles of data stewardship. FAIRDOMHub includes special support for the Systems Biology community.

Flexynesis is an end-to-end framework for multi-omics data integration and predictive modeling, combining data preprocessing, feature selection, Bayesian hyperparameter optimization, model training, evaluation, and interpretation within a unified workflow. It supports both deep learning and classical machine learning methods through a standardized interface, enabling classification, regression, survival analysis, multi-task learning, and cross-modality prediction from heterogeneous molecular datasets. Flexynesis is designed with interpretability in mind. By integrating methods such as integrated gradients through Captum, it helps researchers identify informative molecular markers and better understand model predictions beyond black-box classification or regression. Key benefits Deep learning framework for multi-omics data integration Supports multiple neural architectures for different prediction tasks Flexible fusion of heterogeneous omics layers Automated feature selection and hyperparameter optimization Interpretability support for marker discovery using integrated gradients Applicable to classification, regression, survival, and cross-modality prediction tasks Continuously benchmarked on public datasets, especially in oncology Applications Prediction of clinical and preclinical endpoints from multi-omics data Drug response prediction in patients and preclinical models such as cell lines and PDXs Cancer subtype classification Survival and outcome prediction Cross-modality prediction between molecular data layers Discovery of predictive biomarkers and molecular signatures Benchmarking of deep learning approaches for biomedical multi-omics integration Intended use Flexynesis is intended for computational biologists, bioinformaticians, translational researchers, and machine learning researchers working with multi-omics datasets and clinically relevant endpoints. It is particularly suited for users who want to build interpretable deep learning models for biomedical prediction tasks, especially in oncology and preclinical research.

The Freiburg RNA Toolbox provides a comprehensive set of online tools for RNA research, covering various aspects such as sequence-structure alignments, clustering, interaction prediction, identification of homologs, sequence design, and more. Tools Interaction Prediction CopraRNA : A tool for sRNA target prediction that combines whole genome IntaRNA predictions using homologous sRNA sequences from distinct organisms. IntaRNA : A tool for predicting RNA-RNA interactions, including mRNA target sites for non-coding RNAs (ncRNAs) like eukaryotic microRNAs (miRNAs) or bacterial small RNAs (sRNAs). metaMIR : A framework to predict interactions in human between miRNAs and clusters of genes. Seq-Str Alignment LocARNA : A tool for multiple alignments of RNAs based on their sequence and structure similarity, considering the whole ensemble of secondary structures for each RNA. CARNA : A tool for multiple alignment of RNA molecules based on their full ensembles of structures, computing the alignment that fits best to all likely structures simultaneously. MARNA : A tool for multiple sequence-structure alignments considering a single fixed structure for each sequence only. ExpaRNA : A fast, motif-based comparison and alignment tool for RNA molecules. CRISPR CRISPRmap : A tool providing a quick and detailed insight into repeat conservation and diversity of both bacterial and archaeal systems. CRISPRloci : A full suite for CRISPR locus characterization that includes CRISPR array orientation, detection of conserved leaders, cas gene annotation, and subtype classification. Sequence Design AntaRNA : An Ant-Colony Optimization based tool solving the RNA inverse folding problem, designing RNA sequences satisfying a set of constraints. INFORNA : A server for the design of RNA sequences that fold into a given pseudo-knot free RNA secondary structure. SECISDesign : A server for the design of SECIS-elements within the coding sequence of an mRNA with both structure and sequence constraints. Splicing NIPU : A tool allowing to display splicing regulatory motifs and single-stranded regions. SNP & Mutation CopomuS : A tool rating and ranking possible compensatory mutations of IntaRNA predictions. MutaRNA : A tool predicting and visualizing the mutation-induced structure changes of a single-nucleotide polymorphism (SNP) in an RNA sequence. RaSE : An offline tool using the graph vectorization technique to compute a score indicative of the structural stability responsibility of each nucleotide in an RNA sequence. Classification BrainDead : A tool learning a two-class model for short RNA sequences based on accessibility-enhanced k-mer features and applying it for class prediction of unknown RNAs. Gene set extension DiGI : A tool predicting and ranking a list of unknown genes based on their probabilities to be related to a given genetic disease. Additional Resources The Freiburg Bioinformatics Group also provides: MoDPepInt Server : A simple and interactive webserver for predicting the binding partners of three different modular protein domains. CPSP-Tools Server : An exact and efficient approach to identify optimal structures of lattice proteins within the hydrophobic-polar (HP) model. Galaxy Project - Uni Freiburg : A framework for scientists on e.g. NGS data analyses, genome annotation analyses, proteomics, and metabolomics analysis. CMV server : Tools for the visualization of RNA family models, also known as co-variance models (CM) and Hidden Markov Models (HMM).

Fusion (Omics Fusion) is a web-based platform for the integrative analysis, visualization, and exploration of omics data. It supports researchers in analysing single- and multi-level datasets, particularly from transcriptomics, proteomics, and metabolomics experiments. The platform provides tools for data import, management, normalization, transformation, filtering, statistical and cluster analysis, visualization, and pathway mapping. Key benefits Web-based platform for single- and multi-level omics data analysis Supports integration of transcriptomics, proteomics, and metabolomics datasets Provides data preprocessing, filtering, statistical analysis, and clustering Offers interactive visualizations for exploring complex omics data Includes pathway mapping for biological interpretation Applications Analysis and visualization of transcriptomics, proteomics, and metabolomics data Exploration of single-omics and multi-omics datasets Statistical comparison and clustering of experimental data Cross-omics validation of biological patterns Pathway-based interpretation of omics results Intended use Fusion is intended for life science researchers, bioinformaticians, and systems biology researchers working with omics datasets from transcriptomics, proteomics, metabolomics, or combined multi-level experiments. It is particularly suited for users who want to explore, visualize, and interpret omics data in an integrated web-based environment.

Galaxy Docker provides a ready-to-use Docker-based distribution of the Galaxy platform, enabling users to deploy Galaxy quickly and reproducibly on local machines, servers, or cloud environments. It offers a convenient way to start a fully functional Galaxy instance without manual installation of dependencies, making it well suited for testing, training, and portable analysis setups. Key benefits: Fast and reproducible deployment of a Galaxy instance using Docker No complex local installation—dependencies and configuration are packaged into the container Portable setup for local use, servers, and cloud/HPC-adjacent environments Useful for training courses, workshops, demos, and prototyping Open-source and maintained in a public repository Applications: Rapid setup of Galaxy for teaching, workshops, and hands-on tutorials Testing Galaxy configurations, tools, or workflows in an isolated environment Providing a portable Galaxy environment for teams or collaborations Quick prototyping of analysis environments prior to production deployment Intended use: Galaxy Docker is intended for bioinformatics users, trainers, and service operators who want to deploy Galaxy quickly for temporary or reproducible environments. It is particularly suited for users who prefer a containerized approach for setup and maintenance, or who need a reliable Galaxy instance for training and testing scenarios.

The Galaxy Help Forum provides an open, community-driven platform for user support, troubleshooting, and discussion related to the Galaxy platform. Researchers can ask questions about workflows, tools, installations, errors, and best practices, and receive guidance from Galaxy developers, service operators, and experienced community members. The forum serves as a central knowledge hub for resolving technical issues and improving Galaxy-based analyses. Key benefits: Open and transparent support platform for Galaxy-related questions Direct interaction with developers, administrators, and experienced users Publicly searchable knowledge base of previously answered questions Community-driven troubleshooting and best-practice guidance No cost for scientific users Applications: Troubleshooting Galaxy workflows and tool execution errors Guidance on workflow design and optimization Support for Galaxy installation and configuration Advice on tool selection and parameter settings Exchange of best practices for reproducible analysis Intended use: The Galaxy Help Forum is intended for researchers, bioinformaticians, and Galaxy service users who require assistance with Galaxy workflows, installations, or analysis strategies. It is particularly suited for users seeking community-based support and transparent knowledge exchange in an open forum environment.

Galaxy TIaaS (Training Infrastructure as a Service) is provided by the European Galaxy Server (usegalaxy.eu) to support hands-on training events within the Galaxy training community. TIaaS offers dedicated computational infrastructure for workshops and courses, ensuring stable performance and sufficient resources for all participants during practical sessions. Key benefits: Dedicated computing resources for Galaxy training events Stable and predictable performance during hands-on sessions No local installation required for trainers or participants Scalable infrastructure supporting small and large courses Integrated within the European Galaxy ecosystem Applications: Hands-on bioinformatics workshops using Galaxy University courses and training schools Online and hybrid Galaxy training events Community-driven training initiatives within ELIXIR and de.NBI Intended use: Galaxy TIaaS is intended for trainers, educators, and workshop organizers who conduct hands-on Galaxy courses and require reliable computational infrastructure for participants. It is particularly suited for events where consistent performance and centralized resource management are essential for a smooth training experience.

GEAR is a genome analysis web server that provides easy-to-use applications for molecular biologists working with DNA sequence data. It supports routine laboratory workflows such as Sanger trace analysis, PCR primer design, and general sequence analysis through an intuitive web-based interface. GEAR combines accessible web applications with reusable open-source backend tools, including the de.NBI services Tracy, Wally, and Alfred. Key benefits Web-based access to genome and sequence analysis tools Supports routine workflows such as Sanger sequencing and PCR primer design Includes open-source backend tools for reproducible analyses Suitable for both browser-based use and command-line integration Useful for research, teaching, and method development Applications Analysis and visualization of Sanger sequencing traces DNA sequence inspection and quality assessment PCR primer design for experimental workflows Visualization of aligned reads and contigs NGS alignment quality control and feature counting Included tools Tracy – basecalling, alignment, assembly, and deconvolution of Sanger chromatogram trace files Wally – visualization of aligned sequencing reads and contigs Alfred – NGS alignment quality control, RNA/DNA feature counting, and flexible feature annotation Intended use GEAR is intended for molecular biologists, geneticists, sequencing facilities, bioinformaticians, and life science researchers who need accessible tools for common genome and sequence analysis tasks. It is particularly suited for users who prefer a web-based interface while still benefiting from robust, open-source tools that can also be reused in automated or reproducible workflows.

GeoMine is a tool for the automated mining of protein–ligand binding sites. It enables users to define custom queries and search large collections of protein–ligand complexes and binding pockets for specific spatial interaction patterns. GeoMine supports ligand-based radius pockets as well as predicted pockets generated with DoGSite3 and provides matched binding-site superpositions together with geometric statistics. Key benefits Automated search for spatial patterns in protein–ligand binding sites Custom query design for specific interaction geometries Searches large, regularly updated collections of protein structures and pockets Supports ligand-based and DoGSite3-predicted binding pockets Available through a graphical interface and REST service Provides structural superpositions and statistics on distances, angles, and matching points Applications Identification of recurring interaction patterns in protein binding sites Comparison of geometrically similar binding pockets Analysis of conserved ligand-binding arrangements Discovery of structurally related binding sites across different proteins Support for structure-based drug discovery and ligand design Generation of reference sets for binding-site classification and validation Intended use GeoMine is intended for structural biologists, medicinal chemists, computational chemists, and bioinformaticians working with protein–ligand complexes and binding-site geometries. It is particularly suited for users who want to search large structural datasets for custom spatial interaction patterns and compare matched binding sites in detail.

Goslin is a software tool that facilitates the parsing and normalization of lipid nomenclatures. It provides a standardized way to represent lipids in a computationally accessible format. Key Features: Lipid ontology : Goslin uses a comprehensive lipid ontology to cover various lipid classes and subclasses. Nomenclature parsing : The tool can parse different lipid nomenclatures, including shorthand notations and systematic names. Normalization : Goslin normalizes lipid structures to a standardized format for efficient comparison and analysis. Benefits: Standardization : Goslin enables researchers to easily compare and integrate lipidomics data across different studies and platforms. Improved data quality : The tool's normalization capabilities help ensure accurate and consistent lipid structures. Availability: Goslin is available as a software library that can be downloaded from the LIFS Tools website, or used through its web-based application.

Helixer is an ab initio gene prediction tool for identifying protein-coding genes directly from raw eukaryotic DNA sequences. It combines deep learning-based base-wise predictions with a Hidden Markov Model to generate structural gene models without requiring additional experimental evidence such as RNA-seq data or protein alignments. Helixer is available as an online service and as open-source software for local installation. Key benefits Ab initio prediction of protein-coding genes from genomic DNA Combines deep learning with Hidden Markov Model-based postprocessing Does not require RNA-seq data or protein homology evidence Suitable for structural annotation of eukaryotic genomes Available via web interface and GitHub Applications Structural gene annotation of newly sequenced eukaryotic genomes Prediction of primary protein-coding gene models Genome annotation workflows without additional experimental evidence Comparative genomics and functional genomics projects Preparation of gene models for downstream biological interpretation Intended use Helixer is intended for genome annotation researchers, bioinformaticians, eukaryotic genomics researchers, and plant scientists who need to predict protein-coding genes from genomic DNA sequences. It is particularly suited for projects where RNA-seq or protein evidence is unavailable, incomplete, or not intended to be used.