Registry Catalogue

LipidCompass – Interactive Exploration and Comparison of Quantitative Lipidomes LipidCompass is a web-based database and analysis platform for the interactive exploration, comparison, and visualization of quantitative lipidomics datasets. It helps researchers navigate the lipid structural space and investigate lipid abundance patterns across samples, tissues, organisms, and studies. As part of the LIFS (Lipidomics Informatics for Life Science) ecosystem, LipidCompass serves as a FAIR resource for storing, exploring, and comparing lipidomics data using standardized nomenclature and metadata. Key benefits Interactive exploration of quantitative lipidomics datasets Comparison of lipidomes within and across studies FAIR data resource with standardized lipid annotations and metadata Integration with established lipid databases and controlled vocabularies Interactive visualization of lipid abundances and structural relationships Supports lipidomics data submitted in standardized formats such as mzTab-M Part of the broader LIFS lipidomics software ecosystem Applications Exploration and comparison of quantitative lipidomes Identification of similarities and differences between biological samples Cross-study comparison of lipidomics datasets Investigation of tissue-, organism-, and condition-specific lipid profiles Integration of lipidomics data into systems biology workflows Interactive visualization and interpretation of lipidomics experiments Intended use LipidCompass is intended for lipidomics researchers, mass spectrometry users, bioinformaticians, and systems biologists who need a centralized platform for exploring and comparing quantitative lipidomics data. It is particularly suited for users seeking FAIR-compliant data management, interactive visualization, and large-scale comparison of lipidomes across experiments and studies.

Lipidome Projector: Web-Based Application for Quantitative and Qualitative Lipidome Comparison Lipidome Projector is a web-based application designed to facilitate the comparison of lipidomes across different samples, conditions, or species. The tool enables researchers to visualize and analyze quantitative and qualitative differences in lipid profiles, providing insights into changes in lipid metabolism, regulation, and function. Key Features: Structure-based lipidome embeddings: Lipidome Projector uses a novel approach to embed lipid structures into a lower-dimensional space, allowing for the visualization of complex lipidomes. Quantitative and qualitative comparison: The tool enables researchers to compare lipid profiles both quantitatively (e.g., changes in lipid abundance) and qualitatively (e.g., changes in lipid structure). Interactive visualization: Lipidome Projector provides an interactive interface for exploring and visualizing lipidomes, allowing users to zoom in/out, rotate, and select specific lipids or groups of lipids. Benefits: Improved understanding of lipid metabolism: By comparing lipid profiles across different samples or conditions, researchers can gain insights into changes in lipid metabolism and regulation. Identification of biomarkers: Lipidome Projector can help identify potential biomarkers for diseases or disorders by highlighting changes in lipid profiles associated with specific conditions. Streamlined data analysis: The tool simplifies the process of comparing lipidomes, reducing the need for manual processing and allowing researchers to focus on interpreting results. Technical Details: Input data: Lipidome Projector accepts tables of lipid abundances and lipidome sample features in simple CSV formats. Output data: The tool generates interactive visualizations of lipidomes, which can be exported as images or used for further analysis. Collaboration: Lipidome Projector allows users to share their projects with colleagues or collaborators, facilitating collaborative research. Availability: Lipidome Projector is available as a web-based application on the LIFS Tools website. Users can access the tool by creating an account on the website.

LipidXplorer is a software tool designed for shotgun lipidomics, enabling researchers to identify and quantify lipids in complex biological samples. The software uses an language-driven approach for lipid identification expressed in MFQL (Mass Spectrometry Formula Query Language). Key Features: Shotgun lipidomics : LipidXplorer is specifically designed for shotgun lipidomics, allowing researchers to analyze complex lipid mixtures without the need for prior separation or fractionation. MFQL-based lipid identification : The software uses a language-driven approach for lipid identification, expressed in MFQL. This enables users to define specific queries for identifying lipids based on their molecular formulas and fragmentation patterns. High-performance analysis : LipidXplorer is designed for high-performance analysis, allowing researchers to process large datasets quickly and efficiently. Benefits: Improved accuracy and specificity : By using a language-driven approach for lipid identification, LipidXplorer enables researchers to improve the accuracy and specificity of their results. Increased sensitivity : The software's ability to analyze complex lipid mixtures without prior separation or fractionation enables researchers to detect lipids that may not be detectable by other methods. Streamlined workflow : LipidXplorer is designed to integrate with existing workflows, enabling researchers to quickly and easily incorporate shotgun lipidomics into their research. Technical Details: Input data : LipidXplorer accepts mass spectrometry data in various formats, including mzML and mzXML. Output data : The software generates output files that contain information on identified lipids, including molecular formulas, fragmentation patterns, and intensities. Operating system : LipidXplorer is available for Windows, macOS, and Linux operating systems. Availability: LipidXplorer is available as a free download from the LIFS Tools website. Users can access the software by creating an account on the website.

lxPostman is a web-based application designed to facilitate the post-processing of output files generated by LipidXplorer, a software tool for shotgun lipidomics. The application provides a user-friendly interface for quality control, quantitation, and merging of results from multiple runs or samples. Key Features: Quality control : lxPostman allows users to evaluate the quality of their data by assessing metrics such as signal-to-noise ratio, peak intensity, and retention time. Quantitation : The application enables users to quantify lipids based on peak areas, heights, or intensities, and to normalize results using various methods (e.g., TIC normalization). Merging results : lxPostman allows users to combine results from multiple runs or samples, creating a single output file that contains all the data. Interactive visualization : The application provides an interactive interface for visualizing lipid profiles, allowing users to explore and compare results in detail. Benefits: Improved data quality : By providing tools for quality control and quantitation, lxPostman helps ensure that lipidomics data is accurate and reliable. Increased efficiency : The application streamlines the process of post-processing LipidXplorer output files, saving time and reducing manual effort. Enhanced collaboration : lxPostman allows users to share their results with colleagues or collaborators, facilitating collaborative research. Technical Details: Input data : lxPostman accepts output files generated by LipidXplorer in various formats (e.g., CSV, Excel). Output data : The application generates output files that contain quality-controlled and quantified lipidomics data, which can be used for further analysis or exported to other software tools. Integration with LipidXplorer : lxPostman is designed to work seamlessly with LipidXplorer, allowing users to easily transfer results between the two applications. Availability: lxPostman is available as a web-based application on the LIFS Tools website. Users can access the tool by creating an account on the website.

MacPepDB is a database that enables fast and comprehensive access to all theoretically generated tryptic peptides derived from the UniProtKB. It allows users to query peptide sequences across organisms and proteomes, facilitating proteomics research that relies on in silico digestion and peptide-centric analyses. Key benefits Fast retrieval of tryptic peptides derived from UniProtKB proteins Organism- and proteome-wide peptide search capabilities Supports peptide-centric workflows in proteomics research Facilitates theoretical digestion-based analyses Web-accessible database for immediate querying Applications In silico tryptic digestion of UniProtKB protein entries Peptide lookup across species and proteomes Support for mass spectrometry-based proteomics workflows Assessment of peptide uniqueness and proteome coverage Database support for method development and benchmarking Intended use MacPepDB is intended for researchers in proteomics, bioinformatics, and computational biology who require rapid access to theoretical tryptic peptides for database searches, method development, or peptide-centric analyses. It is particularly suited for users working with mass spectrometry data and proteome-wide peptide investigations.

The MdOA toolbox is a collection of browser-based applications that support end-to-end analysis and interpretation of omics datasets – from mass-spectrometry metaproteomics to feature selection for biomarker panels and interpretable clinical risk modeling. All tools run in the browser (supported by de.NBI Cloud); no local installation is required. Key Features Web-first access: Use the tools directly in your browser; no setup on local machines. Purpose-built apps: Each app tackles a concrete task (MS/MS metaproteomics analysis, molecule/feature panel selection, interpretable sepsis risk prediction). Transparent & interpretable outputs: Interactive visuals (PCA/cluster plots, model metrics, SHAP explanations) to aid result interpretation. Hosted on German research infrastructure with clear ownership/contact Tools MPA Cloud – MetaProteomeAnalyzer Cloud – Web version of the MetaProteomeAnalyzer for metaproteomics/proteomics MS/MS data processing and visualization. Ideal for taxonomic/functional insights from complex communities. (Funded by de.NBI) Prophane - Provides a tailored and fully automated workflow for metaproteomics analysis with special focus on metaprotein taxonomic and functional annotation. For the annotations you can choose between different databases and algorithm. (Funded by DFG) OMEx – Omics Molecule Extractor – Open-source web app for selecting molecules and multi-marker panels from large omics tables using a stepwise, ML-based feature-selection workflow; includes interactive plots and performance metrics. (Funded by Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V.) SBC-SHAP – A lightweight clinical utility app for real-time sepsis risk prediction using only age, sex, and complete blood count (CBC); provides SHAP-based explanations. (Funded by OVGU Magdeburg) Applications Metaproteomics & proteomics: Process and explore high-resolution MS/MS datasets; derive community composition and functional signals (MPA Cloud). Biomarker discovery & panel building: Identify reproducible multi-marker panels for classification tasks in omics studies (OMEx). Interpretable clinical modeling (research use): Rapid, explainable risk scoring from routine lab values to support methodological exploration and education (SBC-SHAP). Target Audience Researchers in microbiome/metaproteomics and translational omics needing browser-based analysis/selection tools. Method developers & educators demonstrating interpretable ML on clinical-style lab data (with clear non-diagnostic disclaimers). Training & workshops within the de.NBI ecosystem (e.g., metaproteomics courses highlighting MPA Cloud). The Applied Metaproteomics Workshop takes places yearly in Magdeburg, for further information take a look at our training course calendar.

The Metagenomics Toolkit (MGtk) is a scalable, data-agnostic workflow for the automated analysis of metagenomic datasets derived from both short (Illumina) and long (Oxford Nanopore Technologies) reads. Designed for versatility, reproducibility, and minimal hardware requirements, MGtk streamlines the complete metagenomic analysis pipeline – from raw reads to annotated, interpretable genomes. Key Benefits End-to-end automation: Covers all core steps of metagenome processing, from quality control to annotation. Cross-platform support: Compatible with Illumina and Oxford Nanopore datasets. Resource-efficient assembly: Integrates a machine-learning–optimized assembler that adjusts RAM requests dynamically to match actual needs, reducing dependence on high-memory servers. Comprehensive feature set: Beyond classical analysis, MGtk identifies plasmids, recovers unassembled taxa, and models microbial interdependencies. Modular and reproducible: Fully containerized for scalable use on local systems, HPC clusters, or the cloud. Tools & Modules Quality Control & Preprocessing – Adapter trimming, quality filtering, and contamination screening. Assembly & Binning – Optimized short- and long-read assemblers with automatic parameter tuning. Annotation – Taxonomic and functional genome annotation with standardized outputs. Plasmid Identification – Integrates multiple tools for reliable plasmid detection and classification. Community Reconstruction – Recovery of unassembled members and dereplication for non-redundant genome sets. Microbial Interaction Modeling – Combines co-occurrence analysis with genome-scale metabolic models to explore ecological dependencies. Applications Reconstruction of microbial community structure and function from complex metagenomes. Discovery of novel plasmids, symbionts, and microbial interactions in environmental or host-associated samples. Benchmarking and teaching of scalable metagenomics workflows. Predictive modeling of community metabolism and interspecies relationships. Intended Use The Metagenomics Toolkit is ideal for microbiome researchers, bioinformaticians, and systems biologists seeking a reproducible, resource-efficient workflow for analyzing metagenomic datasets from any sequencing platform. If you used this service, please provide feedback in our short survey.

MPA Cloud provides web-based access to the MetaProteomeAnalyzer (MPA), an open-source platform for metaproteomics data analysis and interpretation. It enables researchers to identify taxonomic and functional relationships between proteins from tandem mass spectrometry experiments and supports comprehensive analysis of microbial community composition and function. Key benefits Web-based and user-friendly metaproteomics analysis platform Supports multiple protein database search engines Identification of taxonomic and functional protein relationships Metaprotein grouping to reduce redundancy and improve interpretation Integration of metadata from UniProt, KEGG, and NCBI Taxonomy Tools for sample comparison, visualization, and data export Applications Analysis of tandem mass spectrometry metaproteomics datasets Taxonomic and functional profiling of microbial communities Protein identification and quantification workflows Comparison of multiple biological samples Generation of publication-ready exports and visualizations BLAST-supported downstream analysis and validation Intended use MPA Cloud is intended for researchers in microbiome research, proteomics, and systems biology who require accessible and reproducible metaproteomics analysis workflows. It is particularly suited for users who want to analyze mass spectrometry data without installing and maintaining local analysis infrastructure. Resources Intro Videos : Intro videos are available here (http://www.mpa.ovgu.de/index.php/tutorials/video-tutorials/) to provide guidance on using the MetaProteomeAnalyzer software.

This consulting service supports researchers in planning and executing metaproteomics projects, covering the entire workflow from experimental design to bioinformatic analysis and interpretation. Support includes both wet-lab planning (e.g. sample handling, study design, metadata collection, common pitfalls) and computational analysis (e.g. database strategy, peptide/protein identification and quantification, quality control, statistics, and reporting). Consulting and analysis services are offered free of charge for scientific users. Key benefits End-to-end support for metaproteomics projects Integration of experimental design and computational strategy Expert guidance on database construction and search strategies Quality control, troubleshooting, and reproducible analysis workflows Support for statistical analysis, visualization, and interpretation Free-of-charge consulting for scientific users Applications Study design and metadata planning for metaproteomics experiments Selection and optimization of protein databases and search parameters Peptide and protein identification and quantification workflows Quality assessment and troubleshooting of LC-MS/MS data Statistical analysis and data visualization Support in preparing figures and methods text for publications Intended use This service is intended for researchers in microbiome research, proteomics, and systems biology who plan or conduct metaproteomics studies and require expert guidance throughout the workflow. It is particularly suited for scientific users who seek structured support in both experimental planning and bioinformatic data analysis.

MicroMiner is a tool for identifying and analyzing single-residue substitutions in protein structures. Based on the SIENA methodology, it searches for residue environments with local sequence and structural similarity across the Protein Data Bank (PDB), user-provided structure collections, or selected subsets of the AlphaFold Protein Structure Database. This enables researchers to explore mutation landscapes in both experimentally determined and predicted protein structures. Key benefits Identifies structurally similar residue environments for single-residue substitutions Combines local sequence and structural similarity Searches the PDB, private structure collections, and AlphaFold Database subsets Supports both experimental and predicted protein structures Applicable to individual domains as well as protein–protein and protein–ligand interfaces Provides filtering options to facilitate downstream interpretation Applications Structural interpretation of amino acid substitutions Exploration of protein mutation landscapes Comparison of local residue environments across related structures Analysis of substitutions in protein domains and binding interfaces Investigation of mutations in experimental and AlphaFold-predicted structures Prioritization of structurally relevant mutation examples for downstream studies Intended use MicroMiner is intended for structural biologists, protein scientists, bioinformaticians, and researchers studying protein variants or mutations. It is particularly suited for users who want to investigate how single-residue substitutions relate to known structural environments, including mutations located in protein–protein or protein–ligand interfaces.

MYB Annotator is a web-based tool for the automated identification and functional annotation of MYB transcription factors from coding DNA (CDS) or protein sequence collections. The tool enables rapid characterization of MYB gene families in newly sequenced plant species by combining homology-based candidate identification with motif analysis and orthology-based functional prediction. It requires no manual preparation of reference datasets, as curated MYB sequences are provided as built-in search baits. Key benefits Automated identification of MYB transcription factors from CDS or protein sequences Functional annotation based on orthology to experimentally characterized MYB proteins Detection of conserved MYB repeats and additional diagnostic sequence motifs No manual preparation of reference sequences required Fast and reproducible annotation workflow suitable for newly sequenced plant genomes Generates both annotated FASTA files and comprehensive summary tables Applications Identification of MYB gene family members in plant genomes and transcriptomes Functional annotation of MYB transcription factors Comparative genomics of MYB gene families across plant species Evolutionary analysis of plant transcription factors Candidate gene identification for functional genomics and breeding studies Annotation of newly assembled genome and transcriptome datasets Intended use The MYB Annotator is intended for plant biologists, genome annotation specialists, bioinformaticians, and evolutionary researchers working with plant genome or transcriptome data. It is particularly suited for users seeking an automated and standardized workflow to identify, classify, and functionally annotate MYB transcription factors in newly sequenced plant species.

A Comprehensive Toolbox for Mass Spectrometry Data Analysis OpenMS is a powerful framework that provides an open-source software library and python bindings, as well as an infrastructure for rapid development of mass spectrometry-related software. The toolbox offers a rich set of tools that can be flexibly combined into powerful analysis workflows, supporting several workflow systems including KNIME, Galaxy, and Nextflow. OpenMS Tools: TOPP: The OpenMS Proteomics Pipeline provides a range of tools for protein identification, quantification, and characterization. TOPPView: TOPPView enables the visualization of MS data, allowing users to explore and understand their results in an intuitive way. MetaProSIP: MetaProSIP is a tool for automated inference of elemental fluxes in microbial communities, enabling researchers to study metaproteomics data. DIAMetAlyzer: DIAMetAlyzer generates targeted assays for metabolomics, streamlining the analysis of small molecules. DIAproteomics: DIAproteomics is a workflow for Data-Independent Acquisition (DIA) MS and statistical post-analysis, enabling researchers to analyze complex proteomic data sets. Nucleic Acid Analysis: NASE is a nucleic acid search engine that supports RNA and DNA mass spectrometry analysis. Protein-Protein Interactions: OpenPepXL enables the study of protein-protein interactions, providing insights into biological processes. Benefits: Flexibility: OpenMS provides a modular framework that allows users to combine tools in various ways to create customized workflows. Reproducibility: The toolbox enables reproducible computational analysis, ensuring that results are consistent and reliable. Comprehensive Analysis: OpenMS offers a wide range of tools for different types of mass spectrometry data analysis, making it a one-stop solution for researchers. FLASH Suite for Top Down Proteomics: Top-Down MS Data Analysis: FLASHDeconv, FLASHIda, and FLASHQuant provide tools for top-down MS data deconvolution, intelligent data acquisition, and quantification. See details here. Selected Workflows: HLA Ligand Atlas: A comprehensive collection of tissue and HLA allele-specific HLA ligands that are naturally presented. MHCquant: A workflow for identification and quantification of HLA ligands. quantMS: A workflow for quantitative mass spectrometry analysis. By using OpenMS, researchers can streamline their mass spectrometry data analysis, gain deeper insights into biological processes, and accelerate discovery in various fields. If you have used this service, please help us improve by taking our short survey (https://de.surveymonkey.com/r/denbi-service?sc=cibi&tool=openms).