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"Windows", "Mac" ], "language": [], "license": "GPL-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/ElucidataInc/ElMaven", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/ElucidataInc/ElMaven/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://elucidatainc.github.io/ElMaven/Downloads/", "type": "Binaries", "note": null, "version": null }, { "url": "https://github.com/ElucidataInc/ElMaven/releases", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://elucidatainc.github.io/ElMaven/documentation/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1007/978-1-4939-9236-2_19", "pmid": "31119671", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "EL-MAVEN: A fast, robust, and user-friendly mass spectrometry data processing engine for metabolomics", "abstract": "", "date": "2019-01-01T00:00:00Z", "citationCount": 106, "authors": [], "journal": "Methods in Molecular Biology" } } ], "credit": [ { "name": null, "email": "info@elucidata.io", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Support" ], "note": null }, { "name": null, "email": "elmaven@elucidata.io", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "hans", "additionDate": "2019-08-09T13:14:25Z", "lastUpdate": "2025-11-03T16:47:19.388844Z", "editPermission": { "type": "group", "authors": [ "recetox-specdatri" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "TiSim", "description": "TiSim-CellSys is a modular software tool for efficient off-lattice simulation of growth and organization processes in multicellular systems in two and three dimensions. It implements an agent-based model that approximates cells as isotropic, elastic and adhesive objects. Cell migration is modeled by an equation of motion for each cell. The software includes many modules specifically tailored to support the simulation and analysis of virtual tissues including real-time 3D visualization and VRML 2.0 support. All cell and environment parameters can be independently varied which facilitates species specific simulations and allows for detailed analyses of growth dynamics and links between cellular and multicellular phenotypes.", "homepage": "https://www.hoehme.com/software/tisim", "biotoolsID": "cellsys", "biotoolsCURIE": "biotools:cellsys", "version": [ "5.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0244", "term": "Simulation analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3869", "term": "Simulation" }, "format": [] } ], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_2229", "term": "Cell biology" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [ "PerMedCoE" ], "maturity": null, "cost": null, "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://www.hoehme.com/software/tisim", "type": "Binaries", "note": null, "version": "5.0" } ], "documentation": [ { "url": "https://www.hoehme.com/images/Software/cellsys_user_guide.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btq437", "pmid": "20709692", "pmcid": "PMC2951083", "type": [], "version": null, "note": null, "metadata": { "title": "A cell-based simulation software for multi-cellular systems", "abstract": "CellSys is a modular software tool for efficient off-lattice simulation of growth and organization processes in multi-cellular systems in 2D and 3D. It implements an agent-based model that approximates cells as isotropic, elastic and adhesive objects. Cell migration is modeled by an equation of motion for each cell. The software includes many modules specifically tailored to support the simulation and analysis of virtual tissues including real-time 3D visualization and VRML 2.0 support. All cell and environment parameters can be independently varied which facilitates species specific simulations and allows for detailed analyses of growth dynamics and links between cellular and multi-cellular phenotypes. © The Author(s) 2010. Published by Oxford University Press.", "date": "2010-08-13T00:00:00Z", "citationCount": 139, "authors": [ { "name": "Hoehme S." }, { "name": "Drasdo D." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "tntiniak", "additionDate": "2022-04-22T14:17:27.559879Z", "lastUpdate": "2025-07-16T09:46:10.555167Z", "editPermission": { "type": "public", "authors": [ "ArnauMontagud" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "SQANTI3", "description": "SQANTI3 constitutes the first module of the Functional IsoTranscriptomics (FIT) pipeline, which is an end-to-end strategy to perform isoform-level bioinformatics analyses. \n\nThe SQANTI3 tool is designed to enable quality control and filtering of long read-defined transcriptomes, which are often rich in artifacts and false-positive isoforms. \n\nTherefore, a good curation of the transcriptome is indispensable to proceed with FIT analysis and produce valid, biologically sound conclusions/hypothesis.", "homepage": "https://github.com/ConesaLab/SQANTI3", "biotoolsID": "sqanti3", "biotoolsCURIE": "biotools:sqanti3", "version": [ "5.5" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3512", "term": "Gene transcripts" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Spain" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/ConesaLab/SQANTI3", "type": [ "Repository" ], "note": "Github repository for source code access and download" } ], "download": [ { "url": "https://github.com/ConesaLab/SQANTI3/releases", "type": "Downloads page", "note": null, "version": null }, { "url": "https://github.com/ConesaLab/SQANTI3/releases/download/v5.5/SQANTI3_v5.5.zip", "type": "Binaries", "note": "Version 5.5 download link from github", "version": "5.5" } ], "documentation": [ { "url": "https://github.com/ConesaLab/SQANTI3/wiki", "type": [ "General" ], "note": "SQANTI3 main documentation resource" }, { "url": "https://github.com/ConesaLab/SQANTI3/blob/master/CODE_OF_CONDUCT.md", "type": [ "Code of conduct" ], "note": null }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-Quality-Control", "type": [ "Command-line options" ], "note": "Command-line options and instructions for the QC submodule" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-filter", "type": [ "Command-line options" ], "note": "Command-line options and instructions for the filter submodule" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-rescue", "type": [ "Command-line options" ], "note": "Command-line options and instructions for the rescue submodule" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Dependencies-and-installation", "type": [ "Installation instructions" ], "note": "Instructions to install and use sqanti, either in docker or apptainer containers or in a linux system" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Tutorial:-running-SQANTI3-on-an-example-dataset", "type": [ "Quick start guide" ], "note": "Basic tutorial with examples to start using SQANTI3" }, { "url": "https://github.com/ConesaLab/SQANTI3/releases", "type": [ "Release notes" ], "note": "Changelog and release notes for every version" }, { "url": "https://github.com/ConesaLab/SQANTI3?tab=readme-ov-file#how-to-cite-sqanti3", "type": [ "Citation instructions" ], "note": "Citation instructions are on the end of the Github repository's main page" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/SQANTI3-memory-requeriments-and-paralellization", "type": [ "Other" ], "note": "Benchmarking about the resources needed to run sqanti3 with multiple cores" } ], "publication": [ { "doi": "10.1038/s41592-024-02229-2", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "5.1", "note": "Publication of SQANTI3", "metadata": { "title": "SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms", "abstract": "SQANTI3 offers a flexible tool for quality control, curation and annotation of long-read RNA sequencing data. SQANTI3 is a tool designed for the quality control, curation and annotation of long-read transcript models obtained with third-generation sequencing technologies. Leveraging its annotation framework, SQANTI3 calculates quality descriptors of transcript models, junctions and transcript ends. With this information, potential artifacts can be identified and replaced with reliable sequences. Furthermore, the integrated functional annotation feature enables subsequent functional iso-transcriptomics analyses.", "date": "2024-05-01T00:00:00Z", "citationCount": 41, "authors": [ { "name": "Pardo-Palacios F.J." }, { "name": "Arzalluz-Luque A." }, { "name": "Kondratova L." }, { "name": "Salguero P." }, { "name": "Mestre-Tomas J." }, { "name": "Amorin R." }, { "name": "Estevan-Morio E." }, { "name": "Liu T." }, { "name": "Nanni A." }, { "name": "McIntyre L." }, { "name": "Tseng E." }, { "name": "Conesa A." } ], "journal": "Nature Methods" } }, { "doi": "10.1101/gr.222976.117", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": null, "note": "Original SQANTI publication", "metadata": { "title": "SQANTI: Extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification", "abstract": "High-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of thousands of novel transcripts, even in well-annotated mammalian species. The advances in sequencing technology have created a need for studies and tools that can characterize these novel variants. Here, we present SQANTI, an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline using 47 unique descriptors. We apply SQANTI to a neuronal mouse transcriptome using Pacific Biosciences (PacBio) long reads and illustrate how the tool is effective in characterizing and describing the composition of the full-length transcriptome. We perform extensive evaluation of ToFU PacBio transcripts by PCR to reveal that an important number of the novel transcripts are technical artifacts of the sequencing approach and that SQANTI quality descriptors can be used to engineer a filtering strategy to remove them. Most novel transcripts in this curated transcriptome are novel combinations of existing splice sites, resulting more frequently in novel ORFs than novel UTRs, and are enriched in both general metabolic and neural-specific functions. We show that these new transcripts have a major impact in the correct quantification of transcript levels by state-of-the-art short-read-based quantification algorithms. By comparing our iso-transcriptome with public proteomics databases, we find that alternative isoforms are elusive to proteogenomics detection. SQANTI allows the user to maximize the analytical outcome of long-read technologies by providing the tools to deliver quality-evaluated and curated full-length transcriptomes.", "date": "2018-03-01T00:00:00Z", "citationCount": 256, "authors": [ { "name": "Tardaguila M." }, { "name": "De La Fuente L." }, { "name": "Marti C." }, { "name": "Pereira C." }, { "name": "Pardo-Palacios F.J." }, { "name": "Del Risco H." }, { "name": "Ferrell M." }, { "name": "Mellado M." }, { "name": "Macchietto M." }, { "name": "Verheggen K." }, { "name": "Edelmann M." }, { "name": "Ezkurdia I." }, { "name": "Vazquez J." }, { "name": "Tress M." }, { "name": "Mortazavi A." }, { "name": "Martens L." }, { "name": "Rodriguez-Navarro S." }, { "name": "Moreno-Manzano V." }, { "name": "Conesa A." } ], "journal": "Genome Research" } } ], "credit": [ { "name": "Ana Conesa", "email": "ana.conesa@csic.es", "url": null, "orcidid": "https://orcid.org/0000-0001-9597-311X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Pablo Atienza", "email": "pablo.atienza@csic.es", "url": null, "orcidid": "https://orcid.org/0009-0002-1093-693X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": "Maintainer of SQANTI3" }, { "name": "Fabián Robledo", "email": "fabian.robledo@csic.es", "url": null, "orcidid": "https://orcid.org/0009-0005-9047-3315", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": "Maintainer of SQANTI3 and ELIXIR-related contact" } ], "owner": "Fabian-RY", "additionDate": "2025-07-07T09:04:03.787249Z", "lastUpdate": "2025-07-07T09:35:33.280160Z", "editPermission": { "type": "group", "authors": [ "Fabian-RY" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PIA - Protein Inference Algorithms", "description": "The main focus lays on the integrated inference algorithms, concluding the proteins from a set of identified spectra. 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The main focus of PIA lays on the integrated inference algorithms, i.e. concluding the proteins from a set of identified spectra. But it also allows you to inspect your peptide spectrum matches, calculate FDR values across different search engine results and visualize the correspondence between PSMs, peptides and proteins. Search engine results in several formats peptide spectrum matches (PSMs) and peptides Inferred Proteins", "cmd": null } ], "toolType": [ "Command-line tool", "Library", "Desktop application", "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_3120", "term": "Protein variants" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java" ], "license": "BSD-3-Clause", "collectionID": [ "KNIME", "de.NBI", "Proteomics", "BioInfra.Prot", "CUBiMed.RUB" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [ "Proteomics" ], "link": [ { "url": "https://github.com/medbioinf/pia", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/mpc-bioinformatics/pia", "type": "Source code", "note": null, "version": null }, { "url": "http://bioconda.github.io/recipes/pia/README.html", "type": "Software package", "note": null, "version": null }, { "url": "https://github.com/mpc-bioinformatics/pia/releases", "type": "Binaries", "note": null, "version": null }, { "url": "https://hub.docker.com/r/julianusz/pia", "type": "Container file", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/medbioinf/pia/wiki", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jproteome.5b00121", "pmid": "25938255", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "PIA: An Intuitive Protein Inference Engine with a Web-Based User Interface", "abstract": "Protein inference connects the peptide spectrum matches (PSMs) obtained from database search engines back to proteins, which are typically at the heart of most proteomics studies. Different search engines yield different PSMs and thus different protein lists. Analysis of results from one or multiple search engines is often hampered by different data exchange formats and lack of convenient and intuitive user interfaces. We present PIA, a flexible software suite for combining PSMs from different search engine runs and turning these into consistent results. PIA can be integrated into proteomics data analysis workflows in several ways. A user-friendly graphical user interface can be run either locally or (e.g., for larger core facilities) from a central server. For automated data processing, stand-alone tools are available. PIA implements several established protein inference algorithms and can combine results from different search engines seamlessly. On several benchmark data sets, we show that PIA can identify a larger number of proteins at the same protein FDR when compared to that using inference based on a single search engine. PIA supports the majority of established search engines and data in the mzIdentML standard format. It is implemented in Java and freely available at https://github.com/mpc-bioinformatics/pia.", "date": "2015-07-02T00:00:00Z", "citationCount": 57, "authors": [ { "name": "Uszkoreit J." }, { "name": "Maerkens A." }, { "name": "Perez-Riverol Y." }, { "name": "Meyer H.E." }, { "name": "Marcus K." }, { "name": "Stephan C." }, { "name": "Kohlbacher O." }, { "name": "Eisenacher M." } ], "journal": "Journal of Proteome Research" } }, { "doi": "10.1021/acs.jproteome.8b00723", "pmid": "30474983", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Protein Inference Using PIA Workflows and PSI Standard File Formats", "abstract": "Proteomics using LC-MS/MS has become one of the main methods to analyze the proteins in biological samples in high-throughput. But the existing mass-spectrometry instruments are still limited with respect to resolution and measurable mass ranges, which is one of the main reasons why shotgun proteomics is the major approach. Here proteins are digested, which leads to the identification and quantification of peptides instead. While often neglected, the important step of protein inference needs to be conducted to infer from the identified peptides to the actual proteins in the original sample. In this work, we highlight some of the previously published and newly added features of the tool PIA - Protein Inference Algorithms, which helps the user with the protein inference of measured samples. We also highlight the importance of the usage of PSI standard file formats, as PIA is the only current software supporting all available standards used for spectrum identification and protein inference. Additionally, we briefly describe the benefits of working with workflow environments for proteomics analyses and show the new features of the PIA nodes for the KNIME Analytics Platform. Finally, we benchmark PIA against a recently published data set for isoform detection. PIA is open source and available for download on GitHub (https://github.com/mpc-bioinformatics/pia) or directly via the community extensions inside the KNIME analytics platform.", "date": "2019-02-01T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Uszkoreit J." }, { "name": "Perez-Riverol Y." }, { "name": "Eggers B." }, { "name": "Marcus K." }, { "name": "Eisenacher M." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Julian Uszkoreit", "email": "julian.uszkoreit@rub.de", "url": null, "orcidid": "http://orcid.org/0000-0001-7522-4007", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer" ], "note": null }, { "name": "CUBiMed.RUB", "email": "cubimed@rub.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "julianu", "additionDate": "2016-07-12T10:54:05Z", "lastUpdate": "2025-05-02T13:15:26.717477Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "OpenMS", "description": "Open source library and a collection of tools and interfaces for the analysis of mass spectrometry data. Includes over 200 standalone (TOPP) tools that can be combined to a workflow with the integrated workflow editor TOPPAS. 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"term": "Annotation" }, { "uri": "http://edamontology.org/operation_3092", "term": "Protein feature detection" }, { "uri": "http://edamontology.org/operation_3705", "term": "Isotope-coded protein label" }, { "uri": "http://edamontology.org/operation_3634", "term": "Label-free quantification" }, { "uri": "http://edamontology.org/operation_3639", "term": "iTRAQ" }, { "uri": "http://edamontology.org/operation_3631", "term": "Peptide identification" }, { "uri": "http://edamontology.org/operation_3215", "term": "Peak detection" }, { "uri": "http://edamontology.org/operation_3694", "term": "Mass spectrum visualisation" }, { "uri": "http://edamontology.org/operation_3635", "term": "Labeled quantification" }, { "uri": "http://edamontology.org/operation_3359", "term": "Splitting" }, { "uri": "http://edamontology.org/operation_3214", "term": "Spectral analysis" }, { "uri": "http://edamontology.org/operation_3629", "term": "Deisotoping" }, { "uri": "http://edamontology.org/operation_3649", 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"http://edamontology.org/format_3654", "term": "mzXML" }, { "uri": "http://edamontology.org/format_3246", "term": "TraML" }, { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3247", "term": "mzIdentML" }, { "uri": "http://edamontology.org/format_3651", "term": "MGF" }, { "uri": "http://edamontology.org/format_3683", "term": "qcML" } ] }, { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3655", "term": "pepXML" }, { "uri": "http://edamontology.org/format_3248", "term": "mzQuantML" }, { "uri": "http://edamontology.org/format_3652", "term": "dta" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" }, { "uri": "http://edamontology.org/format_3764", "term": "idXML" }, { "uri": "http://edamontology.org/format_3654", "term": "mzXML" }, { "uri": "http://edamontology.org/format_3246", "term": "TraML" }, { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3247", "term": "mzIdentML" }, { "uri": "http://edamontology.org/format_3651", "term": "MGF" }, { "uri": "http://edamontology.org/format_3683", "term": "qcML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library", "Workbench" ], "topic": [ { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C++" ], "license": "BSD-3-Clause", "collectionID": [ "KNIME", "de.NBI", "Proteomics", "OpenMS" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/OpenMS/OpenMS", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/OpenMS/OpenMS", "type": "Source code", "note": null, "version": null }, { "url": "http://sourceforge.net/projects/open-ms/files/OpenMS/OpenMS-2.0/", "type": "Binaries", "note": null, "version": null }, { "url": "https://github.com/OpenMS/OpenMS", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "http://ftp.mi.fu-berlin.de/pub/OpenMS/release-documentation/html/index.html", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/nmeth.3959", "pmid": "27575624", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "OpenMS: A flexible open-source software platform for mass spectrometry data analysis", "abstract": "© 2016 Nature America, Inc. All rights reserved.High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de) a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease.", "date": "2016-08-30T00:00:00Z", "citationCount": 246, "authors": [ { "name": "Rost H.L." }, { "name": "Sachsenberg T." }, { "name": "Aiche S." }, { "name": "Bielow C." }, { "name": "Weisser H." }, { "name": "Aicheler F." }, { "name": "Andreotti S." }, { "name": "Ehrlich H.-C." }, { "name": "Gutenbrunner P." }, { "name": "Kenar E." }, { "name": "Liang X." }, { "name": "Nahnsen S." }, { "name": "Nilse L." }, { "name": "Pfeuffer J." }, { "name": "Rosenberger G." }, { "name": "Rurik M." }, { "name": "Schmitt U." }, { "name": "Veit J." }, { "name": "Walzer M." }, { "name": "Wojnar D." }, { "name": "Wolski W.E." }, { "name": "Schilling O." }, { "name": "Choudhary J.S." }, { "name": "Malmstrom L." }, { "name": "Aebersold R." }, { "name": "Reinert K." }, { "name": "Kohlbacher O." } ], "journal": "Nature Methods" } }, { "doi": "10.1007/978-1-60761-987-1_23", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "OpenMS and TOPP: open source software for LC-MS data analysis.", "abstract": "Proteomics experiments based on state-of-the-art mass spectrometry produce vast amounts of data, which cannot be analyzed manually. Hence, software is needed which is able to analyze the data in an automated fashion. The need for robust and reusable software tools triggered the development of libraries implementing different algorithms for the various analysis steps. OpenMS is such a software library and provides a wealth of data structures and algorithms for the analysis of mass spectrometric data. For users unfamiliar with programming, TOPP (\"The OpenMS Proteomics Pipeline\") offers a wide range of already implemented tools sharing the same interface and designed for a specific analysis task each. TOPP thus makes the sophisticated algorithms of OpenMS accessible to nonprogrammers. The individual TOPP tools can be strung together into pipelines for analyzing mass spectrometry-based experiments starting from the raw output of the mass spectrometer. These analysis pipelines can be constructed using a graphical editor. Even complex analytical workflows can thus be analyzed with ease.", "date": "2011-01-01T00:00:00Z", "citationCount": 65, "authors": [ { "name": "Bertsch A." }, { "name": "Gropl C." }, { "name": "Reinert K." }, { "name": "Kohlbacher O." } ], "journal": "Methods in molecular biology (Clifton, N.J.)" } } ], "credit": [ { "name": "ETH Zürich", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Eberhard-Karls-Universität Tübingen", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Freie Universität Berlin", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Center for Integrative Bioinformatics (CiBi)", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [], "note": null }, { "name": "cibi", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "General Mailinglist", "email": "open-ms-general@lists.sourceforge.net", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Support" ], "note": null }, { "name": "General Mailinglist", "email": "open-ms-general@lists.sourceforge.net", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Hannes Röst", "email": null, "url": null, "orcidid": "http://orcid.org/0000-0003-0990-7488", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "samwein", "additionDate": "2016-01-19T16:39:56Z", "lastUpdate": "2025-04-30T11:39:30.251890Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "compareMS2", "description": "compareMS2 is a tool for comparing sets of (tandem) mass spectra for clustering samples, molecular phylogenetics, identification of biological species or tissues, and quality control. compareMS2 currently consumes Mascot Generic Format, or MGF, and produces output in a variety of common image and distance matrix formats.", "homepage": "https://github.com/524D/compareMS2", "biotoolsID": "comparems2", "biotoolsCURIE": "biotools:comparems2", "version": [ "1.0", "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2424", "term": "Comparison" }, { "uri": "http://edamontology.org/operation_0567", "term": "Phylogenetic tree visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3651", "term": "MGF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3272", "term": "Species tree" }, "format": [ { "uri": "http://edamontology.org/format_3603", "term": "PNG" }, { "uri": "http://edamontology.org/format_3604", "term": "SVG" } ] }, { "data": { "uri": "http://edamontology.org/data_2855", "term": "Distance matrix" }, "format": [ { "uri": "http://edamontology.org/format_1991", "term": "mega" }, { "uri": "http://edamontology.org/format_1912", "term": "Nexus format" }, { "uri": "http://edamontology.org/format_1910", "term": "newick" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0084", "term": "Phylogeny" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C", "JavaScript" ], "license": "MIT", "collectionID": [ "ms-utils", "Proteomics" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Netherlands" ], "elixirCommunity": [ "Proteomics" ], "link": [ { "url": "https://github.com/524D/compareMS2", "type": [ "Repository" ], "note": null }, { "url": "https://www.ms-utils.org/compareMS2.html", "type": [ "Software catalogue" ], "note": null }, { "url": "https://research-software-directory.org/software/comparems2", "type": [ "Software catalogue" ], "note": null } ], "download": [ { "url": "http://www.ms-utils.org/compareMS2.c", "type": "Source code", "note": null, "version": "1.0" }, { "url": "http://www.ms-utils.org/compareMS2.html", "type": "Binaries", "note": null, "version": "1.0" }, { "url": "http://www.ms-utils.org/compareMS2.c", "type": "Source code", "note": null, "version": "1.0" }, { "url": "https://github.com/524D/compareMS2/tree/main/src", "type": "Source code", "note": null, "version": "2.0" }, { "url": "https://github.com/524D/compareMS2/tree/main", "type": "Binaries", "note": null, "version": "2.0" } ], "documentation": [ { "url": "http://www.ms-utils.org/compareMS2.html", "type": [ "General", "Command-line options" ], "note": null }, { "url": "https://github.com/524D/compareMS2", "type": [ "General", "User manual", "Command-line options", "Installation instructions" ], "note": null } ], "publication": [ { "doi": "10.1002/rcm.6162", "pmid": "22368051", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Molecular phylogenetics by direct comparison of tandem mass spectra", "abstract": "Rationale: Molecular phylogenetics is the study of evolution and relatedness of organisms or genes. Mass spectrometry is used routinely for bacterial identification and has also been used for phylogenetic analysis, for instance from bone material. Unfortunately, only a small fraction of the acquired tandem mass spectra allow direct interpretation. Methods: We describe a new algorithm and software for molecular phylogenetics using pairwise comparisons of tandem mass spectra from enzymatically digested proteins. The spectra need not be annotated and all acquired data is used in the analysis. To demonstrate the method, we analyzed tryptic digests of sera from four great apes and two other primates. Results: The distribution of spectra dot products for thousands of tandem mass spectra collected from two samples provides a measure on the fraction of shared peptides between the two samples. When inverted, this becomes a distance metric. By pairwise comparison between species and averaging over four individuals per species, it was possible to reconstruct the unique correct phylogenetic tree for the great apes and other primates. Conclusions: The new method described here has several attractive features compared with existing methods, among them simplicity, the unbiased use of all acquired data rather than a small subset of spectra, and the potential use of heavily degraded proteins or proteins with a priori unknown modifications. © 2012 John Wiley & Sons, Ltd.", "date": "2012-04-15T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Palmblad M." }, { "name": "Deelder A.M." } ], "journal": "Rapid Communications in Mass Spectrometry" } }, { "doi": "10.1021/acs.jproteome.2c00457", "pmid": "36173614", "pmcid": "PMC9903320", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry Datasets", "abstract": "It has long been known that biological species can be identified from mass spectrometry data alone. Ten years ago, we described a method and software tool, compareMS2, for calculating a distance between sets of tandem mass spectra, as routinely collected in proteomics. This method has seen use in species identification and mixture characterization in food and feed products, as well as other applications. Here, we present the first major update of this software, including a new metric, a graphical user interface and additional functionality. The data have been deposited to ProteomeXchange with dataset identifier PXD034932.", "date": "2023-02-03T00:00:00Z", "citationCount": 7, "authors": [ { "name": "Marissen R." }, { "name": "Varunjikar M.S." }, { "name": "Laros J.F.J." }, { "name": "Rasinger J.D." }, { "name": "Neely B.A." }, { "name": "Palmblad M." } ], "journal": "Journal of Proteome Research" } }, { "doi": "10.1021/acs.jproteome.1c00528", "pmid": "34523928", "pmcid": "PMC8491155", "type": [ "Review" ], "version": "2.0", "note": null, "metadata": { "title": "Rewinding the Molecular Clock: Looking at Pioneering Molecular Phylogenetics Experiments in the Light of Proteomics", "abstract": "Science is full of overlooked and undervalued research waiting to be rediscovered. Proteomics is no exception. In this perspective, we follow the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing tryptic peptides across animal species. This pioneering work directly led to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics. In the decades following, proteins continued to provide essential clues on evolutionary history. While technology has continued to improve, contemporary proteomics has strayed from this larger biological context, rarely comparing species or asking how protein structure, function, and interactions have evolved. Here we recombine proteomics with molecular phylogenetics, highlighting the value of framing proteomic results in a larger biological context and how almost forgotten research, though technologically surpassed, can still generate new ideas and illuminate our work from a different perspective. Though it is infeasible to read all research published on a large topic, looking up older papers can be surprisingly rewarding when rediscovering a \"gem\"at the end of a long citation chain, aided by digital collections and perpetually helpful librarians. Proper literature study reduces unnecessary repetition and allows research to be more insightful and impactful by truly standing on the shoulders of giants. 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