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{ "count": 2062, "next": "?page=2", "previous": null, "list": [ { "name": "SAMtools", "description": "SAMtools and BCFtools are widely used programs for processing and analysing high-throughput sequencing data. 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null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Project", "typeRole": [ "Support" ], "note": null } ], "owner": "awhitwham", "additionDate": "2017-01-13T13:16:12Z", "lastUpdate": "2025-12-16T15:42:24.521617Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-EE", "animalandcropgenomics", "alice", "awhitwham", "sergitobara" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "HTSlib", "description": "The main purpose of HTSlib is to provide access to genomic information files, both alignment data (SAM, BAM, and CRAM formats) and variant data (VCF and BCF formats). 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for annotating in-source metabolite ions from LC-MS untargeted metabolomics data based on a coelution similarity network.", "homepage": "https://github.com/osenan/cliqueMS", "biotoolsID": "CliqueMS", "biotoolsCURIE": "biotools:CliqueMS", "version": [ "0.3.2" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3798", "term": "Read binning" }, { "uri": "http://edamontology.org/operation_3803", "term": "Natural product identification" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "R", "C++" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/osenan/cliqueMS/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://cran.r-project.org/src/contrib/Archive/cliqueMS/", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/osenan/cliqueMS/blob/master/vignettes/annotate_features.Rmd", "type": [ "Training material" ], "note": "Tutorial material" } ], "publication": [ { "doi": "10.1093/bioinformatics/btz207", "pmid": "30903689", "pmcid": "PMC6792096", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "CliqueMS: A computational tool for annotating in-source metabolite ions from LC-MS untargeted metabolomics data based on a coelution similarity network", "abstract": "The analysis of biological samples in untargeted metabolomic studies using LC-MS yields tens of thousands of ion signals. Annotating these features is of the utmost importance for answering questions as fundamental as, e.g. how many metabolites are there in a given sample.Results: Here, we introduce CliqueMS, a new algorithm for annotating in-source LC-MS1 data. CliqueMS is based on the similarity between coelution profiles and therefore, as opposed to most methods, allows for the annotation of a single spectrum. Furthermore, CliqueMS improves upon the state of the art in several dimensions: (i) it uses a more discriminatory feature similarity metric; (ii) it treats the similarities between features in a transparent way by means of a simple generativemodel; (iii) it uses a well-grounded maximum likelihood inference approach to group features; (iv) it uses empirical adduct frequencies to identify the parental mass and (v) it deals more flexibly with the identification of the parental mass by proposing and ranking alternative annotations. We validate our approach with simple mixtures of standards and with real complex biological samples. CliqueMS reduces the thousands of features typically obtained in complex samples to hundreds of metabolites, and it is able to correctly annotate more metabolites and adducts from a single spectrum than available tools.", "date": "2019-10-15T00:00:00Z", "citationCount": 48, "authors": [ { "name": "Senan O." }, { "name": "Aguilar-Mogas A." }, { "name": "Navarro M." }, { "name": "Capellades J." }, { "name": "Noon L." }, { "name": "Burks D." }, { "name": "Yanes O." }, { "name": "Guimera R." }, { "name": "Sales-Pardo M." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Oriol Senan", "email": "oriol.senan@urv.cat", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Ruta", "additionDate": "2019-07-04T14:05:39Z", "lastUpdate": "2025-11-03T16:44:03.166147Z", "editPermission": { "type": "group", "authors": [ "recetox-specdatri" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "The MINERVA Platform", "description": "The MINERVA (Molecular Interaction NEtwoRk VisuAlization) platform is a standalone webserver for visualization, exploration and management of molecular networks encoded in SBGN-compliant format, including files produced using CellDesigner or SBGN editors. 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"typeEntity": "Person", "typeRole": [ "Developer", "Maintainer" ], "note": null }, { "name": "Erasmus MC", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "hachterberg", "additionDate": "2025-07-23T10:24:09.622930Z", "lastUpdate": "2025-07-24T08:55:06.000976Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "InMoose", "description": "InMoose, the INtegrated Multi-Omic Open-Source environment, ports to Python state-of-the-art R tools for the analysis of transcriptomic data.", "homepage": "https://github.com/epigenelabs/inmoose", "biotoolsID": "inmoose", "biotoolsCURIE": "biotools:inmoose", "version": [ "0.8.0" ], "otherID": [], "relation": [ { "biotoolsID": "deseq2", "type": "isNewVersionOf" }, { "biotoolsID": "limma", "type": "isNewVersionOf" }, { "biotoolsID": "edger", "type": "isNewVersionOf" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3223", "term": "Differential gene expression profiling" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3917", "term": "Count matrix" }, "format": [] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/epigenelabs/inmoose", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/epigenelabs/inmoose/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://inmoose.readthedocs.io/en/stable/", "type": [ "General" ], "note": null }, { "url": "https://colab.research.google.com/drive/1bzmNDZeaw1A6tSgfx61O6PFtaQDve6SV?usp=sharing", "type": [ "Quick start guide" ], "note": null } ], "publication": [ { "doi": "10.1038/s41598-025-03376-y", "pmid": null, "pmcid": null, "type": [ "Primary", "Usage" ], "version": null, "note": null, "metadata": { "title": "Bridging the gap between R and Python in bulk transcriptomic data analysis with InMoose", "abstract": "We introduce InMoose, an open-source Python environment aimed at omic data analysis. We illustrate its capabilities for bulk transcriptomic data analysis. Due to its wide adoption, Python has grown as a de facto standard in fields increasingly important for bioinformatic pipelines, such as data science, machine learning, or artificial intelligence (AI). As a general-purpose language, Python is also recognized for its versatility and scalability. InMoose aims at bringing state-of-the-art tools, historically written in R, to the Python ecosystem. InMoose focuses on providing drop-in replacements for R tools, to ensure consistency and reproducibility between R-based and Python-based pipelines. The first development phase has focused on bulk transcriptomic data, with current capabilities encompassing data simulation, batch effect correction, and differential analysis and meta-analysis.", "date": "2025-12-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Colange M." }, { "name": "Appe G." }, { "name": "Meunier L." }, { "name": "Weill S." }, { "name": "Johnson W.E." }, { "name": "Nordor A." }, { "name": "Behdenna A." } ], "journal": "Scientific Reports" } }, { "doi": "10.1186/s12859-023-05578-5", "pmid": null, "pmcid": null, "type": [ "Benchmarking study", "Method" ], "version": null, "note": null, "metadata": { "title": "pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods", "abstract": "Background: Variability in datasets is not only the product of biological processes: they are also the product of technical biases. ComBat and ComBat-Seq are among the most widely used tools for correcting those technical biases, called batch effects, in, respectively, microarray and RNA-Seq expression data. Results: In this technical note, we present a new Python implementation of ComBat and ComBat-Seq. While the mathematical framework is strictly the same, we show here that our implementations: (i) have similar results in terms of batch effects correction; (ii) are as fast or faster than the original implementations in R and; (iii) offer new tools for the bioinformatics community to participate in its development. pyComBat is implemented in the Python language and is distributed under GPL-3.0 (https://www.gnu.org/licenses/gpl-3.0.en.html) license as a module of the inmoose package. Source code is available at https://github.com/epigenelabs/inmoose and Python package at https://pypi.org/project/inmoose . Conclusions: We present a new Python implementation of state-of-the-art tools ComBat and ComBat-Seq for the correction of batch effects in microarray and RNA-Seq data. This new implementation, based on the same mathematical frameworks as ComBat and ComBat-Seq, offers similar power for batch effect correction, at reduced computational cost.", "date": "2023-12-01T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Behdenna A." }, { "name": "Colange M." }, { "name": "Haziza J." }, { "name": "Gema A." }, { "name": "Appe G." }, { "name": "Azencott C.-A." }, { "name": "Nordor A." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.1186/s12859-025-06180-7", "pmid": null, "pmcid": null, "type": [ "Benchmarking study", "Method" ], "version": null, "note": null, "metadata": { "title": "Differential expression analysis with inmoose, the integrated multi-omic open-source environment in Python", "abstract": "Background: Differential gene expression analysis is a prominent technique for the analysis of biomolecular data to identify genetic features associated with phenotypes. Limma—for microarray data –, and edgeR and DESeq2—for RNA-Seq data–, are the most widely used tools for differential gene expression analysis of bulk transcriptomic data. Results: We present the differential expression features of InMoose, a Python implementation of R tools limma, edgeR, and DESeq2. We experimentally show that InMoose stands as a drop-in replacement for those tools, with nearly identical results. This ensures reproducibility when interfacing both languages in bioinformatic pipelines. InMoose is an open source software released under the GPL3 license, available at www.github.com/epigenelabs/inmoose and https://inmoose.readthedocs.io. Conclusions: We present a new Python implementation of state-of-the-art tools limma, edgeR, and DESeq2, to perform differential gene expression analysis of bulk transcriptomic data. This new implementation exhibits results nearly identical to the original tools, improving interoperability and reproducibility between Python and R bioinformatics pipelines.", "date": "2025-12-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Colange M." }, { "name": "Appe G." }, { "name": "Meunier L." }, { "name": "Weill S." }, { "name": "Nordor A." }, { "name": "Behdenna A." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Maximilien Colange", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-4769-3302", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Epigene Labs", "email": null, "url": "https://www.epigenelabs.com/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "maximilien.colange", "additionDate": "2025-07-10T12:32:00.838316Z", "lastUpdate": "2025-07-10T13:00:37.310588Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "ColoPola dataset for colorectal cancer detection", "description": "The dataset consists of 572 slices (specimens) with 20,592 images. There are 284 cancer samples and 288 normal samples. The lists of samples for training (train+val) set and testing set are provided in the Zenodo repository. 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It includes features to define models of biological processes, simulate and analyze these models, generate analysis reports, and import/export models in SBML format.", "homepage": "http://copasi.org/", "biotoolsID": "copasi", "biotoolsCURIE": "biotools:copasi", "version": [], "otherID": [], "relation": [ { "biotoolsID": "corc", "type": "usedBy" }, { "biotoolsID": "pycotools", "type": "usedBy" }, { "biotoolsID": "biosimulations", "type": "includedIn" }, { "biotoolsID": "sbmlwebapp", "type": "usedBy" }, { "biotoolsID": "libsbml", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3562", "term": "Network simulation" }, { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" }, { "uri": "http://edamontology.org/operation_3660", "term": "Metabolic network modelling" }, { "uri": "http://edamontology.org/operation_3926", "term": "Pathway visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2600", "term": "Pathway or network" }, "format": [ { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "uri": "http://edamontology.org/format_3239", "term": "CopasiML" }, { "uri": "http://edamontology.org/format_3685", "term": "SED-ML" }, { "uri": "http://edamontology.org/format_3686", "term": "COMBINE OMEX" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2600", "term": "Pathway or network" }, "format": [ { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "uri": "http://edamontology.org/format_3239", "term": "CopasiML" }, { "uri": "http://edamontology.org/format_3685", "term": "SED-ML" }, { "uri": "http://edamontology.org/format_3686", "term": "COMBINE OMEX" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C++" ], "license": "Artistic-2.0", "collectionID": [ "de.NBI", "EBI Training Tools" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://groups.google.com/g/copasi-user-forum", "type": [ "Discussion forum" ], "note": "User Forum" }, { "url": "http://tracker.copasi.org/", "type": [ "Issue tracker" ], "note": "Issue tracker" }, { "url": "https://github.com/copasi/COPASI", "type": [ "Repository" ], "note": "Github Repo" }, { "url": "https://fosstodon.org/@copasi", "type": [ "Social media" ], "note": null } ], "download": [ { "url": "http://copasi.org/Download/", "type": "Binaries", "note": "Source and binary packages are available for download.", "version": null } ], "documentation": [ { "url": "http://copasi.org/Support/User_Manual/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btl485", "pmid": "17032683", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "COPASI - A COmplex PAthway SImulator", "abstract": "Motivation: Simulation and modeling is becoming a standard approach to understand complex biochemical processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods. Results: Here, we present COPASI, a platform-independent and user-friendly biochemical simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic-stochastic methods, and the importance of random number generator numerical resolution in stochastic simulation. © 2006 Oxford University Press.", "date": "2006-12-15T00:00:00Z", "citationCount": 2004, "authors": [ { "name": "Hoops S." }, { "name": "Gauges R." }, { "name": "Lee C." }, { "name": "Pahle J." }, { "name": "Simus N." }, { "name": "Singhal M." }, { "name": "Xu L." }, { "name": "Mendes P." }, { "name": "Kummer U." } ], "journal": "Bioinformatics" } }, { "doi": "10.1007/978-1-59745-525-1_2", "pmid": "19399433", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Computational modeling of biochemical networks using COPASI", "abstract": "Computational modeling and simulation of biochemical networks is at the core of systems biology and this includes many types of analyses that can aid understanding of how these systems work. COPASI is a generic software package for modeling and simulation of biochemical networks which provides many of these analyses in convenient ways that do not require the user to program or to have deep knowledge of the numerical algorithms. Here we provide a description of how these modeling techniques can be applied to biochemical models using COPASI. The focus is both on practical aspects of software usage as well as on the utility of these analyses in aiding biological understanding. Practical examples are described for steady-state and time-course simulations, stoichiometric analyses, parameter scanning, sensitivity analysis (including metabolic control analysis), global optimization, parameter estimation, and stochastic simulation. The examples used are all published models that are available in the BioModels database in SBML format. © 2009 Humana Press.", "date": "2009-12-01T00:00:00Z", "citationCount": 171, "authors": [ { "name": "Mendes P." }, { "name": "Hoops S." }, { "name": "Sahle S." }, { "name": "Gauges R." }, { "name": "Dada J." }, { "name": "Kummer U." } ], "journal": "Methods in Molecular Biology" } }, { "doi": "10.1016/j.jbiotec.2017.06.1200", "pmid": "28655634", "pmcid": "PMC5623632", "type": [], "version": null, "note": null, "metadata": { "title": "COPASI and its applications in biotechnology", "abstract": "COPASI is software used for the creation, modification, simulation and computational analysis of kinetic models in various fields. It is open-source, available for all major platforms and provides a user-friendly graphical user interface, but is also controllable via the command line and scripting languages. These are likely reasons for its wide acceptance. We begin this review with a short introduction describing the general approaches and techniques used in computational modeling in the biosciences. Next we introduce the COPASI package, and its capabilities, before looking at typical applications of COPASI in biotechnology.", "date": "2017-11-10T00:00:00Z", "citationCount": 81, "authors": [ { "name": "Bergmann F.T." }, { "name": "Hoops S." }, { "name": "Klahn B." }, { "name": "Kummer U." }, { "name": "Mendes P." }, { "name": "Pahle J." }, { "name": "Sahle S." } ], "journal": "Journal of Biotechnology" } } ], "credit": [ { "name": null, "email": null, "url": "http://copasi.org/About/Team/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Frank T. Bergmann", "email": "frank.bergmann@bioquant.uni-heidelberg.de", "url": null, "orcidid": "https://orcid.org/0000-0001-5553-4702", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "frankbergmann", "additionDate": "2017-01-17T15:07:47Z", "lastUpdate": "2025-07-07T11:17:37.638447Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "purge_dups", "description": "Identifying and removing haplotypic duplication in primary genome assemblies | haplotypic duplication identification tool | scripts/pd_config.py: script to generate a configuration file used by run_purge_dups.py | purge haplotigs and overlaps in an assembly based on read depth | Given a primary assembly pri_asm and an alternative assembly hap_asm (optional, if you have one), follow the steps shown below to build your own purge_dups pipeline, steps with same number can be run simultaneously. Among all the steps, although step 4 is optional, we highly recommend our users to do so, because assemblers may produce overrepresented seqeuences. In such a case, The final step 4 can be applied to remove those seqeuences", "homepage": "https://github.com/dfguan/purge_dups", "biotoolsID": "purge_dups", "biotoolsCURIE": "biotools:purge_dups", "version": [ "v.1.2.6" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0525", "term": "Genome assembly" }, { "uri": "http://edamontology.org/operation_3798", "term": "Read binning" }, { "uri": "http://edamontology.org/operation_3216", "term": "Scaffolding" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] }, { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "Python", "C" ], "license": "MIT", "collectionID": [ "ONTeater" ], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/dfguan/purge_dups", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/dfguan/purge_dups/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1101/729962", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Dengfeng Guan", "email": null, "url": "https://www.chatlink.com.cn", "orcidid": "https://orcid.org/0000-0002-6376-3940", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "Pub2Tools", "additionDate": "2019-11-14T18:08:10Z", "lastUpdate": "2025-06-30T15:34:51.626796Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Compleasm", "description": "Compleasm: a faster and more accurate reimplementation of BUSCO.\nIt provides measures for quantitative assessment of genome assembly, gene set, and transcriptome completeness based on evolutionarily informed expectations of gene content from near-universal single-copy orthologs.", "homepage": "https://github.com/huangnengCSU/compleasm", "biotoolsID": "compleasm", "biotoolsCURIE": "biotools:compleasm", "version": [ "v.0.2.5" ], "otherID": [], "relation": [ { "biotoolsID": "busco", "type": "isNewVersionOf" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3180", "term": "Sequence assembly validation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_2546", "term": "FASTA-like" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2955", "term": "Sequence report" }, "format": [] } ], "note": "Runs compleasm using the BUSCO set corresponding to the lineage given.", "cmd": "compleasm run -l \"$lineage\" -a assembly.fa -o output_prefix" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [ "ONTeater" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/huangnengCSU/compleasm", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/huangnengCSU/compleasm/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://busco.ezlab.org/list_of_lineages.html", "type": [ "Other" ], "note": "List of accepted lineages (taxonomic groups with curated BUSCO sets)" } ], "download": [], "documentation": [ { "url": "https://github.com/huangnengCSU/compleasm/blob/0.2.6/README.md", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btad595", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "compleasm: a faster and more accurate reimplementation of BUSCO", "abstract": "Motivation: Evaluating the gene completeness is critical to measuring the quality of a genome assembly. An incomplete assembly can lead to errors in gene predictions, annotation, and other downstream analyses. Benchmarking Universal Single-Copy Orthologs (BUSCO) is a widely used tool for assessing the completeness of genome assembly by testing the presence of a set of single-copy orthologs conserved across a wide range of taxa. However, BUSCO is slow particularly for large genome assemblies. It is cumbersome to apply BUSCO to a large number of assemblies. Results: Here, we present compleasm, an efficient tool for assessing the completeness of genome assemblies. Compleasm utilizes the miniprot protein-to-genome aligner and the conserved orthologous genes from BUSCO. It is 14 times faster than BUSCO for human assemblies and reports a more accurate completeness of 99.6% than BUSCO's 95.7%, which is in close agreement with the annotation completeness of 99.5% for T2T-CHM13.", "date": "2023-10-01T00:00:00Z", "citationCount": 95, "authors": [ { "name": "Huang N." }, { "name": "Li H." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Neng Huang", "email": "neng@ds.dfci.harvard.edu", "url": null, "orcidid": "https://orcid.org/0000-0001-7187-0749", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "rlibouban", "additionDate": "2024-03-18T14:51:49.667412Z", "lastUpdate": "2025-06-30T15:30:41.266812Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "NanoPlot", "description": "NanoPlot is a tool with various visualizations of sequencing data in bam, cram, fastq, fasta or platform-specific TSV summaries, mainly intended for long-read sequencing from Oxford Nanopore Technologies and Pacific Biosciences", "homepage": "https://github.com/wdecoster/NanoPlot", "biotoolsID": "nanoplot", "biotoolsCURIE": "biotools:nanoplot", "version": [ "v.1.42.0" ], "otherID": [], "relation": [ { "biotoolsID": "nanopack", "type": "includedIn" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2940", "term": "Scatter plot plotting" }, { "uri": "http://edamontology.org/operation_2943", "term": "Box-Whisker plot plotting" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_2546", "term": "FASTA-like" }, { "uri": "http://edamontology.org/format_1207", "term": "nucleotide" } ] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [ "ONTeater" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/wdecoster/NanoPlot", "type": [ "Repository" ], "note": "Issue tracker and most up to date software version" }, { "url": "http://nanoplot.bioinf.be/", "type": [ "Service" ], "note": "Web service with more limited options compared to the command line tool" } ], "download": [ { "url": "https://anaconda.org/bioconda/nanoplot", "type": "Command-line specification", "note": null, "version": null }, { "url": "https://pypi.org/project/NanoPlot/", "type": "Command-line specification", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/wdecoster/NanoPlot", "type": [ "Command-line options" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/bty149", "pmid": "29547981", "pmcid": "PMC6061794", "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "NanoPack: Visualizing and processing long-read sequencing data", "abstract": "Summary: Here we describe NanoPack, a set of tools developed for visualization and processing of long-read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences. Availability and implementation: The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.", "date": "2018-08-01T00:00:00Z", "citationCount": 1840, "authors": [ { "name": "De Coster W." }, { "name": "D'Hert S." }, { "name": "Schultz D.T." }, { "name": "Cruts M." }, { "name": "Van Broeckhoven C." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Wouter De Coster", "email": null, "url": "https://gigabaseorgigabyte.wordpress.com/", "orcidid": "https://orcid.org/0000-0002-5248-8197", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "wdecoster", "additionDate": "2021-07-06T20:27:27Z", "lastUpdate": "2025-06-18T12:31:48.762608Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "kraken2", "description": "Kraken 2 is the newest version of Kraken, a taxonomic classification system using exact k-mer matches to achieve high accuracy and fast classification speeds. This classifier matches each k-mer within a query sequence to the lowest common ancestor (LCA) of all genomes containing the given k-mer. The k-mer assignments inform the classification algorithm.\nAny assumption that Kraken’s raw read assignments can be directly translated into species or strain-level abundance estimates is flawed. Bracken (Bayesian Reestimation of Abundance after Classification with KrakEN), estimates species abundances in metagenomics samples by probabilistically re-distributing reads in the taxonomic tree. (Lu, Jennifer et al. “Bracken: estimating species abundance in metagenomics data.”)", "homepage": "https://ccb.jhu.edu/software/kraken2/", "biotoolsID": "kraken2", "biotoolsCURIE": "biotools:kraken2", "version": [ "2.0.8-beta" ], "otherID": [], "relation": [ { "biotoolsID": "kraken", "type": "isNewVersionOf" }, { "biotoolsID": "bracken", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] } ], "note": null, "cmd": "`kraken2 --db <kraken2_database> <input.fastq>`" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" }, { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" }, { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" } ], "operatingSystem": [], "language": [ "C++", "Perl" ], "license": "MIT", "collectionID": [ "ONTeater" ], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/DerrickWood/kraken2", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/DerrickWood/kraken2/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/DerrickWood/kraken2/archive/v2.0.8-beta.tar.gz", "type": "Source code", "note": null, "version": "2.0.8-beta" } ], "documentation": [ { "url": "https://github.com/DerrickWood/kraken2/wiki/Manual", "type": [ "User manual" ], "note": null }, { "url": "https://benlangmead.github.io/aws-indexes/k2", "type": [ "User manual" ], "note": "Links to multiple Kraken 2 and bracken databases and indexes" } ], "publication": [ { "doi": "10.1101/762302", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Derrick E. Wood", "email": null, "url": null, "orcidid": "http://orcid.org/0000-0002-7429-1854", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Jennifer Lu", "email": null, "url": null, "orcidid": "http://orcid.org/0000-0001-9167-2002", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Ben Langmead", "email": "langmea@cs.jhu.edu", "url": null, "orcidid": "http://orcid.org/0000-0003-2437-1976", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "anand-anshu", "additionDate": "2019-09-13T12:51:16Z", "lastUpdate": "2025-06-18T12:24:26.657325Z", "editPermission": { "type": "group", "authors": [ "vashokan", "Keiler_Collier" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "NextDenovo", "description": "NextDenovo is a string graph-based de novo assembler for long reads (CLR, HiFi and ONT). It uses a \"correct-then-assemble\" strategy similar to canu (no correction step for PacBio Hifi reads), but requires significantly less computing resources and storages.", "homepage": "https://github.com/Nextomics/NextDenovo", "biotoolsID": "nextdenovo", "biotoolsCURIE": "biotools:nextdenovo", "version": [ "v.2.5.2" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0524", "term": "De-novo assembly" }, { "uri": "http://edamontology.org/operation_0525", "term": "Genome assembly" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0924", "term": "Sequence trace" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" }, { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0925", "term": "Sequence assembly" }, "format": [ { "uri": "http://edamontology.org/format_2561", "term": "Sequence assembly format (text)" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" }, { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" } ], "operatingSystem": [], "language": [ "Python", "C" ], "license": "GPL-3.0", "collectionID": [ "ONTeater" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/Nextomics/NextDenovo/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/Nextomics/NextDenovo/releases/tag/2.5.2", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://nextdenovo.readthedocs.io/en/latest/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1101/2023.03.09.531669.", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Nextomics", "email": "support@nextomics.org", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Kigaard", "additionDate": "2021-05-26T21:13:32Z", "lastUpdate": "2025-06-18T12:20:23.607241Z", "editPermission": { "type": "group", "authors": [ "jw", "ELIXIR-CZ", "Keiler_Collier" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "quickmerge", "description": "Quickmerge is a program that uses complementary information from genomes assembled with long reads in order to improve contiguity, and works with assemblies derived from both Pacific Biosciences or Oxford Nanopore. Quickmerge will even work with hybrid assemblies made by combining long reads and Illumina short reads.", "homepage": "https://github.com/mahulchak/quickmerge", "biotoolsID": "quickmerge", "biotoolsCURIE": "biotools:quickmerge", "version": [ "v.0.3" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0525", "term": "Genome assembly" }, { "uri": "http://edamontology.org/operation_3216", "term": "Scaffolding" }, { "uri": "http://edamontology.org/operation_0524", "term": "De-novo assembly" }, { "uri": "http://edamontology.org/operation_3196", "term": "Genotyping" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": "Runs whole merge process on an input assembly.\nAssembly 2 will be used to fill gaps in assembly 1.", "cmd": "merge_wrapper.py -pre output_prefix assembly_1.fa assembly_2.fa" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3175", "term": "Structural variation" }, { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/topic_2885", "term": "DNA polymorphism" }, { "uri": "http://edamontology.org/topic_3673", "term": "Whole genome sequencing" }, { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "C++", "C" ], "license": "GPL-3.0", "collectionID": [ "ONTeater" ], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/mahulchak/quickmerge/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/mahulchak/quickmerge", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1534/g3.118.200162", "pmid": "30018084", "pmcid": "PMC6169397", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Rapid low-cost assembly of the drosophila melanogaster reference genome using low-coverage, long-read sequencing", "abstract": "Accurate and comprehensive characterization of genetic variation is essential for deciphering the genetic basis of diseases and other phenotypes. A vast amount of genetic variation stems from largescale sequence changes arising from the duplication, deletion, inversion, and translocation of sequences. In the past 10 years, high-throughput short reads have greatly expanded our ability to assay sequence variation due to single nucleotide polymorphisms. However, a recent de novo assembly of a second Drosophila melanogaster reference genome has revealed that short read genotyping methods miss hundreds of structural variants, including those affecting phenotypes. While genomes assembled using highcoverage long reads can achieve high levels of contiguity and completeness, concerns about cost, errors, and low yield have limited widespread adoption of such sequencing approaches. Here we resequenced the reference strain of D. melanogaster (ISO1) on a single Oxford Nanopore MinION flow cell run for 24 hr. Using only reads longer than 1 kb or with at least 30x coverage, we assembled a highly contiguous de novo genome. The addition of inexpensive paired reads and subsequent scaffolding using an optical map technology achieved an assembly with completeness and contiguity comparable to the D. melanogaster reference assembly. Comparison of our assembly to the reference assembly of ISO1 uncovered a number of structural variants (SVs), including novel LTR transposable element insertions and duplications affecting genes with developmental, behavioral, and metabolic functions. Collectively, these SVs provide a snapshot of the dynamics of genome evolution. Furthermore, our assembly and comparison to the D. melanogaster reference genome demonstrates that high-quality de novo assembly of reference genomes and comprehensive variant discovery using such assemblies are now possible by a single lab for under $1,000 (USD).", "date": "2018-10-01T00:00:00Z", "citationCount": 70, "authors": [ { "name": "Solares E.A." }, { "name": "Chakraborty M." }, { "name": "Miller D.E." }, { "name": "Kalsow S." }, { "name": "Hall K." }, { "name": "Perera A.G." }, { "name": "Emerson J.J." }, { "name": "Scott Hawley R." } ], "journal": "G3: Genes, Genomes, Genetics" } } ], "credit": [ { "name": "Mahul Chakraborty", "email": null, "url": "https://mahulchakraborty.wordpress.com/", "orcidid": "https://orcid.org/0000-0003-2414-9187", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Kigaard", "additionDate": "2021-05-27T09:04:45Z", "lastUpdate": "2025-06-18T12:17:20.983962Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-CZ", "Keiler_Collier" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "QUAST", "description": "QUAST stands for QUality ASsessment Tool. \nIt evaluates a quality of genome assemblies by computing various metrics and providing nice reports.", "homepage": "http://quast.sourceforge.net/quast", "biotoolsID": "quast", "biotoolsCURIE": "biotools:quast", "version": [ "v.5.3.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_3180", "term": "Sequence assembly validation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [], "note": "# Running quast on a eukaryotic genome", "cmd": "quast -ek assembly.fa --out output_prefix" } ], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Perl", "Python", "C" ], "license": "GPL-2.0", "collectionID": [ "ONTeater" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/ablab/quast", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/ablab/quast/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "http://quast.bioinf.spbau.ru/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btt086", "pmid": "23422339", "pmcid": "PMC3624806", "type": [], "version": null, "note": null, "metadata": { "title": "QUAST: Quality assessment tool for genome assemblies", "abstract": "Limitations of genome sequencing techniques have led to dozens of assembly algorithms, none of which is perfect. A number of methods for comparing assemblers have been developed, but none is yet a recognized benchmark. Further, most existing methods for comparing assemblies are only applicable to new assemblies of finished genomes; the problem of evaluating assemblies of previously unsequenced species has not been adequately considered. Here, we present QUAST - a quality assessment tool for evaluating and comparing genome assemblies. This tool improves on leading assembly comparison software with new ideas and quality metrics. QUAST can evaluate assemblies both with a reference genome, as well as without a reference. QUAST produces many reports, summary tables and plots to help scientists in their research and in their publications. In this study, we used QUAST to compare several genome assemblers on three datasets. QUAST tables and plots for all of them are available in the Supplementary Material, and interactive versions of these reports are on the QUAST website. © 2013 The Author.", "date": "2013-04-15T00:00:00Z", "citationCount": 6872, "authors": [ { "name": "Gurevich A." }, { "name": "Saveliev V." }, { "name": "Vyahhi N." }, { "name": "Tesler G." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "QUAST Support", "email": "quast.support@cab.spbu.ru", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "seqwiki_import", "additionDate": "2017-01-13T13:16:01Z", "lastUpdate": "2025-06-18T11:53:52.861712Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-CZ", "Keiler_Collier" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Racon", "description": "Consensus module for raw de novo DNA assembly of long uncorrected reads\n\nRacon is intended as a standalone consensus module to correct raw contigs generated by rapid assembly methods which do not include a consensus step. The goal of Racon is to generate genomic consensus which is of similar or better quality compared to the output generated by assembly methods which employ both error correction and consensus steps, while providing a speedup of several times compared to those methods. It supports data produced by both Pacific Biosciences and Oxford Nanopore Technologies.", "homepage": "https://github.com/isovic/racon", "biotoolsID": "Racon", "biotoolsCURIE": "biotools:Racon", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0525", "term": "Genome assembly" }, { "uri": "http://edamontology.org/operation_0523", "term": "Mapping assembly" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" }, { "uri": "http://edamontology.org/format_2573", "term": "SAM" } ] }, { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] }, { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": "# The mapping file can be generated with any mapping program - eg, bwa-mem or minimap2.\n# The following is an example using minimap2 with ONT data\nminimap2 assembly.fa-ax map-ont reads.fa > mapped_reads.sam", "cmd": "racon -u reads.fa mapped_reads.sam assembly.fa > assembly_racon.fa" } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3673", "term": "Whole genome sequencing" }, { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "C++", "Python" ], "license": "MIT", "collectionID": [ "ONTeater" ], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/isovic/racon", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/isovic/racon/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.3390/plants8080270", "pmid": "31390788", "pmcid": "PMC6724115", "type": [], "version": null, "note": null, "metadata": { "title": "Constructing a reference genome in a single lab: The possibility to use oxford nanopore technology", "abstract": "The whole genome sequencing (WGS) has become a crucial tool in understanding genome structure and genetic variation. The MinION sequencing of Oxford Nanopore Technologies (ONT) is an excellent approach for performing WGS and it has advantages in comparison with other Next-Generation Sequencing (NGS): It is relatively inexpensive, portable, has simple library preparation, can be monitored in real-time, and has no theoretical limits on reading length. Sorghum bicolor (L.) Moench is diploid (2n = 2x = 20) with a genome size of about 730 Mb, and its genome sequence information is released in the Phytozome database. Therefore, sorghum can be used as a good reference. However, plant species have complex and large genomes when compared to animals or microorganisms. As a result, complete genome sequencing is difficult for plant species. MinION sequencing that produces long-reads can be an excellent tool for overcoming the weak assembly of short-reads generated from NGS by minimizing the generation of gaps or covering the repetitive sequence that appears on the plant genome. Here, we conducted the genome sequencing for S. bicolor cv. BTx623 while using the MinION platform and obtained 895,678 reads and 17.9 gigabytes (Gb) (ca. 25× coverage of reference) from long-read sequence data. A total of 6124 contigs (covering 45.9%) were generated from Canu, and a total of 2661 contigs (covering 50%) were generated from Minimap and Miniasm with a Racon through a de novo assembly using two different tools and mapped assembled contigs against the sorghum reference genome. Our results provide an optimal series of long-read sequencing analysis for plant species while using the MinION platform and a clue to determine the total sequencing scale for optimal coverage that is based on various genome sizes.", "date": "2019-08-01T00:00:00Z", "citationCount": 13, "authors": [ { "name": "Lee Y.G." }, { "name": "Choi S.C." }, { "name": "Kang Y." }, { "name": "Kim K.M." }, { "name": "Kang C.-S." }, { "name": "Kim C." } ], "journal": "Plants" } } ], "credit": [ { "name": "Chon-Sik Kang", "email": "cskang@korea.kr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Changsoo Kim", "email": "changsookim@cnu.ac.kr", "url": null, "orcidid": "https://orcid.org/0000-0002-3596-2934", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "Pub2Tools", "additionDate": "2019-11-14T18:44:38Z", "lastUpdate": "2025-06-18T11:42:42.378216Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Flye", "description": "Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs.", "homepage": "https://github.com/fenderglass/Flye", "biotoolsID": "Flye", "biotoolsCURIE": "biotools:Flye", "version": [ "2.9.6" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0525", "term": "Genome assembly" }, { "uri": "http://edamontology.org/operation_0524", "term": "De-novo assembly" }, { "uri": "http://edamontology.org/operation_0523", "term": "Mapping assembly" }, { "uri": "http://edamontology.org/operation_3730", "term": "Cross-assembly" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3673", "term": "Whole genome sequencing" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "C++", "Python", "C" ], "license": "BSD-3-Clause", "collectionID": [ "ONTeater" ], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/fenderglass/Flye/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/mikolmogorov/Flye", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1099/mgen.0.000294", "pmid": "31483244", "pmcid": "PMC6807382", "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "Comparison of long-read sequencing technologies in the hybrid assembly of complex bacterial genomes", "abstract": "Illumina sequencing allows rapid, cheap and accurate whole genome bacterial analyses, but short reads (<300 bp) do not usually enable complete genome assembly. Long-read sequencing greatly assists with resolving complex bacterial genomes, particularly when combined with short-read Illumina data (hybrid assembly). However, it is not clear how different long-read sequencing methods affect hybrid assembly accuracy. Relative automation of the assembly process is also crucial to facilitating high-throughput complete bacterial genome reconstruction, avoiding multiple bespoke filtering and data manipulation steps. In this study, we compared hybrid assemblies for 20 bacterial isolates, including two reference strains, using Illumina sequencing and long reads from either Oxford Nanopore Technologies (ONT) or SMRT Pacific Biosciences (PacBio) sequencing platforms. We chose isolates from the family Enterobacteriaceae, as these frequently have highly plastic, repetitive genetic structures, and complete genome reconstruction for these species is relevant for a precise understanding of the epidemiology of antimicrobial resistance. We de novo assembled genomes using the hybrid assembler Unicycler and compared different read processing strategies, as well as comparing to long-read-only assembly with Flye followed by short-read polishing with Pilon. Hybrid assembly with either PacBio or ONT reads facilitated high-quality genome reconstruction, and was superior to the longread assembly and polishing approach evaluated with respect to accuracy and completeness. Combining ONT and Illumina reads fully resolved most genomes without additional manual steps, and at a lower consumables cost per isolate in our setting. Automated hybrid assembly is a powerful tool for complete and accurate bacterial genome assembly.", "date": "2019-01-01T00:00:00Z", "citationCount": 166, "authors": [ { "name": "De Maio N." }, { "name": "Shaw L.P." }, { "name": "Hubbard A." }, { "name": "George S." }, { "name": "Sanderson N.D." }, { "name": "Swann J." }, { "name": "Wick R." }, { "name": "Oun M.A." }, { "name": "Stubberfield E." }, { "name": "Hoosdally S.J." }, { "name": "Crook D.W." }, { "name": "Peto T.E.A." }, { "name": "Sheppard A.E." }, { "name": "Bailey M.J." }, { "name": "Read D.S." }, { "name": "Anjum M.F." }, { "name": "Sarah Walker A." }, { "name": "Stoesser N." } ], "journal": "Microbial Genomics" } }, { "doi": "10.1038/s41587-019-0072-8", "pmid": "30936562", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Assembly of long, error-prone reads using repeat graphs", "abstract": "Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here, we present Flye, a long-read assembly algorithm that generates arbitrary paths in an unknown repeat graph, called disjointigs, and constructs an accurate repeat graph from these error-riddled disjointigs. We benchmark Flye against five state-of-the-art assemblers and show that it generates better or comparable assemblies, while being an order of magnitude faster. Flye nearly doubled the contiguity of the human genome assembly (as measured by the NGA50 assembly quality metric) compared with existing assemblers.", "date": "2019-05-01T00:00:00Z", "citationCount": 3077, "authors": [ { "name": "Kolmogorov M." }, { "name": "Yuan J." }, { "name": "Lin Y." }, { "name": "Pevzner P.A." } ], "journal": "Nature Biotechnology" } }, { "doi": "10.1038/s41592-020-00971-x", "pmid": "33020656", "pmcid": "PMC10699202", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "metaFlye: scalable long-read metagenome assembly using repeat graphs", "abstract": "Long-read sequencing technologies have substantially improved the assemblies of many isolate bacterial genomes as compared to fragmented short-read assemblies. However, assembling complex metagenomic datasets remains difficult even for state-of-the-art long-read assemblers. Here we present metaFlye, which addresses important long-read metagenomic assembly challenges, such as uneven bacterial composition and intra-species heterogeneity. First, we benchmarked metaFlye using simulated and mock bacterial communities and show that it consistently produces assemblies with better completeness and contiguity than state-of-the-art long-read assemblers. Second, we performed long-read sequencing of the sheep microbiome and applied metaFlye to reconstruct 63 complete or nearly complete bacterial genomes within single contigs. Finally, we show that long-read assembly of human microbiomes enables the discovery of full-length biosynthetic gene clusters that encode biomedically important natural products.", "date": "2020-11-01T00:00:00Z", "citationCount": 511, "authors": [ { "name": "Kolmogorov M." }, { "name": "Bickhart D.M." }, { "name": "Behsaz B." }, { "name": "Gurevich A." }, { "name": "Rayko M." }, { "name": "Shin S.B." }, { "name": "Kuhn K." }, { "name": "Yuan J." }, { "name": "Polevikov E." }, { "name": "Smith T.P.L." }, { "name": "Pevzner P.A." } ], "journal": "Nature Methods" } } ], "credit": [ { "name": "Mikhail Kolmogorov", "email": "fenderglass@gmail.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Support" ], "note": null }, { "name": "Yu Lin", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jeffrey Yuan", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "Pub2Tools", "additionDate": "2019-11-14T20:08:20Z", "lastUpdate": "2025-06-18T10:20:03.775603Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "BioSimulations", "description": "BioSimulations is a web application for sharing and re-using biomodels, simulations, and visualizations of simulations results. BioSimulations supports a wide range of modeling frameworks (e.g., kinetic, constraint-based, and logical modeling), model formats (e.g., BNGL, CellML, SBML), and simulation tools (e.g., COPASI, libRoadRunner/tellurium, NFSim, VCell). BioSimulations aims to help researchers discover published models that might be useful for their research and quickly try them via a simple web-based interface.", "homepage": "https://www.biosimulations.org/", "biotoolsID": "biosimulations", "biotoolsCURIE": "biotools:biosimulations", "version": [], "otherID": [ { "value": "RRID:SCR_018733", "type": "rrid", "version": null } ], "relation": [ { "biotoolsID": "runbiosimulations", "type": "uses" }, { "biotoolsID": "biosimulators", "type": "uses" }, { "biotoolsID": "biomodels", "type": "uses" }, { "biotoolsID": "sbml", "type": "uses" }, { "biotoolsID": "bionetgen", "type": "uses" }, { "biotoolsID": "cobrapy", "type": "uses" }, { "biotoolsID": "copasi", "type": "uses" }, { "biotoolsID": "libroadrunner", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0950", "term": "Mathematical model" }, "format": [ { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "uri": "http://edamontology.org/format_3240", "term": "CellML" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3870", "term": "Trajectory data" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_3604", "term": "SVG" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Web API", "Web application", "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" }, { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" } ], "operatingSystem": [], "language": [ "JavaScript", "Python" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/reproducible-biomedical-modeling/Biosimulations/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/reproducible-biomedical-modeling/Biosimulations", "type": [ "Repository" ], "note": null }, { "url": "https://api.biosimulations.org/", "type": [ "Service" ], "note": null } ], "download": [], "documentation": [ { "url": "https://docs.biosimulations.org", "type": [ "General" ], "note": null }, { "url": "https://api.biosimulations.org/", "type": [ "API documentation" ], "note": null }, { "url": "https://docs.biosimulations.org/developers/conduct/", "type": [ "Code of conduct" ], "note": null }, { "url": "https://docs.biosimulations.org/about/terms/", "type": [ "Terms of use" ], "note": null } ], "publication": [], "credit": [ { "name": "Jonathan Karr", "email": "karr@mssm.edu", "url": "https://www.karrlab.org", "orcidid": "https://orcid.org/0000-0002-2605-5080", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Bilal Shaikh", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-5801-5510", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "Bioinfo", "additionDate": "2020-06-18T05:28:02Z", "lastUpdate": "2025-06-17T16:32:28.548746Z", "editPermission": { "type": "group", "authors": [ "bilalshaikh42", "Bioinfo" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Bracken", "description": "Bracken is a companion program to Kraken 1, KrakenUniq, or Kraken 2 While Kraken classifies reads to multiple levels in the taxonomic tree, Bracken allows estimation of abundance at a single level using those classifications (e.g. Bracken can estimate abundance of species within a sample).", "homepage": "https://ccb.jhu.edu/software/bracken/", "biotoolsID": "bracken", "biotoolsCURIE": "biotools:bracken", "version": [], "otherID": [], "relation": [ { "biotoolsID": "kraken2", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" } ], "operatingSystem": [ "Linux" ], "language": [ "Perl", "Python" ], "license": "GPL-3.0", "collectionID": [ "Animal and Crop Genomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/jenniferlu717/Bracken", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/jenniferlu717/Bracken/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://ccb.jhu.edu/software/bracken/index.shtml?t=manual", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.7717/peerj-cs.104", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Bracken: Estimating species abundance in metagenomics data", "abstract": "Metagenomic experiments attempt to characterize microbial communities using high-throughput DNA sequencing. Identification of the microorganisms in a sample provides information about the genetic profile, population structure, and role of microorganisms within an environment. Until recently, most metagenomics studies focused on high-level characterization at the level of phyla, or alternatively sequenced the 16S ribosomalRNAgene that is present in bacterial species. As the cost of sequencing has fallen, though, metagenomics experiments have increasingly used unbiased shotgun sequencing to capture all the organisms in a sample. This approach requires a method for estimating abundance directly from the raw read data. Here we describe a fast, accurate new method that computes the abundance at the species level using the reads collected in a metagenomics experiment. Bracken (Bayesian Reestimation of Abundance after Classification with KrakEN) uses the taxonomic assignments made by Kraken, a very fast read-level classifier, along with information about the genomes themselves to estimate abundance at the species level, the genus level, or above. We demonstrate that Bracken can produce accurate species- and genus-level abundance estimates even when a sample contains multiple near-identical species.", "date": "2017-01-01T00:00:00Z", "citationCount": 1084, "authors": [ { "name": "Lu J." }, { "name": "Breitwieser F.P." }, { "name": "Thielen P." }, { "name": "Salzberg S.L." } ], "journal": "PeerJ Computer Science" } } ], "credit": [ { "name": null, "email": "jlu26@jhmi.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "admin", "additionDate": "2017-08-20T15:17:20Z", "lastUpdate": "2025-06-11T12:25:29.118910Z", "editPermission": { "type": "group", "authors": [ "animalandcropgenomics", "ELIXIR-CZ", "bebatut", "vashokan" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "pyM2aia", "description": "pyM²aia is a Python package for memory-efficient access and processing of mass spectrometry image data. The I/O functionality is derived from the interactive desktop application M²aia. Special features are the batch generator utilities for deep learning applications.", "homepage": "https://m2aia.de/pym2aia.html", "biotoolsID": "pym2aia", "biotoolsCURIE": "biotools:pym2aia", "version": [], "otherID": [], "relation": [ { "biotoolsID": "m2aia", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3435", "term": "Standardisation and normalisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" } ] }, { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" } ] }, { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" }, { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python", "C++" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/m2aia/pym2aia", "type": [ "Issue tracker", "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/m2aia/pym2aia", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://data.jtfc.de/pym2aia/sphinx-build/html/index.html", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/gigascience/giab049", "pmid": "34282451", "pmcid": "PMC8290197", "type": [], "version": null, "note": "Cordes J; Enzlein T; Marsching C; Hinze M; Engelhardt S; Hopf C; Wolf I (July, 2021): M²aia - Interactive, fast and memory efficient analysis of 2D and 3D multi-modal mass spectrometry imaging data https://doi.org/10.1093/gigascience/giab049", "metadata": { "title": "M2aia-Interactive, fast, and memory-efficient analysis of 2D and 3D multi-modal mass spectrometry imaging data", "abstract": "Background: Mass spectrometry imaging (MSI) is a label-free analysis method for resolving bio-molecules or pharmaceuticals in the spatial domain. It offers unique perspectives for the examination of entire organs or other tissue specimens. Owing to increasing capabilities of modern MSI devices, the use of 3D and multi-modal MSI becomes feasible in routine applications-resulting in hundreds of gigabytes of data. To fully leverage such MSI acquisitions, interactive tools for 3D image reconstruction, visualization, and analysis are required, which preferably should be open-source to allow scientists to develop custom extensions. Findings: We introduce M2aia (MSI applications for interactive analysis in MITK), a software tool providing interactive and memory-efficient data access and signal processing of multiple large MSI datasets stored in imzML format. M2aia extends MITK, a popular open-source tool in medical image processing. Besides the steps of a typical signal processing workflow, M2aia offers fast visual interaction, image segmentation, deformable 3D image reconstruction, and multi-modal registration. A unique feature is that fused data with individual mass axes can be visualized in a shared coordinate system. We demonstrate features of M2aia by reanalyzing an N-glycan mouse kidney dataset and 3D reconstruction and multi-modal image registration of a lipid and peptide dataset of a mouse brain, which we make publicly available. Conclusions: To our knowledge, M2aia is the first extensible open-source application that enables a fast, user-friendly, and interactive exploration of large datasets. M2aia is applicable to a wide range of MSI analysis tasks.", "date": "2021-07-01T00:00:00Z", "citationCount": 17, "authors": [ { "name": "Cordes J." }, { "name": "Enzlein T." }, { "name": "Marsching C." }, { "name": "Hinze M." }, { "name": "Engelhardt S." }, { "name": "Hopf C." }, { "name": "Wolf I." } ], "journal": "GigaScience" } } ], "credit": [ { "name": "Jonas Cordes", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-3148-4282", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "jtfc", "additionDate": "2023-08-30T09:06:30.320364Z", "lastUpdate": "2025-06-05T12:19:20.571346Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MALDIquant", "description": "MALDIquant is a complete analysis pipeline for matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass spectrometry data. In addition to commonly used plotting and processing methods it includes distinctive features, namely baseline subtraction methods such as morphological filters (TopHat) or the statistics-sensitive non-linear iterative peak-clipping algorithm (SNIP), peak alignment using warping functions, handling of replicated measurements as well as allowing spectra with different resolutions.", "homepage": "https://cran.r-project.org/package=MALDIquant", "biotoolsID": "maldi_quant", "biotoolsCURIE": "biotools:maldi_quant", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3799", "term": "Quantification" }, { "uri": "http://edamontology.org/operation_3860", "term": "Spectrum calculation" }, { "uri": "http://edamontology.org/operation_3215", "term": "Peak detection" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" } ] }, { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" } ] }, { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [ { "uri": "http://edamontology.org/format_3603", "term": "PNG" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3627", "term": "Mass spectra calibration" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" } ] }, { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" } ] }, { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library", "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/sgibb/MALDIquant/", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/sgibb/MALDIquant/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "http://strimmerlab.org/software/maldiquant/", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [ { "url": "https://cran.r-project.org/web/packages/MALDIquant/MALDIquant.pdf", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/bts447", "pmid": "22796955", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Maldiquant: A versatile R package for the analysis of mass spectrometry data", "abstract": "MALDIquant is an R package providing a complete and modular analysis pipeline for quantitative analysis of mass spectrometry data. MALDIquant is specifically designed with application in clinical diagnostics in mind and implements sophisticated routines for importing raw data, preprocessing, non-linear peak alignment and calibration. It also handles technical replicates as well as spectra with unequal resolution. © The Author 2012. Published by Oxford University Press. All rights reserved.", "date": "2012-09-01T00:00:00Z", "citationCount": 499, "authors": [ { "name": "Gibb S." }, { "name": "Strimmer K." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Sebastian Gibb", "email": "mail@sebastiangibb.de", "url": null, "orcidid": "https://orcid.org/0000-0001-7406-4443", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer" ], "note": null }, { "name": "Korbinian Strimmer", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-7917-2056", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "Kigaard", "additionDate": "2021-05-26T20:42:18Z", "lastUpdate": "2025-06-05T11:28:57.497366Z", "editPermission": { "type": "group", "authors": [ "sizhengZhao" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "AMICI", "description": "AMICI provides a multi-language (Python, C++, Matlab) interface for the SUNDIALS solvers CVODES (for ordinary differential equations) and IDAS (for algebraic differential equations). AMICI allows the user to read differential equation models specified as SBML or PySB and automatically compiles such models into .mex simulation files (Matlab), C++ executables or Python modules.\n\nBeyond forward integration, the compiled simulation file also allows for forward sensitivity analysis, steady state sensitivity analysis and adjoint sensitivity analysis for likelihood-based output functions.\n\nThe interface was designed to provide routines for efficient gradient computation in parameter estimation of biochemical reaction models but it is also applicable to a wider range of differential equation constrained optimization problems.", "homepage": "https://github.com/AMICI-dev/AMICI", "biotoolsID": "AMICI", "biotoolsCURIE": "biotools:AMICI", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3562", "term": "Network simulation" }, { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2600", "term": "Pathway or network" }, "format": [ { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "uri": "http://edamontology.org/format_4015", "term": "PEtab" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3870", "term": "Trajectory data" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "MATLAB", "C++", "Python" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/AMICI-dev/AMICI/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://amici.readthedocs.io/en/latest/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btab227", "pmid": "33821950", "pmcid": "PMC8545331", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "AMICI: high-performance sensitivity analysis for large ordinary differential equation models", "abstract": "Ordinary differential equation models facilitate the understanding of cellular signal transduction and other biological processes. However, for large and comprehensive models, the computational cost of simulating or calibrating can be limiting. AMICI is a modular toolbox implemented in C++/Python/MATLAB that provides efficient simulation and sensitivity analysis routines tailored for scalable, gradient-based parameter estimation and uncertainty quantification.", "date": "2021-10-15T00:00:00Z", "citationCount": 37, "authors": [ { "name": "Frohlich F." }, { "name": "Weindl D." }, { "name": "Schalte Y." }, { "name": "Pathirana D." }, { "name": "Paszkowski L." }, { "name": "Lines G.T." }, { "name": "Stapor P." }, { "name": "Hasenauer J." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Fabian Fröhlich", "email": "fabian_froehlich@hms.harvard.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer", "Developer" ], "note": null }, { "name": "Jan Hasenauer", "email": "jan.hasenauer@uni-bonn.de", "url": null, "orcidid": "https://orcid.org/0000-0002-4935-3312", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Daniel Weindl", "email": "daniel.weindl@uni-bonn.de", "url": null, "orcidid": "https://orcid.org/0000-0001-9963-6057", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer", "Developer" ], "note": null } ], "owner": "dweindl", "additionDate": "2019-09-28T12:06:10Z", "lastUpdate": "2025-05-08T07:28:52.817175Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "pyOpenMS", "description": "Python library for mass spectrometry, specifically for the analysis of proteomics and metabolomics data.", "homepage": "https://github.com/OpenMS/pyopenms-extra/blob/master/docs/source/index.rst", "biotoolsID": "pyOpenMS", "biotoolsCURIE": "biotools:pyOpenMS", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0601", "term": "Protein modifications" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/OpenMS/pyopenms-extra", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/OpenMS/pyopenms-extra/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://pyopenms.readthedocs.io", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.7287/PEERJ.PREPRINTS.27736", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Hannes L. Rost", "email": "hannes.rost@utoronto.ca", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "samwein", "additionDate": "2019-08-09T13:16:33Z", "lastUpdate": "2025-04-30T11:39:29.549782Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Gemma", "description": "Gemma provides data, experimental design annotations, and differential expression analysis results for thousands of microarray and RNA-seq experiments. We re-analyze raw data from public sources (primarily NCBI GEO), annotate experimental conditions, conduct quality control and compute differential expression using standardized procedures. We have especially good coverage of experiments relevant to the nervous system.", "homepage": "https://gemma.msl.ubc.ca/", "biotoolsID": "gemma", "biotoolsCURIE": "biotools:gemma", "version": [ "1.31.13" ], "otherID": [], "relation": [ { "biotoolsID": "rsem", "type": "uses" }, { "biotoolsID": "multiqc", "type": "uses" }, { "biotoolsID": "cutadapt", "type": "uses" }, { "biotoolsID": "star", "type": "uses" }, { "biotoolsID": "ncbi_geo", "type": "uses" }, { "biotoolsID": "sradb", "type": "uses" }, { "biotoolsID": "ncbi_gene", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3223", "term": "Differential gene expression profiling" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3112", "term": "Gene expression matrix" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3110", "term": "Raw microarray data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1636", "term": "Heat map" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3914", "term": "Quality control report" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web API" ], "topic": [ { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_3053", "term": "Genetics" }, { "uri": "http://edamontology.org/topic_3518", "term": "Microarray experiment" }, { "uri": "http://edamontology.org/topic_0219", "term": "Data curation and archival" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java", "JavaScript" ], "license": "CC-BY-NC-4.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/PavlidisLab/Gemma", "type": [ "Repository", "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/PavlidisLab/Gemma/releases", "type": "Downloads page", "note": null, "version": null } ], "documentation": [ { "url": "https://pavlidislab.github.io/Gemma/", "type": [ "General" ], "note": null }, { "url": "https://gemma.msl.ubc.ca/resources/restapidocs/", "type": [ "API documentation" ], "note": "Documentation for the Gemma REST API." } ], "publication": [ { "doi": "10.1093/bioinformatics/btp259", "pmid": "19376825", "pmcid": "PMC2687992", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Application and evaluation of automated semantic annotation of gene expression experiments", "abstract": "Motivation: Many microarray datasets are available online with formalized standards describing the probe sequences and expression values. Unfortunately, the description, conditions and parameters of the experiments are less commonly formalized and often occur as natural language text. This hinders searching, high-throughput analysis, organization and integration of the datasets. Results: We use the lexical resources and software tools from the Unified Medical Language System (UMLS) to extract concepts from text. We then link the UMLS concepts to classes in open biomedical ontologies. The result is accessible and clear semantic annotations of gene expression experiments. We applied the method to 595 expression experiments from Gemma, a resource for re-use and meta-analysis of gene expression profiling data. We evaluated and corrected all stages of the annotation process. The majority of missed annotations were due to a lack of cross-references. The most error-prone stage was the extraction of concepts from phrases. Final review of the annotations in context of the experiments revealed 89% precision. A naive system, lacking the phrase to concept corrections is 68% precise. We have integrated this annotation pipeline into Gemma. © 2009 The Author(s).", "date": "2009-06-09T00:00:00Z", "citationCount": 9, "authors": [ { "name": "French L." }, { "name": "Lane S." }, { "name": "Law T." }, { "name": "Xu L." }, { "name": "Pavlidis P." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/database/baab006", "pmid": "33599246", "pmcid": "PMC7904053", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Curation of over 10 000 transcriptomic studies to enable data reuse", "abstract": "Vast amounts of transcriptomic data reside in public repositories, but effective reuse remains challenging. Issues include unstructured dataset metadata, inconsistent data processing and quality control, and inconsistent probe-gene mappings across microarray technologies. Thus, extensive curation and data reprocessing are necessary prior to any reuse. The Gemma bioinformatics system was created to help address these issues. Gemma consists of a database of curated transcriptomic datasets, analytical software, a web interface and web services. Here we present an update on Gemma's holdings, data processing and analysis pipelines, our curation guidelines, and software features. As of June 2020, Gemma contains 10 811 manually curated datasets (primarily human, mouse and rat), over 395 000 samples and hundreds of curated transcriptomic platforms (both microarray and RNA sequencing). Dataset topics were represented with 10 215 distinct terms from 12 ontologies, for a total of 54 316 topic annotations (mean topics/dataset = 5.2). While Gemma has broad coverage of conditions and tissues, it captures a large majority of available brain-related datasets, accounting for 34% of its holdings. Users can access the curated data and differential expression analyses through the Gemma website, RESTful service and an R package. Database URL: https://gemma.msl.ubc.ca/home.html", "date": "2021-01-01T00:00:00Z", "citationCount": 21, "authors": [ { "name": "Lim N." }, { "name": "Tesar S." }, { "name": "Belmadani M." }, { "name": "Poirier-Morency G." }, { "name": "Mancarci B.O." }, { "name": "Sicherman J." }, { "name": "Jacobson M." }, { "name": "Leong J." }, { "name": "Tan P." }, { "name": "Pavlidis P." } ], "journal": "Database" } } ], "credit": [ { "name": "Pavlidis Lab Support", "email": "pavlab-support@msl.ubc.ca", "url": "https://pavlab.msl.ubc.ca/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Support" ], "note": null } ], "owner": "artrymix", "additionDate": "2017-04-22T17:35:18Z", "lastUpdate": "2025-04-22T22:09:03.811075Z", "editPermission": { "type": "group", "authors": [ "artrymix", "paulpavlidis" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Protists Ribosomal Reference Database", "description": "The PR2 reference sequence database was initiated in 2010 in the frame of the BioMarks project from work that had developed in the previous ten years in the Plankton Group of the Station Biologique of Roscoff. It aims to provide a reference database of carefully annotated 18S rRNA sequences using nine unique taxonomic fields (from domain to species). At present, it contains over 240,000 sequences. Although it focuses on protists, it also contains sequences from metazoa, fungi and plants as well a limited set of 16S sequences from plastids and bacteria. Several metadata fields are available for many sequences, including geo-localisation, whether it originates from a culture or a natural sample, host type etc… The annotation of PR2 is performed by experts from each taxonomic groups.", "homepage": "https://app.pr2-database.org/", "biotoolsID": "pr2-reference", "biotoolsCURIE": "biotools:pr2-reference", "version": [ "5.1.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Database portal", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_4038", "term": "Metabarcoding" } ], "operatingSystem": [], "language": [ "R" ], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/pr2database/pr2database/releases", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/pr2database/pr2database/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://pr2-database.org/", "type": [ "Other" ], "note": null } ], "download": [ { "url": "https://github.com/pr2database/pr2database/releases", "type": "Downloads page", "note": null, "version": "5.1.0" } ], "documentation": [ { "url": "https://pr2database.github.io/pr2database/articles/pr2database.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gks1160", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The Protist Ribosomal Reference database (PR2): A catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy", "abstract": "The interrogation of genetic markers in environmental meta-barcoding studies is currently seriously hindered by the lack of taxonomically curated reference data sets for the targeted genes. The Protist Ribosomal Reference database (PR2, http://ssu-rrna.org/) provides a unique access to eukaryotic small sub-unit (SSU) ribosomal RNA and DNA sequences, with curated taxonomy. The database mainly consists of nuclear-encoded protistan sequences. However, metazoans, land plants, macrosporic fungi and eukaryotic organelles (mitochondrion, plastid and others) are also included because they are useful for the analysis of high-troughput sequencing data sets. Introns and putative chimeric sequences have been also carefully checked. Taxonomic assignation of sequences consists of eight unique taxonomic fields. In total, 136866 sequences are nuclear encoded, 45708 (36 501 mitochondrial and 9657 chloroplastic) are from organelles, the remaining being putative chimeric sequences. The website allows the users to download sequences from the entire and partial databases (including representative sequences after clustering at a given level of similarity). Different web tools also allow searches by sequence similarity. The presence of both rRNA and rDNA sequences, taking into account introns (crucial for eukaryotic sequences), a normalized eight terms ranked-taxonomy and updates of new GenBank releases were made possible by a long-term collaboration between experts in taxonomy and computer scientists. © The Author(s) 2012.", "date": "2013-01-01T00:00:00Z", "citationCount": 1456, "authors": [ { "name": "Guillou L." }, { "name": "Bachar D." }, { "name": "Audic S." }, { "name": "Bass D." }, { "name": "Berney C." }, { "name": "Bittner L." }, { "name": "Boutte C." }, { "name": "Burgaud G." }, { "name": "De Vargas C." }, { "name": "Decelle J." }, { "name": "Del Campo J." }, { "name": "Dolan J.R." }, { "name": "Dunthorn M." }, { "name": "Edvardsen B." }, { "name": "Holzmann M." }, { "name": "Kooistra W.H.C.F." }, { "name": "Lara E." }, { "name": "Le Bescot N." }, { "name": "Logares R." }, { "name": "Mahe F." }, { "name": "Massana R." }, { "name": "Montresor M." }, { "name": "Morard R." }, { "name": "Not F." }, { "name": "Pawlowski J." }, { "name": "Probert I." }, { "name": "Sauvadet A.-L." }, { "name": "Siano R." }, { "name": "Stoeck T." }, { "name": "Vaulot D." }, { "name": "Zimmermann P." }, { "name": "Christen R." } ], "journal": "Nucleic Acids Research" } } ], "credit": [], "owner": "vaulot", "additionDate": "2025-04-11T13:56:02.037873Z", "lastUpdate": "2025-04-11T14:01:09.249274Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null } ] }