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{ "count": 1979, "next": "?page=2", "previous": null, "list": [ { "name": "DataDiscovery", "description": "DataDiscovery aims at providing researchers a simple and fast access to relevant biological data using specific keywords and easy to use filters.\n\nThis tool is expected to be easily customizable for specific filters, environments, or data schemas. Its current implementations supported by URGI are: WheatIS, Plant, RARe.", "homepage": "https://urgi.versailles.inrae.fr/data-discovery/", "biotoolsID": "DataDiscovery", "biotoolsCURIE": "biotools:DataDiscovery", "version": [], "otherID": [], "relation": [ { "biotoolsID": "wheatis", "type": "usedBy" }, { "biotoolsID": "RARe", "type": "usedBy" }, { "biotoolsID": "Plant_DataDiscovery", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" }, { "uri": "http://edamontology.org/operation_3625", "term": "Relation extraction" }, { "uri": "http://edamontology.org/operation_0227", "term": "Indexing" }, { "uri": "http://edamontology.org/operation_3908", "term": "Information retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0968", "term": "Keyword" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2353", "term": "Ontology data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2093", "term": "Data reference" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0842", "term": "Identifier" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web API", "Web application", "Web service", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_0610", "term": "Ecology" }, { "uri": "http://edamontology.org/topic_3071", "term": "Biological databases" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3810", "term": "Agricultural science" } ], "operatingSystem": [ "Linux" ], "language": [ "JavaScript", "Java", "Bash" ], "license": "BSD-3-Clause", "collectionID": [ "elixir-fr-sdp-2019", "URGI" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Data", "Tools", "Interoperability" ], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [ { "url": "https://forgemia.inra.fr/urgi-is/data-discovery", "type": [ "Repository" ], "note": "GitLab code repository for DataDiscovery" }, { "url": "https://github.com/gnpis/DataDiscovery/", "type": [ "Mirror" ], "note": "Code repository mirror link for DataDiscovery" } ], "download": [], "documentation": [ { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/LEGAL-MENTIONS.md", "type": [ "Terms of use" ], "note": "General terms of use" }, { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/README.md#contribute", "type": [ "Contributions policy" ], "note": "How to contribute" }, { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/HELP.md", "type": [ "User manual" ], "note": "How to use" }, { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/README.md#setup", "type": [ "Installation instructions" ], "note": "How to install" } ], "publication": [ { "doi": "10.3835/plantgenome2015.06.0038", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": "1-\tSpannagl, M., Alaux, M., Lange, M., Bolser, D. M., Bader, K. C., Letellier, T., Kimmel, E., Flores, R.-G., Pommier, C., Kerhornou, A., Walts, B., Nussbaumer, T., Grabmuller, C., Chen, J., Colmsee, C., Beier, S., Mascher, M., Schmutzer, T., Arend, D., Thanki, A., Ramirez-Gonzalez, R., Ayling, M., Ayling, S., Caccamo, M., Mayer, K. F. X., Scholz, U., Steinbach, D., Quesneville, H., Kersey, P. (2016). TransPLANT resources for triticeae genomic data. Plant Genome, 9 (1), 13 p.", "metadata": { "title": "TransPLANT resources for triticeae genomic data", "abstract": "The genome sequences of many important Triticeae species, including bread wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), remained uncharacterized for a long time because their high repeat content, large sizes, and polyploidy. As a result of improvements in sequencing technologies and novel analyses strategies, several of these have recently been deciphered. These efforts have generated new insights into Triticeae biology and genome organization and have important implications for downstream usage by breeders, experimental biologists, and comparative genomicists. transPLANT (http://www.transplantdb.eu) is an EU-funded project aimed at constructing hardware, software, and data infrastructure for genome-scale research in the life sciences. Since the Triticeae data are intrinsically complex, heterogenous, and distributed, the transPLANT consortium has undertaken efforts to develop common data formats and tools that enable the exchange and integration of data from distributed resources. Here we present an overview of the individual Triticeae genome resources hosted by transPLANT partners, introduce the objectives of transPLANT, and outline common developments and interfaces supporting integrated data access.", "date": "2016-03-01T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Spannagl M." }, { "name": "Alaux M." }, { "name": "Lange M." }, { "name": "Bolser D.M." }, { "name": "Bader K.C." }, { "name": "Letellier T." }, { "name": "Kimmel E." }, { "name": "Flores R." }, { "name": "Pommier C." }, { "name": "Kerhornou A." }, { "name": "Walts B." }, { "name": "Nussbaumer T." }, { "name": "Grabmuller C." }, { "name": "Chen J." }, { "name": "Colmsee C." }, { "name": "Beier S." }, { "name": "Mascher M." }, { "name": "Schmutzer T." }, { "name": "Arend D." }, { "name": "Thanki A." }, { "name": "Ramirez-Gonzalez R." }, { "name": "Ayling M." }, { "name": "Ayling S." }, { "name": "Caccamo M." }, { "name": "Mayer K.F.X." }, { "name": "Scholz U." }, { "name": "Steinbach D." }, { "name": "Quesneville H." }, { "name": "Kersey P.J." } ], "journal": "Plant Genome" } }, { "doi": "10.1038/hortres.2016.56", "pmid": null, "pmcid": null, "type": [], "version": null, "note": "2-\tAdam-Blondon, A.-F., Alaux, M., Pommier, C., Cantu, D., Cheng, Z.-M., Cramer, G. R., Davies, C., Delrot, S., Deluc, L., di Gaspero, G., Grimplet, J., Fennell, A., Londo, J. P., Kersey, P., Mattivi, F., Naithani, S., Neveu, P., Nikolski, M., Pezzotti, M., Reisch, B. I., Topfer, R., Vivier, M., Ware, D., Quesneville, H. (2016). Towards an open grapevine information system. Horticulture Research, 3, 8 p. , DOI : 10.1038/hortres.2016.56", "metadata": { "title": "Towards an open grapevine information system", "abstract": "Viticulture, like other fields of agriculture, is currently facing important challenges that will be addressed only through sustained, dedicated and coordinated research. Although the methods used in biology have evolved tremendously in recent years and now involve the routine production of large data sets of varied nature, in many domains of study, including grapevine research, there is a need to improve the findability, accessibility, interoperability and reusability (FAIR-ness) of these data. Considering the heterogeneous nature of the data produced, the transnational nature of the scientific community and the experience gained elsewhere, we have formed an open working group, in the framework of the International Grapevine Genome Program (www.vitaceae.org), to construct a coordinated federation of information systems holding grapevine data distributed around the world, providing an integrated set of interfaces supporting advanced data modeling, rich semantic integration and the next generation of data mining tools. To achieve this goal, it will be critical to develop, implement and adopt appropriate standards for data annotation and formatting. The development of this system, the GrapeIS, linking genotypes to phenotypes, and scientific research to agronomical and oeneological data, should provide new insights into grape biology, and allow the development of new varieties to meet the challenges of biotic and abiotic stress, environmental change, and consumer demand.", "date": "2016-11-23T00:00:00Z", "citationCount": 37, "authors": [ { "name": "Adam-Blondon A.-F." }, { "name": "Alaux M." }, { "name": "Pommier C." }, { "name": "Cantu D." }, { "name": "Cheng Z.-M." }, { "name": "Cramer G." }, { "name": "Davies C." }, { "name": "Delrot S." }, { "name": "Deluc L." }, { "name": "Di Gaspero G." }, { "name": "Grimplet J." }, { "name": "Fennell A." }, { "name": "Londo J." }, { "name": "Kersey P." }, { "name": "Mattivi F." }, { "name": "Naithani S." }, { "name": "Neveu P." }, { "name": "Nikolski M." }, { "name": "Pezzotti M." }, { "name": "Reisch B." }, { "name": "Topfer R." }, { "name": "Vivier M." }, { "name": "Ware D." }, { "name": "Quesneville H." } ], "journal": "Horticulture Research" } }, { "doi": "10.1186/s13059-018-1491-4", "pmid": null, "pmcid": null, "type": [], "version": null, "note": "3-\tAlaux M, Rogers J, Letellier T, Flores R, Alfama F, Pommier C, Mohellibi N, Durand S, Kimmel E, Michotey C, Guerche C, Loaec M, Lainé M, Steinbach D, Choulet F, Rimbert H, Leroy P, Guilhot N, Salse J, Feuillet C, International Wheat Genome Sequencing Consortium, Paux E, Eversole K, Adam-Blondon A-F, Quesneville H (2018) Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data. Genome Biology, 19:111.", "metadata": { "title": "Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data", "abstract": "The Wheat@URGI portal has been developed to provide the international community of researchers and breeders with access to the bread wheat reference genome sequence produced by the International Wheat Genome Sequencing Consortium. Genome browsers, BLAST, and InterMine tools have been established for in-depth exploration of the genome sequence together with additional linked datasets including physical maps, sequence variations, gene expression, and genetic and phenomic data from other international collaborative projects already stored in the GnpIS information system. The portal provides enhanced search and browser features that will facilitate the deployment of the latest genomics resources in wheat improvement.", "date": "2018-08-17T00:00:00Z", "citationCount": 181, "authors": [ { "name": "Alaux M." }, { "name": "Rogers J." }, { "name": "Letellier T." }, { "name": "Flores R." }, { "name": "Alfama F." }, { "name": "Pommier C." }, { "name": "Mohellibi N." }, { "name": "Durand S." }, { "name": "Kimmel E." }, { "name": "Michotey C." }, { "name": "Guerche C." }, { "name": "Loaec M." }, { "name": "Laine M." }, { "name": "Steinbach D." }, { "name": "Choulet F." }, { "name": "Rimbert H." }, { "name": "Leroy P." }, { "name": "Guilhot N." }, { "name": "Salse J." }, { "name": "Feuillet C." }, { "name": "Paux E." }, { "name": "Eversole K." }, { "name": "Adam-Blondon A.-F." }, { "name": "Quesneville H." } ], "journal": "Genome Biology" } } ], "credit": [ { "name": "urgi-support", "email": "urgi-support@inrae.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact", "Support" ], "note": null } ], "community": null, "owner": "nfrancillon", "additionDate": "2020-01-21T16:40:38Z", "lastUpdate": "2024-09-06T15:57:35.550435Z", "editPermission": { "type": "group", "authors": [ "urgi-contact", "cpommier", "cmichotey", "erlefloch", "raphael.flores" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "FAIDARE", "description": "FAIDARE: FAIR Data-finder for Agronomic Research. \nThe purpose of this portal is to facilitate the discoverability of public data on plant biology from a federation of established data repositories.\n\nIt is based on the Breeding API (BrAPI) specifications and facilitates the access to genotype and phenotype datasets for crop and forest plants through an easy to use web interface. It also provides a standard interface that can be accessed programatically through web services.\n\nIt is an extension of the generic DataDiscovery portal, a web portal that allows finding any type of data across several databases through a lightweight keyword based search. FAIDARE offers more detailed search and data retrieval capabilities and it takes advantage of the growing adoption of the BrAPI.", "homepage": "https://urgi.versailles.inrae.fr/faidare/", "biotoolsID": "faidare", "biotoolsCURIE": "biotools:faidare", "version": [], "otherID": [], "relation": [ { "biotoolsID": "gnpis", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" }, { "uri": "http://edamontology.org/operation_3559", "term": "Ontology visualisation" }, { "uri": "http://edamontology.org/operation_3625", "term": "Relation extraction" }, { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_0227", "term": "Indexing" }, { "uri": "http://edamontology.org/operation_3908", "term": "Information retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0968", "term": "Keyword" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2353", "term": "Ontology data" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0842", "term": "Identifier" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1188", "term": "DOI" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3720", "term": "Geographic location" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0842", "term": "Identifier" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [ { "uri": "http://edamontology.org/format_3620", "term": "xlsx" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_2093", "term": "Data reference" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web API", "Web application", "Database portal", "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_3810", "term": "Agricultural science" }, { "uri": "http://edamontology.org/topic_0610", "term": "Ecology" }, { "uri": "http://edamontology.org/topic_3071", "term": "Biological databases" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Linux" ], "language": [ "JavaScript", "Java", "Bash" ], "license": "BSD-3-Clause", "collectionID": [ "URGI", "elixir-fr-sdp-2019" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools", "Data", "Interoperability" ], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [ { "url": "https://forgemia.inra.fr/urgi-is/faidare", "type": [ "Repository" ], "note": "GitLab code repository for FAIDARE" }, { "url": "https://github.com/elixir-europe/plant-faidare", "type": [ "Mirror" ], "note": "Code repository mirror link for FAIDARE" } ], "download": [], "documentation": [ { "url": "https://urgi.versailles.inrae.fr/faidare/swagger-ui.html", "type": [ "API documentation" ], "note": "Description of the API to access FAIDARE webservice following BRAPI API" }, { "url": "https://forgemia.inra.fr/urgi-is/faidare/blob/master/CONTRIBUTING.md", "type": [ "Contributions policy" ], "note": "How to contribute to FAIDARE software development" }, { "url": "https://urgi.versailles.inrae.fr/faidare/help", "type": [ "User manual" ], "note": "Tips to use the application" }, { "url": "https://urgi.versailles.inrae.fr/faidare/legal", "type": [ "Terms of use" ], "note": null }, { "url": "https://forgemia.inra.fr/urgi-is/faidare/blob/master/README.md", "type": [ "Installation instructions" ], "note": null }, { "url": "https://urgi.versailles.inrae.fr/faidare/join", "type": [ "Contributions policy" ], "note": "How to join the FAIDARE federation" } ], "publication": [], "credit": [ { "name": "URGI support", "email": "urgi-support@inrae.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact", "Support" ], "note": null } ], "community": null, "owner": "nfrancillon", "additionDate": "2020-01-20T16:46:02Z", "lastUpdate": "2024-09-02T05:04:34.812991Z", "editPermission": { "type": "group", "authors": [ "cpommier", "urgi-contact", "cmichotey", "raphael.flores" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MAGMA", "description": "The MAGMA pipeline for comprehensive genomic analyses of clinical Mycobacterium tuberculosis samples", "homepage": "https://github.com/TORCH-Consortium/MAGMA", "biotoolsID": "magma-pipeline", "biotoolsCURIE": "biotools:magma-pipeline", "version": [], "otherID": [], "relation": [ { "biotoolsID": "XBS", "type": "includes" } ], "function": [], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [], "language": [ "Groovy", "Java", "Python" ], "license": "GPL-3.0", "collectionID": [ "Mycobacterium tuberculosis" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/TORCH-Consortium/MAGMA/discussions", "type": [ "Discussion forum" ], "note": "MAGMA pipeline discussion forum" }, { "url": "https://github.com/TORCH-Consortium/MAGMA/issues", "type": [ "Issue tracker" ], "note": "MAGMA pipeline issue tracker" } ], "download": [ { "url": "https://github.com/TORCH-Consortium/MAGMA/releases/tag/v2.0.0", "type": "Source code", "note": "The source code for v2.0.0 release", "version": "v2.0.0" }, { "url": "https://zenodo.org/record/8054182", "type": "Other", "note": "Reference EXIT-RIF GVCF", "version": null } ], "documentation": [ { "url": "https://torch-consortium.github.io/MAGMA/usage.html", "type": [ "User manual" ], "note": "The documentation website for MAGMA pipeline. The main focus is upon usage and interpretation of outputs." } ], "publication": [ { "doi": "10.1371/journal.pcbi.1011648", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "The MAGMA pipeline for comprehensive genomic analyses of clinical Mycobacterium tuberculosis samples", "abstract": "Background Whole genome sequencing (WGS) holds great potential for the management and control of tuberculosis. Accurate analysis of samples with low mycobacterial burden, which are characterized by low (<20x) coverage and high (>40%) levels of contamination, is challenging. We created the MAGMA (Maximum Accessible Genome for Mtb Analysis) bioinformatics pipeline for analysis of clinical Mtb samples. Methods and results High accuracy variant calling is achieved by using a long seedlength during read mapping to filter out contaminants, variant quality score recalibration with machine learning to identify genuine genomic variants, and joint variant calling for low Mtb coverage genomes. MAGMA automatically generates a standardized and comprehensive output of drug resistance information and resistance classification based on the WHO catalogue of Mtb mutations. MAGMA automatically generates phylogenetic trees with drug resistance annotations and trees that visualize the presence of clusters. Drug resistance and phylogeny outputs from sequencing data of 79 primary liquid cultures were compared between the MAGMA and MTBseq pipelines. The MTBseq pipeline reported only a proportion of the variants in candidate drug resistance genes that were reported by MAGMA. Notable differences were in structural variants, variants in highly conserved rrs and rrl genes, and variants in candidate resistance genes for bedaquiline, clofazmine, and delamanid. Phylogeny results were similar between pipelines but only MAGMA visualized clusters. Conclusion The MAGMA pipeline could facilitate the integration of WGS into clinical care as it generates clinically relevant data on drug resistance and phylogeny in an automated, standardized, and reproducible manner.", "date": "2023-11-01T00:00:00Z", "citationCount": 4, "authors": [ { "name": "Heupink T.H." }, { "name": "Verboven L." }, { "name": "Sharma A." }, { "name": "Rennie V." }, { "name": "Fuertes M.D.D." }, { "name": "Warren R.M." }, { "name": "Van Rie A." } ], "journal": "PLoS Computational Biology" } }, { "doi": "10.1099/mgen.0.000689", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Comprehensive and accurate genetic variant identification from contaminated and low-coverage Mycobacterium tuberculosis whole genome sequencing data", "abstract": "Improved understanding of the genomic variants that allow Mycobacterium tuberculosis (Mtb) to acquire drug resistance, or tol-erance, and increase its virulence are important factors in controlling the current tuberculosis epidemic. Current approaches to Mtb sequencing, however, cannot reveal Mtb’s full genomic diversity due to the strict requirements of low contamination levels, high Mtb sequence coverage and elimination of complex regions. We have developed the XBS (compleX Bacterial Samples) bio-informatics pipeline, which implements joint calling and machine-learning-based variant filtering tools to specifically improve variant detection in the important Mtb samples that do not meet these criteria, such as those from unbiased sputum samples. Using novel simulated datasets, which permit exact accuracy verification, XBS was compared to the UVP and MTBseq pipelines. Accuracy statistics showed that all three pipelines performed equally well for sequence data that resemble those obtained from culture isolates of high depth of coverage and low-level contamination. In the complex genomic regions, however, XBS accurately identified 9.0 % more SNPs and 8.1 % more single nucleotide insertions and deletions than the WHO-endorsed unified analysis variant pipeline. XBS also had superior accuracy for sequence data that resemble those obtained directly from sputum samples, where depth of coverage is typically very low and contamination levels are high. XBS was the only pipeline not affected by low depth of coverage (5–10×), type of contamination and excessive contamination levels (>50 %). Simulation results were confirmed using whole genome sequencing (WGS) data from clinical samples, confirming the superior performance of XBS with a higher sensitivity (98.8%) when analysing culture isolates and identification of 13.9 % more variable sites in WGS data from sputum samples as compared to MTBseq, without evidence for false positive variants when rRNA regions were excluded. The XBS pipeline facilitates sequencing of less-than-perfect Mtb samples. These advances will benefit future clinical applications of Mtb sequencing, especially WGS directly from clinical specimens, thereby avoiding in vitro biases and making many more samples available for drug resistance and other genomic analyses. The additional genetic resolution and increased sample success rate will improve genome-wide association studies and sequence-based transmission studies.", "date": "2021-01-01T00:00:00Z", "citationCount": 13, "authors": [ { "name": "Heupink T.H." }, { "name": "Verboven L." }, { "name": "Warren R.M." }, { "name": "Van Rie A." } ], "journal": "Microbial Genomics" } } ], "credit": [ { "name": "Tim Heupink", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-6237-3898", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Lennert Verboven", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-5647-5852", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Abhinav Sharma", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-6402-6993", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Vincent Rennie", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-1031-2441", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Miguel de Diego Fuertes", "email": null, "url": "https://torch-consortium.com/migiel", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Robin Warren", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-5741-7358", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Annelies Van Rie", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-7666-3263", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "community": null, "owner": "abhi18av", "additionDate": "2024-08-28T09:09:21.326316Z", "lastUpdate": "2024-08-28T09:42:42.984756Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "APE", "description": "APE (the Automated Pipeline Explorer) as a command-line tool and API for automated composition of scientific workflows. APE is easily configured to a new application domain by providing it with a domain ontology and semantically annotated tools. It can then be used to synthesize purpose-specific workflows based on a specification of the available workflow inputs, desired outputs and possibly additional constraints.", "homepage": "https://github.com/sanctuuary/APE/", "biotoolsID": "ape", "biotoolsCURIE": "biotools:ape", "version": [ "2.1.7" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3429", "term": "Generation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0949", "term": "Workflow metadata" }, "format": [ { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0949", "term": "Workflow metadata" }, "format": [ { "uri": "http://edamontology.org/format_3857", "term": "CWL" }, { "uri": "http://edamontology.org/format_3603", "term": "PNG" }, { "uri": "http://edamontology.org/format_3604", "term": "SVG" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library", "Web API" ], "topic": [ { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" }, { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Java" ], "license": "Apache-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/sanctuuary/ape", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://mvnrepository.com/artifact/io.github.sanctuuary/APE/2.1.7", "type": "Software package", "note": "Download APE java library or the CLI", "version": "2.1.7" } ], "documentation": [ { "url": "https://ape-framework.readthedocs.io/", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1007/978-3-030-50436-6_34", "pmid": null, "pmcid": "PMC7304703", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Ape: A command-line tool and api for automated workflow composition", "abstract": "Automated workflow composition is bound to take the work with scientific workflows to the next level. On top of today’s comprehensive eScience infrastructure, it enables the automated generation of possible workflows for a given specification. However, functionality for automated workflow composition tends to be integrated with one of the many available workflow management systems, and is thus difficult or impossible to apply in other environments. Therefore we have developed APE (the Automated Pipeline Explorer) as a command-line tool and API for automated composition of scientific workflows. APE is easily configured to a new application domain by providing it with a domain ontology and semantically annotated tools. It can then be used to synthesize purpose-specific workflows based on a specification of the available workflow inputs, desired outputs and possibly additional constraints. The workflows can further be transformed into executable implementations and/or exported into standard workflow formats. In this paper we describe APE v1.0 and discuss lessons learned from applications in bioinformatics and geosciences.", "date": "2020-01-01T00:00:00Z", "citationCount": 12, "authors": [ { "name": "Kasalica V." }, { "name": "Lamprecht A.-L." } ], "journal": "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)" } }, { "doi": "10.1021/ACS.JPROTEOME.0C00983", "pmid": "33720735", "pmcid": "PMC8041394", "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "APE in the Wild: Automated Exploration of Proteomics Workflows in the bio.tools Registry", "abstract": "The bio.tools registry is a main catalogue of computational tools in the life sciences. More than 17 000 tools have been registered by the international bioinformatics community. The bio.tools metadata schema includes semantic annotations of tool functions, that is, formal descriptions of tools' data types, formats, and operations with terms from the EDAM bioinformatics ontology. Such annotations enable the automated composition of tools into multistep pipelines or workflows. In this Technical Note, we revisit a previous case study on the automated composition of proteomics workflows. We use the same four workflow scenarios but instead of using a small set of tools with carefully handcrafted annotations, we explore workflows directly on bio.tools. We use the Automated Pipeline Explorer (APE), a reimplementation and extension of the workflow composition method previously used. Moving \"into the wild\"opens up an unprecedented wealth of tools and a huge number of alternative workflows. Automated composition tools can be used to explore this space of possibilities systematically. Inevitably, the mixed quality of semantic annotations in bio.tools leads to unintended or erroneous tool combinations. However, our results also show that additional control mechanisms (tool filters, configuration options, and workflow constraints) can effectively guide the exploration toward smaller sets of more meaningful workflows.", "date": "2021-04-02T00:00:00Z", "citationCount": 7, "authors": [ { "name": "Kasalica V." }, { "name": "Schwammle V." }, { "name": "Palmblad M." }, { "name": "Ison J." }, { "name": "Lamprecht A.-L." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Vedran Kasalica", "email": "v.kasalica@esciencecenter.nl", "url": null, "orcidid": "https://orcid.org/0000-0002-0097-1056", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Anna-Lena Lamprecht", "email": "anna-lena.lamprecht@uni-potsdam.de", "url": null, "orcidid": "https://orcid.org/0000-0003-1953-5606", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "VKasalica", "additionDate": "2021-01-18T10:10:48Z", "lastUpdate": "2024-08-26T12:57:24.763845Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "OpenChrom", "description": "Open source tool for mass spectrometry and chromatography.", "homepage": "https://www.openchrom.net/", "biotoolsID": "openchrom", "biotoolsCURIE": "biotools:openchrom", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3203", "term": "Chromatogram visualisation" }, { "uri": "http://edamontology.org/operation_3214", "term": "Spectral analysis" }, { "uri": "http://edamontology.org/operation_3629", "term": "Deisotoping" }, { "uri": "http://edamontology.org/operation_2424", "term": "Comparison" }, { "uri": "http://edamontology.org/operation_3695", "term": "Filtering" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" }, { "uri": "http://edamontology.org/operation_3215", "term": "Peak detection" }, { "uri": "http://edamontology.org/operation_3694", "term": "Mass spectrum visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrometry spectra" }, "format": [ { "uri": "http://edamontology.org/format_1637", "term": "dat" }, { "uri": "http://edamontology.org/format_3712", "term": "Thermo RAW" }, { "uri": "http://edamontology.org/format_3654", "term": "mzXML" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3650", "term": "netCDF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0944", "term": "Peptide mass fingerprint" }, "format": [ { "uri": "http://edamontology.org/format_3620", "term": "xlsx" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_3650", "term": "netCDF" }, { "uri": "http://edamontology.org/format_3244", "term": "mzML" } ] }, { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" }, { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java" ], "license": null, "collectionID": [ "ms-utils", "Proteomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://ms-utils.org", "type": [ "Software catalogue" ], "note": null } ], "download": [ { "url": "https://sourceforge.net/projects/openchrom/", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://sourceforge.net/p/openchrom/wiki/Home/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": null, "pmid": "20673335", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "OpenChrom: A cross-platform open source software for the mass spectrometric analysis of chromatographic data", "abstract": "Background: Today, data evaluation has become a bottleneck in chromatographic science. Analytical instruments equipped with automated samplers yield large amounts of measurement data, which needs to be verified and analyzed. Since nearly every GC/MS instrument vendor offers its own data format and software tools, the consequences are problems with data exchange and a lack of comparability between the analytical results. To challenge this situation a number of either commercial or non-profit software applications have been developed. These applications provide functionalities to import and analyze several data formats but have shortcomings in terms of the transparency of the implemented analytical algorithms and/or are restricted to a specific computer platform.Results: This work describes a native approach to handle chromatographic data files. The approach can be extended in its functionality such as facilities to detect baselines, to detect, integrate and identify peaks and to compare mass spectra, as well as the ability to internationalize the application. Additionally, filters can be applied on the chromatographic data to enhance its quality, for example to remove background and noise. Extended operations like do, undo and redo are supported.Conclusions: OpenChrom is a software application to edit and analyze mass spectrometric chromatographic data. It is extensible in many different ways, depending on the demands of the users or the analytical procedures and algorithms. It offers a customizable graphical user interface. The software is independent of the operating system, due to the fact that the Rich Client Platform is written in Java. OpenChrom is released under the Eclipse Public License 1.0 (EPL). There are no license constraints regarding extensions. They can be published using open source as well as proprietary licenses. OpenChrom is available free of charge at http://www.openchrom.net. © 2010 Wenig and Odermatt; licensee BioMed Central Ltd.", "date": "2010-07-30T00:00:00Z", "citationCount": 87, "authors": [ { "name": "Wenig P." }, { "name": "Odermatt J." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Philip Wenig", "email": "philip.wenig@gmx.net", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null }, { "name": null, "email": "webmaster@ms-utils.org", "url": "http://ms-utils.org", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Documentor" ], "note": null } ], "community": null, "owner": "msutils_import", "additionDate": "2017-01-17T14:50:39Z", "lastUpdate": "2024-08-21T06:18:20.181329Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools", "Mailaender", "n.m.palmblad@lumc.nl" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Sirius", "description": "Tool for metabolite identification using mass spectrometry.", "homepage": "http://bio.informatik.uni-jena.de/sirius", "biotoolsID": "sirius", "biotoolsCURIE": "biotools:sirius", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3553", "term": "Image annotation" }, { "uri": "http://edamontology.org/operation_3694", "term": "Mass spectrum visualisation" }, { "uri": "http://edamontology.org/operation_3803", "term": "Natural product identification" }, { "uri": "http://edamontology.org/operation_3632", "term": "Isotopic distributions calculation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0944", "term": "Peptide mass fingerprint" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_3651", "term": "MGF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0846", "term": "Chemical formula" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] }, { "data": { "uri": "http://edamontology.org/data_0944", "term": "Peptide mass fingerprint" }, "format": [ { "uri": "http://edamontology.org/format_3579", "term": "JPG" }, { "uri": "http://edamontology.org/format_3603", "term": "png" }, { "uri": "http://edamontology.org/format_3467", "term": "GIF" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java" ], "license": null, "collectionID": [ "ms-utils", "Proteomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://ms-utils.org", "type": [ "Software catalogue" ], "note": null } ], "download": [ { "url": "https://github.com/boecker-lab/sirius_frontend", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://bio.informatik.uni-jena.de/sirius-training/", "type": [ "Training material" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btn603", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "SIRIUS: Decomposing isotope patterns for metabolite identification", "abstract": "Motivation: High-resolution mass spectrometry (MS) is among the most widely used technologies in metabolomics. Metabolites participate in almost all cellular processes, but most metabolites still remain uncharacterized. Determination of the sum formula is a crucial step in the identification of an unknown metabolite, as it reduces its possible structures to a hopefully manageable set. Results: We present a method for determining the sum formula of a metabolite solely from its mass and the natural distribution of its isotopes. Our input is a measured isotope pattern from a high resolution mass spectrometer, and we want to find those molecules that best match this pattern. Our method is computationally efficient, and results on experimental data are very promising: for orthogonal time-of-flight mass spectrometry, we correctly identify sum formulas for >90% of the molecules, ranging in mass up to 1000 Da. © 2008 The Author(s).", "date": "2009-01-01T00:00:00Z", "citationCount": 187, "authors": [ { "name": "Bocker S." }, { "name": "Letzel M.C." }, { "name": "Liptak Z." }, { "name": "Pervukhin A." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Sebastian Boecker", "email": "sebastian.boecker@uni-jena.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null }, { "name": null, "email": "webmaster@ms-utils.org", "url": "http://ms-utils.org", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Documentor" ], "note": null } ], "community": null, "owner": "msutils_import", "additionDate": "2017-01-17T14:50:43Z", "lastUpdate": "2024-08-21T06:17:56.704263Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools", "n.m.palmblad@lumc.nl" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "TBtools", "description": "An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data.", "homepage": "https://github.com/CJ-Chen/TBtools/releases", "biotoolsID": "tbtools", "biotoolsCURIE": "biotools:tbtools", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2409", "term": "Data handling" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" }, { "uri": "http://edamontology.org/topic_0623", "term": "Gene and protein families" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [], "language": [ "Java" ], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1016/J.MOLP.2020.06.009", "pmid": "32585190", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data", "abstract": "© 2020 The AuthorTBtools, a stand-alone bioinformatics software with a user-friendly interface is presented in this study. The toolkit incorporates over 130 functions, which are designed to meet the increasing demand for big-data analyses, ranging from bulk sequence processing to interactive data visualization. Its robustness has been validated by tens of thousands of users, making it a handy and useful toolkit for biologists. © 2020 The AuthorThe rapid development of high-throughput sequencing techniques has led biology into the big-data era. Data analyses using various bioinformatics tools rely on programming and command-line environments, which are challenging and time-consuming for most wet-lab biologists. Here, we present TBtools (a Toolkit for Biologists integrating various biological data-handling tools), a stand-alone software with a user-friendly interface. The toolkit incorporates over 130 functions, which are designed to meet the increasing demand for big-data analyses, ranging from bulk sequence processing to interactive data visualization. A wide variety of graphs can be prepared in TBtools using a new plotting engine (“JIGplot”) developed to maximize their interactive ability; this engine allows quick point-and-click modification of almost every graphic feature. TBtools is platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer. It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases.", "date": "2020-08-03T00:00:00Z", "citationCount": 735, "authors": [ { "name": "Chen C." }, { "name": "Chen H." }, { "name": "Zhang Y." }, { "name": "Thomas H.R." }, { "name": "Frank M.H." }, { "name": "He Y." }, { "name": "Xia R." } ], "journal": "Molecular Plant" } } ], "credit": [], "community": null, "owner": "tienangou", "additionDate": "2021-01-18T09:32:49Z", "lastUpdate": "2024-08-21T06:17:26.650275Z", "editPermission": { "type": "group", "authors": [ "Ryan", "februadi", "Jaskirat" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "MSFragger", "description": "A database search tool for performing mass spectometry data similarity comparisons. 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We present a fragment-ion indexing method, and its implementation in peptide identification tool MSFragger, that enables a more than 100-fold improvement in speed over most existing proteome database search tools. Using several large proteomic data sets, we demonstrate how MSFragger empowers the open database search concept for comprehensive identification of peptides and all their modified forms, uncovering dramatic differences in modification rates across experimental samples and conditions. We further illustrate its utility using protein-RNA cross-linked peptide data and using affinity purification experiments where we observe, on average, a 300% increase in the number of identified spectra for enriched proteins. 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