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            "name": "CarrotOmics",
            "description": "CarrotOmics is an integrated web-based relational database, developed to house and integrate genomic, genetic and breeding data for carrot and related species. CarrotOmics includes genome assemblies, annotated transcripts, traits, maps, and markers being generated and used by carrot researchers.",
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                            "term": "Genome assembly"
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                            "term": "Genetic mapping"
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                            "uri": "http://edamontology.org/operation_0526",
                            "term": "EST assembly"
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                            "term": "Database search"
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                    "term": "Mapping"
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                    "term": "Sequence assembly"
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                    "term": "Genotype and phenotype"
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                    "uri": "http://edamontology.org/topic_3293",
                    "term": "Phylogenetics"
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                    "term": "DNA polymorphism"
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            "documentation": [
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                    "url": "https://www.carrotomics.org/userManual",
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                        "General"
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            "publication": [
                {
                    "doi": "10.1093/DATABASE/BAAC079",
                    "pmid": "36069936",
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                    "metadata": {
                        "title": "CarrotOmics: a genetics and comparative genomics database for carrot (Daucus carota)",
                        "abstract": "Published by Oxford University Press 2022. This work is written by (a) US Government employee(s) and is in the public domain in the US.CarrotOmics (https://carrotomics.org/) is a comprehensive database for carrot (Daucus carota L.) breeding and research. CarrotOmics was developed using resources available at the MainLab Bioinformatics core (https://www.bioinfo.wsu.edu/) and is implemented using Tripal with Drupal modules. The database delivers access to download or visualize the carrot reference genome with gene predictions, gene annotations and sequence assembly. Other genomic resources include information for 11 224 genetic markers from 73 linkage maps or genotyping-by-sequencing and descriptions of 371 mapped loci. There are records for 1601 Apiales species (or subspecies) and descriptions of 9408 accessions from 11 germplasm collections representing more than 600 of these species. Additionally, 204 Apiales species have phenotypic information, totaling 28 517 observations from 10 041 biological samples. Resources on CarrotOmics are freely available, search functions are provided to find data of interest and video tutorials are available to describe the search functions and genomic tools. CarrotOmics is a timely resource for the Apiaceae research community and for carrot geneticists developing improved cultivars with novel traits addressing challenges including an expanding acreage in tropical climates, an evolving consumer interested in sustainably grown vegetables and a dynamic environment due to climate change. Data from CarrotOmics can be applied in genomic-assisted selection and genetic research to improve basic research and carrot breeding efficiency. DATABASE URL: https://carrotomics.org/.",
                        "date": "2022-09-07T00:00:00Z",
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                        "authors": [
                            {
                                "name": "Rolling W.R."
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                            },
                            {
                                "name": "Ellison S."
                            },
                            {
                                "name": "Van Deynze A."
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                            {
                                "name": "Simon P.W."
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                        "journal": "Database : the journal of biological databases and curation"
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                    "name": "Philipp W Simon",
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        {
            "name": "TASSEL",
            "description": "Software package to evaluate traits associations, evolutionary patterns, and linkage disequilibrium.",
            "homepage": "http://www.maizegenetics.net/tassel",
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                            "term": "Linkage analysis"
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                            "term": "Linkage disequilibrium calculation"
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                    "term": "GWAS study"
                },
                {
                    "uri": "http://edamontology.org/topic_0102",
                    "term": "Mapping"
                }
            ],
            "operatingSystem": [
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                "Windows",
                "Mac"
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            "language": [
                "Java"
            ],
            "license": "LGPL-2.1",
            "collectionID": [
                "Animal and Crop Genomics"
            ],
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                    "doi": "10.1093/bioinformatics/btm308",
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                    "metadata": {
                        "title": "TASSEL: Software for association mapping of complex traits in diverse samples",
                        "abstract": "Summary: Association analyses that exploit the natural diversity of a genome to map at very high resolutions are becoming increasingly important. In most studies, however, researchers must contend with the confounding effects of both population and family structure. TASSEL (Trait Analysis by aSSociation, Evolution and Linkage) implements general linear model and mixed linear model approaches for controlling population and family structure. For result interpretation, the program allows for linkage disequilibrium statistics to be calculated and visualized graphically. Database browsing and data importation is facilitated by integrated middleware. Other features include analyzing insertions/deletions, calculating diversity statistics, integration of phenotypic and genotypic data, imputing missing data and calculating principal components. © 2007 The Author(s).",
                        "date": "2007-10-01T00:00:00Z",
                        "citationCount": 3227,
                        "authors": [
                            {
                                "name": "Bradbury P.J."
                            },
                            {
                                "name": "Zhang Z."
                            },
                            {
                                "name": "Kroon D.E."
                            },
                            {
                                "name": "Casstevens T.M."
                            },
                            {
                                "name": "Ramdoss Y."
                            },
                            {
                                "name": "Buckler E.S."
                            }
                        ],
                        "journal": "Bioinformatics"
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        {
            "name": "Genome Database for Rosaceae (GDR)",
            "description": "Contains all publically available Rosaceae sequences including annotated peach, strawberry and almond EST sequences and the genetically anchored peach physical map.",
            "homepage": "http://www.rosaceae.org/",
            "biotoolsID": "gdr",
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                            "uri": "http://edamontology.org/operation_2429",
                            "term": "Mapping"
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                            "uri": "http://edamontology.org/operation_2871",
                            "term": "Sequence tagged site (STS) mapping"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0282",
                            "term": "Genetic mapping"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0526",
                            "term": "EST assembly"
                        },
                        {
                            "uri": "http://edamontology.org/operation_2944",
                            "term": "Physical mapping"
                        }
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                    "input": [],
                    "output": [],
                    "note": null,
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            ],
            "toolType": [
                "Database portal"
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            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0102",
                    "term": "Mapping"
                },
                {
                    "uri": "http://edamontology.org/topic_3512",
                    "term": "Gene transcripts"
                },
                {
                    "uri": "http://edamontology.org/topic_2885",
                    "term": "DNA polymorphism"
                },
                {
                    "uri": "http://edamontology.org/topic_3318",
                    "term": "Physics"
                },
                {
                    "uri": "http://edamontology.org/topic_0199",
                    "term": "Genetic variation"
                }
            ],
            "operatingSystem": [
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                "Windows",
                "Mac"
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            "language": [
                "Perl"
            ],
            "license": null,
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            "documentation": [
                {
                    "url": "https://www.rosaceae.org/userManual",
                    "type": [
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                    "note": null
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            ],
            "publication": [
                {
                    "doi": null,
                    "pmid": "15357877",
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                    "type": [],
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                    "metadata": {
                        "title": "GDR (Genome Database for Rosaceae): Integrated web resources for Rosaceae genomics and genetics research",
                        "abstract": "Background: Peach is being developed as a model organism for Rosaceae, an economically important family that includes fruits and ornamental plants such as apple, pear, strawberry, cherry, almond and rose. The genomics and genetics data of peach can play a significant role in the gene discovery and the genetic understanding of related species. The effective utilization of these peach resources, however, requires the development of an integrated and centralized database with associated analysis tools. Description: The Genome Database for Rosaceae (GDR) is a curated and integrated web-based relational database. GDR contains comprehensive data of the genetically anchored peach physical map, an annotated peach EST database, Rosaceae maps and markers and all publicly available Rosaceae sequences. Annotations of ESTs include contig assembly, putative function, simple sequence repeats, and anchored position to the peach physical map where applicable. Our integrated map viewer provides graphical interface to the genetic, transcriptome and physical mapping information. ESTs, BACs and markers can be queried by various categories and the search result sites are linked to the integrated map viewer or to the WebFPC physical map sites. In addition to browsing and querying the database, users can compare their sequences with the annotated GDR sequences via a dedicated sequence similarity server running either the BLAST or FASTA algorithm. To demonstrate the utility of the integrated and fully annotated database and analysis tools, we describe a case study where we anchored Rosaceae sequences to the peach physical and genetic map by sequence similarity. Conclusions: The GDR has been initiated to meet the major deficiency in Rosaceae genomics and genetics research, namely a centralized web database and bioinformatics tools for data storage, analysis and exchange. GDR can be accessed at http://www.genome.clemson.edu/gdr/. © 2004 Jung et al; licensee BioMed Central Ltd.",
                        "date": "2004-09-09T00:00:00Z",
                        "citationCount": 75,
                        "authors": [
                            {
                                "name": "Jung S."
                            },
                            {
                                "name": "Jesudurai C."
                            },
                            {
                                "name": "Staton M."
                            },
                            {
                                "name": "Du Z."
                            },
                            {
                                "name": "Ficklin S."
                            },
                            {
                                "name": "Cho I."
                            },
                            {
                                "name": "Abbott A."
                            },
                            {
                                "name": "Tomkins J."
                            },
                            {
                                "name": "Main D."
                            }
                        ],
                        "journal": "BMC Bioinformatics"
                    }
                },
                {
                    "doi": null,
                    "pmid": "17932055",
                    "pmcid": null,
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "GDR (Genome Database for Rosaceae): Integrated web-database for Rosaceae genomics and genetics data",
                        "abstract": "The Genome Database for Rosaceae (GDR) is a central repository of curated and integrated genetics and genomics data of Rosaceae, an economically important family which includes apple, cherry, peach, pear, raspberry, rose and strawberry. GDR contains annotated databases of all publicly available Rosaceae ESTs, the genetically anchored peach physical map, Rosaceae genetic maps and comprehensively annotated markers and traits. The ESTs are assembled to produce unigene sets of each genus and the entire Rosaceae. Other annotations include putative function, microsatellites, open reading frames, single nucleotide polymorphisms, gene ontology terms and anchored map position where applicable. Most of the published Rosaceae genetic maps can be viewed and compared through CMap, the comparative map viewer. The peach physical map can be viewed using WebFPC/WebChrom, and also through our integrated GDR map viewer, which serves as a portal to the combined genetic, transcriptome and physical mapping information. ESTs, BACs, markers and traits can be queried by various categories and the search result sites are linked to the mapping visualization tools. GDR also provides online analysis tools such as a batch BLAST/FASTA server for the GDR datasets, a sequence assembly server and microsatellite and primer detection tools. GDR is available at http://www.rosaceae.org. © 2007 The Author(s).",
                        "date": "2008-01-01T00:00:00Z",
                        "citationCount": 161,
                        "authors": [
                            {
                                "name": "Jung S."
                            },
                            {
                                "name": "Staton M."
                            },
                            {
                                "name": "Lee T."
                            },
                            {
                                "name": "Blenda A."
                            },
                            {
                                "name": "Svancara R."
                            },
                            {
                                "name": "Abbott A."
                            },
                            {
                                "name": "Main D."
                            }
                        ],
                        "journal": "Nucleic Acids Research"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Contact Form",
                    "email": null,
                    "url": "https://www.rosaceae.org/contact",
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                    "typeEntity": "Person",
                    "typeRole": [
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                    ],
                    "note": null
                }
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            "community": null,
            "owner": "ELIXIR-EE",
            "additionDate": "2017-03-30T21:27:31Z",
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        },
        {
            "name": "FunMappOne",
            "description": "User-friendly graphical interface that allows to visualize and summarize the functional annotations of one or multiple molecular biology experiments at once.",
            "homepage": "https://github.com/Greco-Lab/FunMappOne",
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                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3501",
                            "term": "Enrichment analysis"
                        },
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                            "uri": "http://edamontology.org/operation_3432",
                            "term": "Clustering"
                        },
                        {
                            "uri": "http://edamontology.org/operation_2495",
                            "term": "Expression analysis"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Desktop application"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0602",
                    "term": "Molecular interactions, pathways and networks"
                },
                {
                    "uri": "http://edamontology.org/topic_0089",
                    "term": "Ontology and terminology"
                },
                {
                    "uri": "http://edamontology.org/topic_0621",
                    "term": "Model organisms"
                }
            ],
            "operatingSystem": [
                "Linux",
                "Windows",
                "Mac"
            ],
            "language": [
                "R"
            ],
            "license": "GPL-3.0",
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            "maturity": "Mature",
            "cost": "Free of charge",
            "accessibility": "Open access",
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            "elixirNode": [],
            "elixirCommunity": [],
            "link": [
                {
                    "url": "https://github.com/Greco-Lab/FunMappOne/issues",
                    "type": [
                        "Issue tracker"
                    ],
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            ],
            "download": [],
            "documentation": [
                {
                    "url": "https://usermanual.wiki/Document/UserManual.999755866.pdf",
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            ],
            "publication": [
                {
                    "doi": "10.1186/s12859-019-2639-2",
                    "pmid": "30767762",
                    "pmcid": "PMC6376640",
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                    "metadata": {
                        "title": "FunMappOne: A tool to hierarchically organize and visually navigate functional gene annotations in multiple experiments",
                        "abstract": "© 2019 The Author(s).Background: Functional annotation of genes is an essential step in omics data analysis. Multiple databases and methods are currently available to summarize the functions of sets of genes into higher level representations, such as ontologies and molecular pathways. Annotating results from omics experiments into functional categories is essential not only to understand the underlying regulatory dynamics but also to compare multiple experimental conditions at a higher level of abstraction. Several tools are already available to the community to represent and compare functional profiles of omics experiments. However, when the number of experiments and/or enriched functional terms is high, it becomes difficult to interpret the results even when graphically represented. Therefore, there is currently a need for interactive and user-friendly tools to graphically navigate and further summarize annotations in order to facilitate results interpretation also when the dimensionality is high. Results: We developed an approach that exploits the intrinsic hierarchical structure of several functional annotations to summarize the results obtained through enrichment analyses to higher levels of interpretation and to map gene related information at each summarized level. We built a user-friendly graphical interface that allows to visualize the functional annotations of one or multiple experiments at once. The tool is implemented as a R-Shiny application called FunMappOne and is available at https://github.com/grecolab/FunMappOne. Conclusion: FunMappOne is a R-shiny graphical tool that takes in input multiple lists of human or mouse genes, optionally along with their related modification magnitudes, computes the enriched annotations from Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, or Reactome databases, and reports interactive maps of functional terms and pathways organized in rational groups. FunMappOne allows a fast and convenient comparison of multiple experiments and an easy way to interpret results.",
                        "date": "2019-02-15T00:00:00Z",
                        "citationCount": 17,
                        "authors": [
                            {
                                "name": "Scala G."
                            },
                            {
                                "name": "Serra A."
                            },
                            {
                                "name": "Marwah V.S."
                            },
                            {
                                "name": "Saarimaki L.A."
                            },
                            {
                                "name": "Greco D."
                            }
                        ],
                        "journal": "BMC Bioinformatics"
                    }
                }
            ],
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            "owner": "Ruta",
            "additionDate": "2019-05-19T09:00:19Z",
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        {
            "name": "mineXpert",
            "description": "mineXpert is a graphical user interface software piece that allows the user to:\n- load mass spectrometry data files [ (x,y) text files or mzML standard format ] \n- visualize the TIC chromatogram and the intensity=(mz, dt) colormap in case of ion mobility mass spectrometry\n- integrate the mass data in many different ways and display them, effectively permitting the exploration of the mass data in their full depth\n- many other features",
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            "biotoolsID": "mineXpert",
            "biotoolsCURIE": "biotools:mineXpert",
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                    "value": "doi:10.1021/acs.jproteome.9b00099",
                    "type": "doi",
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                    "operation": [
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                            "uri": "http://edamontology.org/operation_3203",
                            "term": "Chromatogram visualisation"
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                            "uri": "http://edamontology.org/operation_3694",
                            "term": "Mass spectrum visualisation"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3632",
                            "term": "Isotopic distributions calculation"
                        }
                    ],
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                                "uri": "http://edamontology.org/data_2536",
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                    "output": [
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                            "data": {
                                "uri": "http://edamontology.org/data_2884",
                                "term": "Plot"
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                    "note": null,
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            ],
            "toolType": [
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                "Desktop application"
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            "topic": [
                {
                    "uri": "http://edamontology.org/topic_3292",
                    "term": "Biochemistry"
                },
                {
                    "uri": "http://edamontology.org/topic_3370",
                    "term": "Analytical chemistry"
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                    "uri": "http://edamontology.org/topic_3332",
                    "term": "Computational chemistry"
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                        "title": "MineXpert: Biological Mass Spectrometry Data Visualization and Mining with Full JavaScript Ability",
                        "abstract": "© Copyright 2019 American Chemical Society.Biological mass spectrometry mainly comprises three fields of endeavor, namely, proteomics, metabolomics, and structural biology. In each of these specialties, the mass spectrometrist needs to access MS1 mass spectral data, although not necessarily on the same basis. For example, the bottom-up proteomics scientist will occasionally access MS1 data to perform data inspection, quality assessments, and quantitation measurements, whereas top-down proteomics, structural biology, or metabolomics scientists will actually spend most of their time mining profile-mode MS1 data. Furthermore, the advent of ion mobility-mass spectrometry imposes new manners of mass spectral data visualization. An open-source MS1-only mass data visualization software for the desktop was developed to allow scientists to visualize conventional and drift time mass data. Various mass data integrations are possible, allowing a thorough mass spectral data scrutiny. Isotopic cluster calculations are easily carried over from the chemical formula up to the display of the mass spectrum. Deconvolution of mass peaks can be achieved with a simple mouse drag. Flexible reporting of data inspection events and of mining discoveries is provided. Very large sparse data sets can be sliced into smaller chunks replicating the original data without data loss. Task automation is achieved in a JavaScript environment. This project allows users of mass spectrometry facilities to inspect and mine their MS1 mass data outside of these facilities without having to resort to the closed-source vendor software shipped with the instruments. mineXpert requires no proprietary software whatsoever once the mass spectrometry data have been converted to mzML. The reference implementation is version 5.8.2 or greater. Reference material, a detailed user manual, and video tutorials are available at http://www.msxpertsuite.org.",
                        "date": "2019-05-03T00:00:00Z",
                        "citationCount": 4,
                        "authors": [
                            {
                                "name": "Rusconi F."
                            }
                        ],
                        "journal": "Journal of Proteome Research"
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