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            "name": "IDIA",
            "description": "An integrative signal extractor for data-independent acquisition proteomics.",
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                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3646",
                            "term": "Peptide database search"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3767",
                            "term": "Protein identification"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3695",
                            "term": "Filtering"
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                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0943",
                                "term": "Mass spectrum"
                            },
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                                {
                                    "uri": "http://edamontology.org/format_3654",
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                            ]
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                    ],
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                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0943",
                                "term": "Mass spectrum"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_3651",
                                    "term": "MGF"
                                },
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                                    "uri": "http://edamontology.org/format_3244",
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                {
                    "uri": "http://edamontology.org/topic_3520",
                    "term": "Proteomics experiment"
                },
                {
                    "uri": "http://edamontology.org/topic_0121",
                    "term": "Proteomics"
                },
                {
                    "uri": "http://edamontology.org/topic_0080",
                    "term": "Sequence analysis"
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                    "uri": "http://edamontology.org/topic_0154",
                    "term": "Small molecules"
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                {
                    "doi": "10.1109/BIBM55620.2022.9994873",
                    "pmid": "37034305",
                    "pmcid": "PMC10077956",
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "IDIA: An Integrative Signal Extractor for Data-Independent Acquisition Proteomics",
                        "abstract": "In proteomics, data-independent acquisition (DIA)has been shown to provide less biased and more reproducible results than data-dependent acquisition. Recently, many researchers have developed a series of methods to identify peptides and proteins by using spectrum libraries for DIA data. However, spectrum libraries are not always available for novel organisms or microbial communities. To detect peptides and proteins without a spectrum library, we developed IDIA, a library-free method using DIA data to generate pseudo-spectra that can be searched using conventional sequence database searching software. IDIA integrates two isotopic trace detection strategies and employs B-spline and Gaussian filters to help extract high-quality pseudo-spectra from the complex DIA data. The experimental results on human and yeast data demonstrated that our approach remarkably produced more peptide and protein identifications than the two state-of-the-art library-free methods, i.e., DIA-Umpire and Group-DIA. IDIA is freely available under the GNU GPL license at https://github.com/Biocomputing-Research-Group/IDIA.",
                        "date": "2022-01-01T00:00:00Z",
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                        "authors": [
                            {
                                "name": "Li J."
                            },
                            {
                                "name": "Pan C."
                            },
                            {
                                "name": "Guo X."
                            }
                        ],
                        "journal": "Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022"
                    }
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            "credit": [
                {
                    "name": "Xuan Guo",
                    "email": "xuan.guo@unt.edu",
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            "name": "PROTHON",
            "description": "A local order parameter-based method for efficient comparison of protein ensembles.",
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                            "term": "Molecular dynamics"
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                            "uri": "http://edamontology.org/operation_3891",
                            "term": "Essential dynamics"
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                    ],
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                                "term": "Trajectory data"
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                                "uri": "http://edamontology.org/data_3872",
                                "term": "Topology data"
                            },
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                                    "uri": "http://edamontology.org/format_1476",
                                    "term": "PDB"
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                            "data": {
                                "uri": "http://edamontology.org/data_0888",
                                "term": "Structure similarity score"
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                    "term": "Molecular dynamics"
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                    "uri": "http://edamontology.org/topic_0154",
                    "term": "Small molecules"
                },
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                    "uri": "http://edamontology.org/topic_0078",
                    "term": "Proteins"
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                    "uri": "http://edamontology.org/topic_0593",
                    "term": "NMR"
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                {
                    "doi": "10.1021/acs.jcim.3c00145",
                    "pmid": "37178169",
                    "pmcid": null,
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                        "Primary"
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                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "PROTHON: A Local Order Parameter-Based Method for Efficient Comparison of Protein Ensembles",
                        "abstract": "The comparison of protein conformational ensembles is of central importance in structural biology. However, there are few computational methods for ensemble comparison, and those that are readily available, such as ENCORE, utilize methods that are sufficiently computationally expensive to be prohibitive for large ensembles. Here, a new method is presented for efficient representation and comparison of protein conformational ensembles. The method is based on the representation of a protein ensemble as a vector of probability distribution functions (pdfs), with each pdf representing the distribution of a local structural property such as the number of contacts between Cβ atoms. Dissimilarity between two conformational ensembles is quantified by the Jensen-Shannon distance between the corresponding set of probability distribution functions. The method is validated for conformational ensembles generated by molecular dynamics simulations of ubiquitin, as well as experimentally derived conformational ensembles of a 130 amino acid truncated form of human tau protein. In the ubiquitin ensemble data set, the method was up to 88 times faster than the existing ENCORE software, while simultaneously utilizing 48 times fewer computing cores. We make the method available as a Python package, called PROTHON, and provide a GitHub page with the Python source code at https://github.com/PlotkinLab/Prothon.",
                        "date": "2023-06-12T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Aina A."
                            },
                            {
                                "name": "Hsueh S.C.C."
                            },
                            {
                                "name": "Plotkin S.S."
                            }
                        ],
                        "journal": "Journal of Chemical Information and Modeling"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Steven S. Plotkin",
                    "email": "steve@phas.ubc.ca",
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        {
            "name": "VT3D",
            "description": "Visualization toolbox for 3D transcriptomic data.",
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                            "uri": "http://edamontology.org/operation_0337",
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                "Command-line tool"
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                {
                    "uri": "http://edamontology.org/topic_3308",
                    "term": "Transcriptomics"
                },
                {
                    "uri": "http://edamontology.org/topic_0092",
                    "term": "Data visualisation"
                },
                {
                    "uri": "http://edamontology.org/topic_3382",
                    "term": "Imaging"
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            ],
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                "Mac",
                "Linux",
                "Windows"
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                "Python"
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            "link": [
                {
                    "url": "https://github.com/BGI-Qingdao/VT3D_Browser",
                    "type": [
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                    "note": null
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            ],
            "download": [],
            "documentation": [
                {
                    "url": "http://www.bgiocean.com/vt3d_example",
                    "type": [
                        "Training material"
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                    "note": null
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            ],
            "publication": [
                {
                    "doi": "10.1016/J.JGG.2023.04.001",
                    "pmid": "37054878",
                    "pmcid": null,
                    "type": [],
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                    "note": null,
                    "metadata": {
                        "title": "VT3D: a visualization toolbox for 3D transcriptomic data",
                        "abstract": "Data visualization empowers researchers to communicate their results that support scientific reasoning in an intuitive way. 3D spatially resolved transcriptomic atlases constructed from multi-view and high-dimensional data have rapidly emerged as a powerful tool to unravel spatial gene expression patterns and cell type distribution in biological samples, revolutionizing the understanding of gene regulatory interactions and cell niches. However, limited accessible tools for data visualization impede the potential impact and application of this technology. Here we introduce VT3D, a visualization toolbox that allows users to explore 3D transcriptomic data, enabling gene expression projection to any 2D plane of interest, 2D virtual slice creation and visualization, and interactive 3D data browsing with surface model plots. In addition, it can either work on personal devices in standalone mode or be hosted as a web-based server. We apply VT3D to multiple datasets produced by the most popular techniques, including both sequencing-based approaches including Stereo-seq, spatial transcriptomics (ST), and Slide-seq, and imaging-based approaches including MERFISH and STARMap, and successfully build a 3D atlas database that allows interactive data browsing. We demonstrate that VT3D bridges the gap between researchers and spatially resolved transcriptomics, thus accelerating related studies such as embryogenesis and organogenesis processes. The source code of VT3D is available at https://github.com/BGI-Qingdao/VT3D, and the modeled atlas database is available at http://www.bgiocean.com/vt3d_example.",
                        "date": "2023-01-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Guo L."
                            },
                            {
                                "name": "Li Y."
                            },
                            {
                                "name": "Qi Y."
                            },
                            {
                                "name": "Huang Z."
                            },
                            {
                                "name": "Han K."
                            },
                            {
                                "name": "Liu X."
                            },
                            {
                                "name": "Liu X."
                            },
                            {
                                "name": "Xu M."
                            },
                            {
                                "name": "Fan G."
                            }
                        ],
                        "journal": "Journal of Genetics and Genomics"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Mengyang Xu",
                    "email": "xumengyang@genomics.cn",
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                },
                {
                    "name": "Guangyi Fan",
                    "email": "fanguangyi@genomics.cn",
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        },
        {
            "name": "ANISEED",
            "description": "ANISEED is the main model organism database for the worldwide community of scientists working on tunicates (sister-group of vertebrates). It integrates for each species: \ni) a main knowledge base with extended functional, gene expression, phenotyping, anatomical and phylogenetic information; \nii) A multispecies genomic browser; \niii) a Genomicus gene synteny browser.",
            "homepage": "https://www.aniseed.fr",
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                    "type": "doi",
                    "version": "2015"
                },
                {
                    "value": "DOI:10.1101/gr.108175.110",
                    "type": "doi",
                    "version": "2010"
                },
                {
                    "value": "DOI:10.1016/j.cub.2005.12.044",
                    "type": "doi",
                    "version": "2006"
                }
            ],
            "relation": [
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                {
                    "biotoolsID": "blast",
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                {
                    "biotoolsID": "genomicus-tunicates",
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                {
                    "biotoolsID": "ciona_robusta_anatomy_and_development_ontology",
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                    "biotoolsID": "morphonet",
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                            "term": "Phylogenetic tree visualisation"
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                            "term": "Query and retrieval"
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                            "uri": "http://edamontology.org/operation_0292",
                            "term": "Sequence alignment"
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                            "term": "Genome annotation"
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                    "uri": "http://edamontology.org/topic_2229",
                    "term": "Cell biology"
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                    "uri": "http://edamontology.org/topic_3064",
                    "term": "Developmental biology"
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                    "term": "Data submission, annotation and curation"
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                    "term": "Embryology"
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                    "uri": "http://edamontology.org/topic_3383",
                    "term": "Biological imaging"
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                    "uri": "http://edamontology.org/topic_3679",
                    "term": "Animal study"
                },
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                    "uri": "http://edamontology.org/topic_0085",
                    "term": "Functional genomics"
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                    "uri": "http://edamontology.org/topic_3308",
                    "term": "Transcriptomics"
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                    "uri": "http://edamontology.org/topic_0194",
                    "term": "Phylogenomics"
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            "language": [
                "PHP",
                "JavaScript",
                "Python"
            ],
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                "elixir-fr-sdp-2019"
            ],
            "maturity": "Mature",
            "cost": "Free of charge",
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                "Tools",
                "Data",
                "Interoperability"
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            "elixirNode": [
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            "link": [
                {
                    "url": "https://www.aniseed.fr",
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                        "Service"
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                    "note": null
                },
                {
                    "url": "https://twitter.com/Aniseed_DB",
                    "type": [
                        "Social media"
                    ],
                    "note": "Twitter for ANISEED"
                },
                {
                    "url": "https://www.facebook.com/TunicateCommunity",
                    "type": [
                        "Social media"
                    ],
                    "note": "Facebook for ANISEED"
                },
                {
                    "url": "https://morphonet.org/",
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                        "Service"
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                    "note": null
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            ],
            "download": [
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                    "url": "https://www.aniseed.fr/aniseed/download/download_data",
                    "type": "Biological data",
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                    "version": "2019"
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            "documentation": [
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                    "url": "https://www.aniseed.fr/api",
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                    "type": [
                        "Contributions policy"
                    ],
                    "note": null
                },
                {
                    "url": "https://www.aniseed.fr/aniseed/default/termOfUse",
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                    "metadata": {
                        "title": "ANISEED 2017: Extending the integrated ascidian database to the exploration and evolutionary comparison of genome-scale datasets",
                        "abstract": "ANISEED (www.aniseed.cnrs.fr) is the main model organism database for tunicates, the sister-group of vertebrates. This release gives access to annotated genomes, gene expression patterns, and anatomical descriptions for nine ascidian species. It provides increased integration with external molecular and taxonomy databases, better support for epigenomics datasets, in particular RNA-seq, ChIP-seq and SELEX-seq, and features novel interactive interfaces for existing and novel datatypes. In particular, the cross-species navigation and comparison is enhanced through a novel taxonomy section describing each represented species and through the implementation of interactive phylogenetic gene trees for 60% of tunicate genes. The gene expression section displays the results of RNA-seq experiments for the three major model species of solitary ascidians. Gene expression is controlled by the binding of transcription factors to cis-regulatory sequences. A high-resolution description of the DNA-binding specificity for 131 Ciona robusta (formerly C. intestinalis type A) transcription factors by SELEX-seq is provided and used to map candidate binding sites across the Ciona robusta and Phallusia mammillata genomes. Finally, use of a WashU Epigenome browser enhances genome navigation, while a Genomicus server was set up to explore microsynteny relationships within tunicates and with vertebrates, Amphioxus, echinoderms and hemichordates.",
                        "date": "2018-01-01T00:00:00Z",
                        "citationCount": 62,
                        "authors": [
                            {
                                "name": "Brozovic M."
                            },
                            {
                                "name": "Dantec C."
                            },
                            {
                                "name": "Dardaillon J."
                            },
                            {
                                "name": "Dauga D."
                            },
                            {
                                "name": "Faure E."
                            },
                            {
                                "name": "Gineste M."
                            },
                            {
                                "name": "Louis A."
                            },
                            {
                                "name": "Naville M."
                            },
                            {
                                "name": "Nitta K.R."
                            },
                            {
                                "name": "Piette J."
                            },
                            {
                                "name": "Reeves W."
                            },
                            {
                                "name": "Scornavacca C."
                            },
                            {
                                "name": "Simion P."
                            },
                            {
                                "name": "Vincentelli R."
                            },
                            {
                                "name": "Bellec M."
                            },
                            {
                                "name": "Aicha S.B."
                            },
                            {
                                "name": "Fagotto M."
                            },
                            {
                                "name": "Gueroult-Bellone M."
                            },
                            {
                                "name": "Haeussler M."
                            },
                            {
                                "name": "Jacox E."
                            },
                            {
                                "name": "Lowe E.K."
                            },
                            {
                                "name": "Mendez M."
                            },
                            {
                                "name": "Roberge A."
                            },
                            {
                                "name": "Stolfi A."
                            },
                            {
                                "name": "Yokomori R."
                            },
                            {
                                "name": "Brown C.T."
                            },
                            {
                                "name": "Cambillau C."
                            },
                            {
                                "name": "Christiaen L."
                            },
                            {
                                "name": "Delsuc F."
                            },
                            {
                                "name": "Douzery E."
                            },
                            {
                                "name": "Dumollard R."
                            },
                            {
                                "name": "Kusakabe T."
                            },
                            {
                                "name": "Nakai K."
                            },
                            {
                                "name": "Nishida H."
                            },
                            {
                                "name": "Satou Y."
                            },
                            {
                                "name": "Swalla B."
                            },
                            {
                                "name": "Veeman M."
                            },
                            {
                                "name": "Volff J.-N."
                            },
                            {
                                "name": "Lemaire P."
                            }
                        ],
                        "journal": "Nucleic Acids Research"
                    }
                },
                {
                    "doi": "10.1093/nar/gkv966",
                    "pmid": null,
                    "pmcid": null,
                    "type": [
                        "Primary"
                    ],
                    "version": "2015",
                    "note": null,
                    "metadata": {
                        "title": "ANISEED 2015: A digital framework for the comparative developmental biology of ascidians",
                        "abstract": "Ascidians belong to the tunicates, the sister group of vertebrates and are recognized model organisms in the field of embryonic development, regeneration and stem cells. ANISEED is the main information system in the field of ascidian developmental biology. This article reports the development of the system since its initial publication in 2010. Over the past five years, we refactored the system from an initial custom schema to an extended version of the Chado schema and redesigned all user and back end interfaces. This new architecture was used to improve and enrich the description of Ciona intestinalisembryonic development, based on an improved genome assembly and gene model set, refined functional gene annotation, and anatomical ontologies, and a new collection of full ORF cDNAs. The genomes of nine ascidian species have been sequenced since the release of the C. intestinalisgenome. In ANISEED 2015, all nine new ascidian species can be explored via dedicated genome browsers, and searched by Blast. In addition, ANISEED provides full functional gene annotation, anatomical ontologies and some gene expression data for the six species with highest quality genomes. ANISEED is publicly available at: http://www.aniseed.cnrs.fr.",
                        "date": "2016-01-01T00:00:00Z",
                        "citationCount": 53,
                        "authors": [
                            {
                                "name": "Brozovic M."
                            },
                            {
                                "name": "Martin C."
                            },
                            {
                                "name": "Dantec C."
                            },
                            {
                                "name": "Dauga D."
                            },
                            {
                                "name": "Mendez M."
                            },
                            {
                                "name": "Simion P."
                            },
                            {
                                "name": "Percher M."
                            },
                            {
                                "name": "Laporte B."
                            },
                            {
                                "name": "Scornavacca C."
                            },
                            {
                                "name": "Di Gregorio A."
                            },
                            {
                                "name": "Fujiwara S."
                            },
                            {
                                "name": "Gineste M."
                            },
                            {
                                "name": "Lowe E.K."
                            },
                            {
                                "name": "Piette J."
                            },
                            {
                                "name": "Racioppi C."
                            },
                            {
                                "name": "Ristoratore F."
                            },
                            {
                                "name": "Sasakura Y."
                            },
                            {
                                "name": "Takatori N."
                            },
                            {
                                "name": "Brown T.C."
                            },
                            {
                                "name": "Delsuc F."
                            },
                            {
                                "name": "Douzery E."
                            },
                            {
                                "name": "Gissi C."
                            },
                            {
                                "name": "McDougall A."
                            },
                            {
                                "name": "Nishida H."
                            },
                            {
                                "name": "Sawada H."
                            },
                            {
                                "name": "Swalla B.J."
                            },
                            {
                                "name": "Yasuo H."
                            },
                            {
                                "name": "Lemaire P."
                            }
                        ],
                        "journal": "Nucleic Acids Research"
                    }
                },
                {
                    "doi": "10.1101/gr.108175.110",
                    "pmid": null,
                    "pmcid": null,
                    "type": [
                        "Primary"
                    ],
                    "version": "2010",
                    "note": null,
                    "metadata": {
                        "title": "The ANISEED database: Digital representation, formalization, and elucidation of a chordate developmental program",
                        "abstract": "Developmental biology aims to understand how the dynamics of embryonic shapes and organ functions are encoded in linear DNA molecules. Thanks to recent progress in genomics and imaging technologies, systemic approaches are now used in parallel with small-scale studies to establish links between genomic information and phenotypes, often described at the subcellular level. Current model organism databases, however, do not integrate heterogeneous data sets at different scales into a global view of the developmental program. Here, we present a novel, generic digital system, NISEED, and its implementation, ANISEED, to ascidians, which are invertebrate chordates suitable for developmental systems biology approaches. ANISEED hosts an unprecedented combination of anatomical and molecular data on ascidian development. This includes the first detailed anatomical ontologies for these embryos, and quantitative geometrical descriptions of developing cells obtained from reconstructed three-dimensional (3D) embryos up to the gastrula stages. Fully annotated gene model sets are linked to 30,000 high-resolution spatial gene expression patterns in wild-type and experimentally manipulated conditions and to 528 experimentally validated cis-regulatory regions imported from specialized databases or extracted from 160 literature articles. This highly structured data set can be explored via a Developmental Browser, a Genome Browser, and a 3D Virtual Embryo module. We show how integration of heterogeneous data in ANISEED can provide a system-level understanding of the developmental program through the automatic inference of gene regulatory interactions, the identification of inducing signals, and the discovery and explanation of novel asymmetric divisions. © 2010 by Cold Spring Harbor Laboratory Press.",
                        "date": "2010-01-01T00:00:00Z",
                        "citationCount": 90,
                        "authors": [
                            {
                                "name": "Tassy O."
                            },
                            {
                                "name": "Dauga D."
                            },
                            {
                                "name": "Daian F."
                            },
                            {
                                "name": "Sobral D."
                            },
                            {
                                "name": "Robin F."
                            },
                            {
                                "name": "Khoueiry P."
                            },
                            {
                                "name": "Salgado D."
                            },
                            {
                                "name": "Fox V."
                            },
                            {
                                "name": "Caillol D."
                            },
                            {
                                "name": "Schiappa R."
                            },
                            {
                                "name": "Laporte B."
                            },
                            {
                                "name": "Rios A."
                            },
                            {
                                "name": "Luxardi G."
                            },
                            {
                                "name": "Kusakabe T."
                            },
                            {
                                "name": "Joly J.-S."
                            },
                            {
                                "name": "Darras S."
                            },
                            {
                                "name": "Christiaen L."
                            },
                            {
                                "name": "Contensin M."
                            },
                            {
                                "name": "Auger H."
                            },
                            {
                                "name": "Lamy C."
                            },
                            {
                                "name": "Hudson C."
                            },
                            {
                                "name": "Rothbacher U."
                            },
                            {
                                "name": "Gilchrist M.J."
                            },
                            {
                                "name": "Makabe K.W."
                            },
                            {
                                "name": "Hotta K."
                            },
                            {
                                "name": "Fujiwara S."
                            },
                            {
                                "name": "Satoh N."
                            },
                            {
                                "name": "Satou Y."
                            },
                            {
                                "name": "Lemaire P."
                            }
                        ],
                        "journal": "Genome Research"
                    }
                },
                {
                    "doi": "10.1016/j.cub.2005.12.044",
                    "pmid": null,
                    "pmcid": null,
                    "type": [
                        "Primary"
                    ],
                    "version": "2006",
                    "note": null,
                    "metadata": {
                        "title": "A quantitative approach to the study of cell shapes and interactions during early chordate embryogenesis",
                        "abstract": "Background: The prospects of deciphering the genetic program underlying embryonic development were recently boosted by the generation of large sets of precisely organized quantitative molecular data. In contrast, although the precise arrangement, interactions, and shapes of cells are crucial for the fulfilment of this program, their description remains coarse and qualitative. To bridge this gap, we developed a generic software, 3D Virtual Embryo, to quantify the geometry and interactions of cells in interactive three-dimensional embryo models. We applied this approach to early ascidian embryos, chosen because of their simplicity and their phylogenetic proximity to vertebrates. Results: We generated a collection of 19 interactive ascidian embryos between the 2- and 44-cell stages. We characterized the evolution with time, and in different cell lineages, of the volume of cells and of eight mathematical descriptors of their geometry, and we measured the surface of contact between neighboring blastomeres. These analyses first revealed that early embryonic blastomeres adopt a surprising variety of shapes, which appeared to be under strict and dynamic developmental control. Second, we found novel asymmetric cell divisions in the posterior vegetal lineages, which gave birth to sister cells with different fates. Third, during neural induction, differences in the area of contact between individual competent animal cells and inducing vegetal blastomeres appeared important to select the induced cells. Conclusions: In addition to novel insight into both cell-autonomous and inductive processes controlling early ascidian development, we establish a generic conceptual framework for the quantitative analysis of embryo geometry that can be applied to other model organisms. ©2006 Elsevier Ltd All rights reserved.",
                        "date": "2006-02-21T00:00:00Z",
                        "citationCount": 116,
                        "authors": [
                            {
                                "name": "Tassy O."
                            },
                            {
                                "name": "Daian F."
                            },
                            {
                                "name": "Hudson C."
                            },
                            {
                                "name": "Bertrand V."
                            },
                            {
                                "name": "Lemaire P."
                            }
                        ],
                        "journal": "Current Biology"
                    }
                },
                {
                    "doi": "10.1093/nar/gkz955",
                    "pmid": null,
                    "pmcid": null,
                    "type": [],
                    "version": "2019",
                    "note": null,
                    "metadata": {
                        "title": "ANISEED 2019: 4D exploration of genetic data for an extended range of tunicates",
                        "abstract": "ANISEED (https://www.aniseed.cnrs.fr) is the main model organism database for the worldwide community of scientists working on tunicates, the vertebrate sister-group. Information provided for each species includes functionally-annotated gene and transcript models with orthology relationships within tunicates, and with echinoderms, cephalochordates and vertebrates. Beyond genes the system describes other genetic elements, including repeated elements and cis-regulatory modules. Gene expression profiles for several thousand genes are formalized in both wild-type and experimentally-manipulated conditions, using formal anatomical ontologies. These data can be explored through three complementary types of browsers, each offering a different view-point. A developmental browser summarizes the information in a gene- or territory-centric manner. Advanced genomic browsers integrate the genetic features surrounding genes or gene sets within a species. A Genomicus synteny browser explores the conservation of local gene order across deuterostome. This new release covers an extended taxonomic range of 14 species, including for the first time a non-ascidian species, the appendicularian Oikopleura dioica. Functional annotations, provided for each species, were enhanced through a combination of manual curation of gene models and the development of an improved orthology detection pipeline. Finally, gene expression profiles and anatomical territories can be explored in 4D online through the newly developed Morphonet morphogenetic browser.",
                        "date": "2020-01-01T00:00:00Z",
                        "citationCount": 31,
                        "authors": [
                            {
                                "name": "Dardaillon J."
                            },
                            {
                                "name": "Dauga D."
                            },
                            {
                                "name": "Simion P."
                            },
                            {
                                "name": "Faure E."
                            },
                            {
                                "name": "Onuma T.A."
                            },
                            {
                                "name": "Debiasse M.B."
                            },
                            {
                                "name": "Louis A."
                            },
                            {
                                "name": "Nitta K.R."
                            },
                            {
                                "name": "Naville M."
                            },
                            {
                                "name": "Besnardeau L."
                            },
                            {
                                "name": "Reeves W."
                            },
                            {
                                "name": "Wang K."
                            },
                            {
                                "name": "Fagotto M."
                            },
                            {
                                "name": "Gueroult-Bellone M."
                            },
                            {
                                "name": "Fujiwara S."
                            },
                            {
                                "name": "Dumollard R."
                            },
                            {
                                "name": "Veeman M."
                            },
                            {
                                "name": "Volff J.-N."
                            },
                            {
                                "name": "Roest Crollius H."
                            },
                            {
                                "name": "Douzery E."
                            },
                            {
                                "name": "Ryan J.F."
                            },
                            {
                                "name": "Davidson B."
                            },
                            {
                                "name": "Nishida H."
                            },
                            {
                                "name": "Dantec C."
                            },
                            {
                                "name": "Lemaire P."
                            }
                        ],
                        "journal": "Nucleic Acids Research"
                    }
                },
                {
                    "doi": "10.1093/nar/gkz955",
                    "pmid": null,
                    "pmcid": null,
                    "type": [],
                    "version": "2019",
                    "note": null,
                    "metadata": null
                }
            ],
            "credit": [
                {
                    "name": "Patrick Lemaire",
                    "email": "patrick.lemaire@crbm.cnrs.fr",
                    "url": "http://www.crbm.cnrs.fr/en/team/lemaire/",
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                },
                {
                    "name": "Christelle Dantec",
                    "email": "christelle.dantec@crbm.cnrs.fr",
                    "url": "http://www.crbm.cnrs.fr/en/team/lemaire/",
                    "orcidid": "https://orcid.org/0000-0001-7247-6460",
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                    "typeEntity": "Person",
                    "typeRole": [
                        "Primary contact"
                    ],
                    "note": null
                },
                {
                    "name": null,
                    "email": "contact@aniseed.fr",
                    "url": null,
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            "additionDate": "2019-10-19T13:23:03Z",
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        {
            "name": "CellTrackVis",
            "description": "interactive browser-based visualization for analyzing cell trajectories and lineages.",
            "homepage": "http://github.com/scbeom/celltrackvis",
            "biotoolsID": "celltrackvis",
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                            "uri": "http://edamontology.org/operation_3890",
                            "term": "Trajectory visualization"
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                        {
                            "uri": "http://edamontology.org/operation_3446",
                            "term": "Cell migration analysis"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0244",
                            "term": "Simulation analysis"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Desktop application"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_2229",
                    "term": "Cell biology"
                },
                {
                    "uri": "http://edamontology.org/topic_3382",
                    "term": "Imaging"
                },
                {
                    "uri": "http://edamontology.org/topic_3068",
                    "term": "Literature and language"
                }
            ],
            "operatingSystem": [
                "Mac",
                "Linux",
                "Windows"
            ],
            "language": [
                "Python"
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            "documentation": [
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                    "url": "http://scbeom.github.io/ctv_tutorial",
                    "type": [
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                    ],
                    "note": null
                }
            ],
            "publication": [
                {
                    "doi": "10.1186/S12859-023-05218-Y",
                    "pmid": "36991341",
                    "pmcid": "PMC10053428",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "CellTrackVis: interactive browser-based visualization for analyzing cell trajectories and lineages",
                        "abstract": "Background: Automatic cell tracking methods enable practitioners to analyze cell behaviors efficiently. Notwithstanding the continuous development of relevant software, user-friendly visualization tools have room for further improvements. Typical visualization mostly comes with main cell tracking tools as a simple plug-in, or relies on specific software/platforms. Although some tools are standalone, limited visual interactivity is provided, or otherwise cell tracking outputs are partially visualized. Results: This paper proposes a self-reliant visualization system, CellTrackVis, to support quick and easy analysis of cell behaviors. Interconnected views help users discover meaningful patterns of cell motions and divisions in common web browsers. Specifically, cell trajectory, lineage, and quantified information are respectively visualized in a coordinated interface. In particular, immediate interactions among modules enable the study of cell tracking outputs to be more effective, and also each component is highly customizable for various biological tasks. Conclusions: CellTrackVis is a standalone browser-based visualization tool. Source codes and data sets are freely available at http://github.com/scbeom/celltrackvis with the tutorial at http://scbeom.github.io/ctv_tutorial.",
                        "date": "2023-12-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Shim C."
                            },
                            {
                                "name": "Kim W."
                            },
                            {
                                "name": "Nguyen T.T.D."
                            },
                            {
                                "name": "Kim D.Y."
                            },
                            {
                                "name": "Choi Y.S."
                            },
                            {
                                "name": "Chung Y.D."
                            }
                        ],
                        "journal": "BMC Bioinformatics"
                    }
                }
            ],
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                    "name": "Yon Dohn Chung",
                    "email": "ydchung@korea.ac.kr",
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        },
        {
            "name": "TB-ML",
            "description": "Framework for comparing machine learning approaches to predict drug resistance of Mycobacterium tuberculosis.",
            "homepage": "https://tb-ml.github.io/tb-ml-containers/",
            "biotoolsID": "tb_ml",
            "biotoolsCURIE": "biotools:tb_ml",
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                            "uri": "http://edamontology.org/operation_3482",
                            "term": "Antimicrobial resistance prediction"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3196",
                            "term": "Genotyping"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3227",
                            "term": "Variant calling"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Command-line tool"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_3474",
                    "term": "Machine learning"
                },
                {
                    "uri": "http://edamontology.org/topic_3673",
                    "term": "Whole genome sequencing"
                },
                {
                    "uri": "http://edamontology.org/topic_0769",
                    "term": "Workflows"
                }
            ],
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                "Mac",
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                "Windows"
            ],
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            "link": [
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            "publication": [
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                    "doi": "10.1093/BIOADV/VBAD040",
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                    "pmcid": "PMC10074023",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "TB-ML - a framework for comparing machine learning approaches to predict drug resistance of Mycobacterium tuberculosis",
                        "abstract": "Motivation: Machine learning (ML) has shown impressive performance in predicting antimicrobial resistance (AMR) from sequence data, including for Mycobacterium tuberculosis, the causative agent of tuberculosis. However, current ML development and publication practices make it difficult for researchers and clinicians to use, test or reproduce published models. Results: We packaged a number of published and unpublished ML models for predicting AMR of M.tuberculosis into Docker containers. Similarly, the pipelines required for pre-processing genomic data into the formats required by the models were also packaged into separate containers. By following a minimal container I/O standard, we ensured as much interoperability as possible. We also created a command-line application, TB-ML, which can be used to easily combine pre-processing and prediction containers into complete pipelines ready for predicting resistance from novel, raw data with a single command. As long as there is adherence to this minimal standard for the container interface, containers produced by researchers holding new models can likewise be included in these pipelines, making benchmark comparisons of different models simple and facilitating faster uptake in the clinic. Availability and implementation: TB-ML contains a simple Docker API written in Python and is available at https://github. com/jodyphelan/tb-ml. Example Docker containers for resistance prediction and corresponding data pre-processing as well as a tutorial on how to create new containers for TB-ML are available at https://tb-ml.github.io/tb-ml-containers/.",
                        "date": "2023-01-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Libiseller-Egger J."
                            },
                            {
                                "name": "Wang L."
                            },
                            {
                                "name": "Deelder W."
                            },
                            {
                                "name": "Campino S."
                            },
                            {
                                "name": "Clark T.G."
                            },
                            {
                                "name": "Phelan J.E."
                            }
                        ],
                        "journal": "Bioinformatics Advances"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Jody E Phelan",
                    "email": "jody.phelan@lshtm.ac.uk",
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                            "uri": "http://edamontology.org/operation_0264",
                            "term": "Alternative splicing prediction"
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                            "uri": "http://edamontology.org/operation_0433",
                            "term": "Splice site prediction"
                        },
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                            "uri": "http://edamontology.org/operation_0446",
                            "term": "Exonic splicing enhancer prediction"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0232",
                            "term": "Sequence merging"
                        },
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                            "uri": "http://edamontology.org/operation_2436",
                            "term": "Gene-set enrichment analysis"
                        }
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                    "uri": "http://edamontology.org/topic_3320",
                    "term": "RNA splicing"
                },
                {
                    "uri": "http://edamontology.org/topic_3512",
                    "term": "Gene transcripts"
                },
                {
                    "uri": "http://edamontology.org/topic_3170",
                    "term": "RNA-Seq"
                },
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                    "uri": "http://edamontology.org/topic_3308",
                    "term": "Transcriptomics"
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                    "term": "Pharmacology"
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            "publication": [
                {
                    "doi": "10.1093/NAR/GKAD111",
                    "pmid": "36864749",
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                    "metadata": {
                        "title": "SpliceTools, a suite of downstream RNA splicing analysis tools to investigate mechanisms and impact of alternative splicing",
                        "abstract": "As a fundamental aspect of normal cell signaling and disease states, there is great interest in determining alternative splicing (AS) changes in physiologic, pathologic, and pharmacologic settings. High throughput RNA sequencing and specialized software to detect AS has greatly enhanced our ability to determine transcriptome-wide splicing changes. Despite the richness of this data, deriving meaning from sometimes thousands of AS events is a substantial bottleneck for most investigators. We present SpliceTools, a suite of data processing modules that arms investigators with the ability to quickly produce summary statistics, mechanistic insights, and functional significance of AS changes through command line or through an online user interface. Utilizing RNA-seq datasets for 186 RNA binding protein knockdowns, nonsense mediated RNA decay inhibition, and pharmacologic splicing inhibition, we illustrate the utility of SpliceTools to distinguish splicing disruption from regulated transcript isoform changes, we show the broad transcriptome footprint of the pharmacologic splicing inhibitor, indisulam, we illustrate the utility in uncovering mechanistic underpinnings of splicing inhibition, we identify predicted neo-epitopes in pharmacologic splicing inhibition, and we show the impact of splicing alterations induced by indisulam on cell cycle progression. Together, SpliceTools puts rapid and easy downstream analysis at the fingertips of any investigator studying AS.",
                        "date": "2023-04-24T00:00:00Z",
                        "citationCount": 1,
                        "authors": [
                            {
                                "name": "Flemington E.K."
                            },
                            {
                                "name": "Flemington S.A."
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                            {
                                "name": "O'Grady T.M."
                            },
                            {
                                "name": "Baddoo M."
                            },
                            {
                                "name": "Nguyen T."
                            },
                            {
                                "name": "Dong Y."
                            },
                            {
                                "name": "Ungerleider N.A."
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                        ],
                        "journal": "Nucleic Acids Research"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Erik K Flemington",
                    "email": "nungerle@tulane.edu",
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                    "name": "Nathan A Ungerleider",
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                    "name": "Samuel A Flemington",
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                    "name": "Tina M O’Grady",
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        {
            "name": "spongEffects",
            "description": "The package provides methods to efficiently detect competitive endogeneous RNA interactions between two genes.",
            "homepage": "https://bioconductor.org/packages/devel/bioc/html/SPONGE.html",
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            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3463",
                            "term": "Expression correlation analysis"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0463",
                            "term": "miRNA target prediction"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3792",
                            "term": "miRNA expression analysis"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
                    "cmd": null
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            ],
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                "Library",
                "Web application"
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            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0659",
                    "term": "Functional, regulatory and non-coding RNA"
                },
                {
                    "uri": "http://edamontology.org/topic_0602",
                    "term": "Molecular interactions, pathways and networks"
                },
                {
                    "uri": "http://edamontology.org/topic_0203",
                    "term": "Gene expression"
                },
                {
                    "uri": "http://edamontology.org/topic_3360",
                    "term": "Biomarkers"
                },
                {
                    "uri": "http://edamontology.org/topic_3512",
                    "term": "Gene transcripts"
                }
            ],
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                {
                    "url": "http://sponge-api.biomedical-big-data.de/",
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            ],
            "publication": [
                {
                    "doi": "10.1093/BIOINFORMATICS/BTAD276",
                    "pmid": "37084275",
                    "pmcid": "PMC10220456",
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "SpongEffects: CeRNA modules offer patient-specific insights into the miRNA regulatory landscape",
                        "abstract": "Motivation: Cancer is one of the leading causes of death worldwide. Despite significant improvements in prevention and treatment, mortality remains high for many cancer types. Hence, innovative methods that use molecular data to stratify patients and identify biomarkers are needed. Promising biomarkers can also be inferred from competing endogenous RNA (ceRNA) networks that capture the gene-miRNA gene regulatory landscape. Thus far, the role of these biomarkers could only be studied globally but not in a sample-specific manner. To mitigate this, we introduce spongEffects, a novel method that infers subnetworks (or modules) from ceRNA networks and calculates patient- or sample-specific scores related to their regulatory activity. Results: We show how spongEffects can be used for downstream interpretation and machine learning tasks such as tumor classification and for identifying subtype-specific regulatory interactions. In a concrete example of breast cancer subtype classification, we prioritize modules impacting the biology of the different subtypes. In summary, spongEffects prioritizes ceRNA modules as biomarkers and offers insights into the miRNA regulatory landscape. Notably, these module scores can be inferred from gene expression data alone and can thus be applied to cohorts where miRNA expression information is lacking.",
                        "date": "2023-05-01T00:00:00Z",
                        "citationCount": 1,
                        "authors": [
                            {
                                "name": "Boniolo F."
                            },
                            {
                                "name": "Hoffmann M."
                            },
                            {
                                "name": "Roggendorf N."
                            },
                            {
                                "name": "Tercan B."
                            },
                            {
                                "name": "Baumbach J."
                            },
                            {
                                "name": "Castro M.A.A."
                            },
                            {
                                "name": "Robertson A.G."
                            },
                            {
                                "name": "Saur D."
                            },
                            {
                                "name": "List M."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Markus Hoffmann",
                    "email": "markus.daniel.hoffmann@tum.de",
                    "url": null,
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                },
                {
                    "name": "Markus List",
                    "email": "markus.list@tum.de",
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        },
        {
            "name": "FAS",
            "description": "Assessing the similarity between proteins using multi-layered feature architectures.",
            "homepage": "https://pypi.org/project/greedyFAS/",
            "biotoolsID": "fas",
            "biotoolsCURIE": "biotools:fas",
            "version": [],
            "otherID": [],
            "relation": [],
            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_2474",
                            "term": "Protein architecture comparison"
                        },
                        {
                            "uri": "http://edamontology.org/operation_2421",
                            "term": "Database search"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3672",
                            "term": "Gene functional annotation"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_2976",
                                "term": "Protein sequence"
                            },
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                                {
                                    "uri": "http://edamontology.org/format_1929",
                                    "term": "FASTA"
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                    ],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1277",
                                "term": "Protein features"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_2332",
                                    "term": "XML"
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                    "uri": "http://edamontology.org/topic_0089",
                    "term": "Ontology and terminology"
                },
                {
                    "uri": "http://edamontology.org/topic_3520",
                    "term": "Proteomics experiment"
                },
                {
                    "uri": "http://edamontology.org/topic_0736",
                    "term": "Protein folds and structural domains"
                },
                {
                    "uri": "http://edamontology.org/topic_0121",
                    "term": "Proteomics"
                },
                {
                    "uri": "http://edamontology.org/topic_0621",
                    "term": "Model organisms"
                }
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            "link": [
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                    "url": "https://github.com/BIONF/FAS",
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            ],
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            "publication": [
                {
                    "doi": "10.1093/BIOINFORMATICS/BTAD226",
                    "pmid": "37084276",
                    "pmcid": "PMC10185405",
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "FAS: assessing the similarity between proteins using multi-layered feature architectures",
                        "abstract": "Motivation: Protein sequence comparison is a fundamental element in the bioinformatics toolkit. When sequences are annotated with features such as functional domains, transmembrane domains, low complexity regions or secondary structure elements, the resulting feature architectures allow better informed comparisons. However, many existing schemes for scoring architecture similarities cannot cope with features arising from multiple annotation sources. Those that do fall short in the resolution of overlapping and redundant feature annotations. Results: Here, we introduce FAS, a scoring method that integrates features from multiple annotation sources in a directed acyclic architecture graph. Redundancies are resolved as part of the architecture comparison by finding the paths through the graphs that maximize the pair-wise architecture similarity. In a large-scale evaluation on more than 10 000 human-yeast ortholog pairs, architecture similarities assessed with FAS are consistently more plausible than those obtained using e-values to resolve overlaps or leaving overlaps unresolved. Three case studies demonstrate the utility of FAS on architecture comparison tasks: benchmarking of orthology assignment software, identification of functionally diverged orthologs, and diagnosing protein architecture changes stemming from faulty gene predictions. With the help of FAS, feature architecture comparisons can now be routinely integrated into these and many other applications. Availability and implementation: FAS is available as python package: https://pypi.org/project/greedyFAS/.",
                        "date": "2023-05-01T00:00:00Z",
                        "citationCount": 3,
                        "authors": [
                            {
                                "name": "Dosch J."
                            },
                            {
                                "name": "Bergmann H."
                            },
                            {
                                "name": "Tran V."
                            },
                            {
                                "name": "Ebersberger I."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Ingo Ebersberger",
                    "email": "ebersberger@bio.uni-frankfurt.de",
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        {
            "name": "methylR",
            "description": "Graphical interface for comprehensive DNA methylation array data analysis.",
            "homepage": "https://methylr.research.liu.se",
            "biotoolsID": "methylr",
            "biotoolsCURIE": "biotools:methylr",
            "version": [],
            "otherID": [],
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            "function": [
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                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3204",
                            "term": "Methylation analysis"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3891",
                            "term": "Essential dynamics"
                        },
                        {
                            "uri": "http://edamontology.org/operation_2436",
                            "term": "Gene-set enrichment analysis"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3928",
                            "term": "Pathway analysis"
                        },
                        {
                            "uri": "http://edamontology.org/operation_2939",
                            "term": "Principal component visualisation"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_3110",
                                "term": "Raw microarray data"
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                    "output": [
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                            "data": {
                                "uri": "http://edamontology.org/data_0916",
                                "term": "Gene report"
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                        },
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1636",
                                "term": "Heat map"
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                        },
                        {
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                                "uri": "http://edamontology.org/data_3754",
                                "term": "GO-term enrichment data"
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                        },
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_3953",
                                "term": "Pathway overrepresentation data"
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                        }
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                "Desktop application"
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                    "term": "Epigenetics"
                },
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                    "uri": "http://edamontology.org/topic_3518",
                    "term": "Microarray experiment"
                },
                {
                    "uri": "http://edamontology.org/topic_0654",
                    "term": "DNA"
                },
                {
                    "uri": "http://edamontology.org/topic_0602",
                    "term": "Molecular interactions, pathways and networks"
                },
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                    "uri": "http://edamontology.org/topic_3170",
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            ],
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                "R"
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            "link": [
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                    "url": "https://groups.google.com/g/methylr",
                    "type": [
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                    "url": "https://sourceforge.net/projects/methylr/",
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                    "url": "http://methylr.netlify.app",
                    "type": [
                        "Other"
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            ],
            "download": [
                {
                    "url": "https://hub.docker.com/r/jd21/methylr",
                    "type": "Container file",
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                    "version": null
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            ],
            "documentation": [
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                    "url": "https://methylr.netlify.app/methylysis",
                    "type": [
                        "User manual"
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            "publication": [
                {
                    "doi": "10.1093/BIOINFORMATICS/BTAD184",
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                    "pmcid": "PMC10125902",
                    "type": [
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                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "methylR: a graphical interface for comprehensive DNA methylation array data analysis",
                        "abstract": "Motivation: DNA methylation analysis using arrays is a widely used method in research and clinical studies to study Epigenetics. Although several packages have been published to incur the results, most of them require a deep computational knowledge to perform the analysis. To resolve the limitation and to offer an easily accessible solution for researchers, we developed methylR a graphical tool that can analyze not only the raw data but also performs different downstream analyses with a few mouse clicks. Results: We used standard and established open-source published packages or pipelines in methylR. We evaluated a publicly available dataset and compared the published results with those obtained with our tool. We implemented eight downstream analysis modules that can perform multidimensional analyses to pathway enrichment. Although the main application is designed for Illumina DNA methylation array data analysis, we made the accessory modules suitable for other kinds of data analysis as well. Availability and implementation: Freely available at Github: https://github.com/JD2112/methylr; Webserver: https://methylr.research.liu.se.",
                        "date": "2023-04-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Volpe M."
                            },
                            {
                                "name": "Das J."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Jyotirmoy Das",
                    "email": "jyotirmoy.das@liu.se",
                    "url": null,
                    "orcidid": "https://orcid.org/0000-0002-5649-4658",
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [],
                    "note": null
                }
            ],
            "community": null,
            "owner": "Pub2Tools",
            "additionDate": "2023-09-15T19:04:20.592395Z",
            "lastUpdate": "2023-09-15T19:04:20.595012Z",
            "editPermission": {
                "type": "public",
                "authors": []
            },
            "validated": 0,
            "homepage_status": 0,
            "elixir_badge": 0,
            "confidence_flag": "tool"
        }
    ]
}