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        {
            "name": "ncRNADrug",
            "description": "Database for validated and predicted ncRNAs associated with drug resistance and targeted by drugs.",
            "homepage": "http://www.jianglab.cn/ncRNADrug",
            "biotoolsID": "ncrnadrug",
            "biotoolsCURIE": "biotools:ncrnadrug",
            "version": [],
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                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3223",
                            "term": "Differential gene expression profiling"
                        },
                        {
                            "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
                }
            ],
            "toolType": [
                "Database portal"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0659",
                    "term": "Functional, regulatory and non-coding RNA"
                },
                {
                    "uri": "http://edamontology.org/topic_0154",
                    "term": "Small molecules"
                },
                {
                    "uri": "http://edamontology.org/topic_2640",
                    "term": "Oncology"
                },
                {
                    "uri": "http://edamontology.org/topic_3373",
                    "term": "Drug development"
                },
                {
                    "uri": "http://edamontology.org/topic_3336",
                    "term": "Drug discovery"
                }
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            "publication": [
                {
                    "doi": "10.1093/NAR/GKAD1042",
                    "pmid": "37953323",
                    "pmcid": "PMC10767907",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "ncRNADrug:ã database for validatedãnd predicted ncRNAsãssociated with drug resistanceãnd targeted by drugs",
                        "abstract": "Drug resistance isã major barrier in cancer treatmentãndãnticancer drug de v elopment. Gro wing e vidence indicates that non-coding RNAs (ncR- NA s), especially microRNA s (miRNA s), long non-coding RNA s (lncRNA s)ãnd circular RNA s (circRNA s), pla y piv otal roles in cancer progression, therapy,ãnd drug resistance. Furthermore, ncRNAs ha v e been pro v en to be promising no v el therapeutic targets f or cancer treatment. R e v ers- ing dysregulated ncRNAs by drugs holds significant potentialãsãn effective therapeutic strategy for overcoming drug resistance. Therefore, w e de v eloped ncRNADrug,ãn integratedãnd comprehensive resource that records manually curatedãnd computationally predicted ncRNAsãssociated with drug resistance, ncRNAs targeted by drugs,ãs wellãs potential drug combinations for the treatment of resistant cancer. Cur- rently, ncRNADrug collects 29 551 experimentally validated entries involving 9195 ncRNAs (2248 miRNAs, 4145 lncRNAsãnd 2802 circRNAs)ãssociated with the drug resistance of 266 drugs,ãnd 32 969 entries in v olving 10 480 ncRNAs (4338 miRNAs, 6087 lncRNAsãnd 55 circRNAs) targeted by 965 drugs. Inãddition, ncRNADrugãlso containsãssociations between ncRNAsãnd drugs predicted from ncRNA expression profiles by differential expressionãnalysis. Altogether, ncRNADrug surpasses the existing related databases in both data volumeãnd functionality. It will beã useful resource for drug developmentãnd cancer treatment. ncRNADrug isãvailableãt http:// www.jianglab.cn/ ncRNADrug .",
                        "date": "2024-01-05T00:00:00Z",
                        "citationCount": 1,
                        "authors": [
                            {
                                "name": "Cao X."
                            },
                            {
                                "name": "Zhou X."
                            },
                            {
                                "name": "Hou F."
                            },
                            {
                                "name": "Huang Y.-E."
                            },
                            {
                                "name": "Yuan M."
                            },
                            {
                                "name": "Long M."
                            },
                            {
                                "name": "Chen S."
                            },
                            {
                                "name": "Lei W."
                            },
                            {
                                "name": "Zhu J."
                            },
                            {
                                "name": "Chen J."
                            },
                            {
                                "name": "Zhang T."
                            },
                            {
                                "name": "Guo A.-Y."
                            },
                            {
                                "name": "Jiang W."
                            }
                        ],
                        "journal": "Nucleic Acids Research"
                    }
                }
            ],
            "credit": [
                {
                    "name": "An-Yuan Guo",
                    "email": "guoanyuan@wchscu.cn",
                    "url": null,
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                {
                    "name": "Wei Jiang",
                    "email": "weijiang@nuaa.edu.cn",
                    "url": null,
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        {
            "name": "G-Aligner",
            "description": "Graph-based feature alignment method for untargeted LC-MS-based metabolomics.",
            "homepage": "https://github.com/CSi-Studio/G-Aligner",
            "biotoolsID": "g-aligner",
            "biotoolsCURIE": "biotools:g-aligner",
            "version": [],
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                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3937",
                            "term": "Feature extraction"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0447",
                            "term": "Sequence alignment validation"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3633",
                            "term": "Retention time prediction"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Workflow"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_3172",
                    "term": "Metabolomics"
                },
                {
                    "uri": "http://edamontology.org/topic_3520",
                    "term": "Proteomics experiment"
                },
                {
                    "uri": "http://edamontology.org/topic_0102",
                    "term": "Mapping"
                },
                {
                    "uri": "http://edamontology.org/topic_0081",
                    "term": "Structure analysis"
                }
            ],
            "operatingSystem": [],
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                "Python",
                "Java"
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            "publication": [
                {
                    "doi": "10.1186/S12859-023-05525-4",
                    "pmid": "37964228",
                    "pmcid": "PMC10644574",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "G-Aligner: a graph-based feature alignment method for untargeted LC–MS-based metabolomics",
                        "abstract": "Background: Liquid chromatography–mass spectrometry is widely used in untargeted metabolomics for composition profiling. In multi-run analysis scenarios, features of each run are aligned into consensus features by feature alignment algorithms to observe the intensity variations across runs. However, most of the existing feature alignment methods focus more on accurate retention time correction, while underestimating the importance of feature matching. None of the existing methods can comprehensively consider feature correspondences among all runs and achieve optimal matching. Results: To comprehensively analyze feature correspondences among runs, we propose G-Aligner, a graph-based feature alignment method for untargeted LC–MS data. In the feature matching stage, G-Aligner treats features and potential correspondences as nodes and edges in a multipartite graph, considers the multi-run feature matching problem an unbalanced multidimensional assignment problem, and provides three combinatorial optimization algorithms to find optimal matching solutions. In comparison with the feature alignment methods in OpenMS, MZmine2 and XCMS on three public metabolomics benchmark datasets, G-Aligner achieved the best feature alignment performance on all the three datasets with up to 9.8% and 26.6% increase in accurately aligned features and analytes, and helped all comparison software obtain more accurate results on their self-extracted features by integrating G-Aligner to their analysis workflow. G-Aligner is open-source and freely available at https://github.com/CSi-Studio/G-Aligner under a permissive license. Benchmark datasets, manual annotation results, evaluation methods and results are available at https://doi.org/10.5281/zenodo.8313034 Conclusions: In this study, we proposed G-Aligner to improve feature matching accuracy for untargeted metabolomics LC–MS data. G-Aligner comprehensively considered potential feature correspondences between all runs, converting the feature matching problem as a multidimensional assignment problem (MAP). In evaluations on three public metabolomics benchmark datasets, G-Aligner achieved the highest alignment accuracy on manual annotated and popular software extracted features, proving the effectiveness and robustness of the algorithm.",
                        "date": "2023-12-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Wang R."
                            },
                            {
                                "name": "Lu M."
                            },
                            {
                                "name": "An S."
                            },
                            {
                                "name": "Wang J."
                            },
                            {
                                "name": "Yu C."
                            }
                        ],
                        "journal": "BMC Bioinformatics"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Changbin Yu",
                    "email": "yu_lab@sdfmu.edu.cn",
                    "url": null,
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                },
                {
                    "name": "Ruimin Wang",
                    "email": null,
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        {
            "name": "RVdb",
            "description": "A comprehensive rhinovirus database and analysis platform integrating many online analysis functions.",
            "homepage": "http://rvdb.mgc.ac.cn",
            "biotoolsID": "rvdb",
            "biotoolsCURIE": "biotools:rvdb",
            "version": [],
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            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_0292",
                            "term": "Sequence alignment"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0323",
                            "term": "Phylogenetic inference"
                        },
                        {
                            "uri": "http://edamontology.org/operation_2421",
                            "term": "Database search"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Database portal",
                "Web application"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_3305",
                    "term": "Public health and epidemiology"
                },
                {
                    "uri": "http://edamontology.org/topic_3293",
                    "term": "Phylogenetics"
                },
                {
                    "uri": "http://edamontology.org/topic_0199",
                    "term": "Genetic variation"
                },
                {
                    "uri": "http://edamontology.org/topic_3322",
                    "term": "Respiratory medicine"
                },
                {
                    "uri": "http://edamontology.org/topic_0780",
                    "term": "Plant biology"
                }
            ],
            "operatingSystem": [
                "Mac",
                "Linux",
                "Windows"
            ],
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            "cost": "Free of charge",
            "accessibility": "Open access",
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            "publication": [
                {
                    "doi": "10.1093/NAR/GKAD937",
                    "pmid": "37930838",
                    "pmcid": "PMC10768139",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "RVdb: a comprehensive resource and analysis platform for rhinovirus research",
                        "abstract": "Rhinovirus (RV), a prominent causative agent of both upper and lower respiratory diseases, ranks among the most prevalent human respiratory viruses. RV infections are associated with various illnesses, including colds, asthma exacerbations, croup and pneumonia, imposing significant and extended societal burdens. Characterized by a high mutation rate and genomic diversity, RV displays a diverse serological landscape, encompassing a total of 174 serotypes identified to date. Understanding RV genetic diversity is crucial for epidemiological surveillance and investigation of respiratory diseases. This study introduces a comprehensive and high-quality RV data resource, designated RVdb (http://rvdb.mgc.ac.cn), covering 26 909 currently identified RV strains, along with RV-related sequences, 3D protein structures and publications. Furthermore, this resource features a suite of web-based utilities optimized for easy browsing and searching, as well as automatic sequence annotation, multiple sequence alignment (MSA), phylogenetic tree construction, RVdb BLAST and a serotyping pipeline. Equipped with a user-friendly interface and integrated online bioinformatics tools, RVdb provides a convenient and powerful platform on which to analyse the genetic characteristics of RVs. Additionally, RVdb also supports the efforts of virologists and epidemiologists to monitor and trace both existing and emerging RV-related infectious conditions in a public health context.",
                        "date": "2024-01-05T00:00:00Z",
                        "citationCount": 1,
                        "authors": [
                            {
                                "name": "Zhao P."
                            },
                            {
                                "name": "Zhou S."
                            },
                            {
                                "name": "Xu P."
                            },
                            {
                                "name": "Su H."
                            },
                            {
                                "name": "Han Y."
                            },
                            {
                                "name": "Dong J."
                            },
                            {
                                "name": "Sui H."
                            },
                            {
                                "name": "Li X."
                            },
                            {
                                "name": "Hu Y."
                            },
                            {
                                "name": "Wu Z."
                            },
                            {
                                "name": "Liu B."
                            },
                            {
                                "name": "Zhang T."
                            },
                            {
                                "name": "Yang F."
                            }
                        ],
                        "journal": "Nucleic Acids Research"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Bo Liu",
                    "email": null,
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                },
                {
                    "name": "Ting Zhang",
                    "email": "zhangting@ipbcams.ac.cn",
                    "url": null,
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                {
                    "name": "Fan Yang",
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            "owner": "Pub2Tools",
            "additionDate": "2024-04-26T12:49:02.139884Z",
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        {
            "name": "Hybkit",
            "description": "Python API and command-line toolkit for hybrid sequence data from chimeric RNA methods.",
            "homepage": "https://pypi.org/project/hybkit/",
            "biotoolsID": "hybkit",
            "biotoolsCURIE": "biotools:hybkit",
            "version": [],
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            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_0463",
                            "term": "miRNA target prediction"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3792",
                            "term": "miRNA expression analysis"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0337",
                            "term": "Visualisation"
                        },
                        {
                            "uri": "http://edamontology.org/operation_1812",
                            "term": "Parsing"
                        }
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                    "input": [],
                    "output": [],
                    "note": null,
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            ],
            "toolType": [
                "Command-line tool"
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            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0659",
                    "term": "Functional, regulatory and non-coding RNA"
                },
                {
                    "uri": "http://edamontology.org/topic_3170",
                    "term": "RNA-Seq"
                },
                {
                    "uri": "http://edamontology.org/topic_3382",
                    "term": "Imaging"
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                {
                    "uri": "http://edamontology.org/topic_3794",
                    "term": "RNA immunoprecipitation"
                }
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            "operatingSystem": [],
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                "Python"
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            "link": [
                {
                    "url": "http://github.com/RenneLab/hybkit",
                    "type": [
                        "Repository"
                    ],
                    "note": null
                }
            ],
            "download": [],
            "documentation": [
                {
                    "url": "http://hybkit.readthedocs.io",
                    "type": [
                        "User manual"
                    ],
                    "note": null
                }
            ],
            "publication": [
                {
                    "doi": "10.1093/BIOINFORMATICS/BTAD721",
                    "pmid": "38006335",
                    "pmcid": "PMC10701094",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Hybkit: A Python API and command-line toolkit for hybrid sequence data from chimeric RNA methods",
                        "abstract": "Summary: Experimental methods using microRNA/target ligation have recently provided significant insights into microRNA functioning through generation of chimeric (hybrid) RNA sequences. Here, we introduce Hybkit, a Python3 API, and command-line toolkit for analysis of hybrid sequence data in the \"hyb\"file format to enable customizable evaluation and annotation of hybrid characteristics. The Hybkit API includes a suite of python objects for developing custom analyses of hybrid data as well as miRNA-specific analysis methods, built-in plotting of analysis results, and incorporation of predicted miRNA/target interactions in Vienna format.",
                        "date": "2023-12-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Stribling D."
                            },
                            {
                                "name": "Gay L.A."
                            },
                            {
                                "name": "Renne R."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Daniel Stribling",
                    "email": "ds@ufl.edu",
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                {
                    "name": "Rolf Renne",
                    "email": "rrenne@ufl.edu",
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                    "orcidid": "https://orcid.org/0000-0001-7391-8806",
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        {
            "name": "PhageScope",
            "description": "Annotated bacteriophage database with automatic analyses and visualizations.",
            "homepage": "https://phagescope.deepomics.org",
            "biotoolsID": "phagescope",
            "biotoolsCURIE": "biotools:phagescope",
            "version": [],
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            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3460",
                            "term": "Taxonomic classification"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0362",
                            "term": "Genome annotation"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0337",
                            "term": "Visualisation"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Database portal"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0637",
                    "term": "Taxonomy"
                },
                {
                    "uri": "http://edamontology.org/topic_0622",
                    "term": "Genomics"
                },
                {
                    "uri": "http://edamontology.org/topic_0798",
                    "term": "Mobile genetic elements"
                },
                {
                    "uri": "http://edamontology.org/topic_3168",
                    "term": "Sequencing"
                },
                {
                    "uri": "http://edamontology.org/topic_0203",
                    "term": "Gene expression"
                }
            ],
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                "Windows"
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            "publication": [
                {
                    "doi": "10.1093/NAR/GKAD979",
                    "pmid": "37904614",
                    "pmcid": "PMC10767790",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "PhageScope: a well-annotated bacteriophage database with automatic analyses and visualizations",
                        "abstract": "Bacteriophages are viruses that infect bacteria or archaea. Understanding the diverse and intricate genomic architectures of phages is essential to study microbial ecosystems and develop phage therapy strategies. However, the existing phage databases are short of meticulous annotations. To this end, we propose PhageScope (https://phagescope.deepomics.org), an online phage database with comprehensive annotations. PhageScope harbors a collection of 873 718 phage sequences from various sources. Applying fifteen state-of-the-art tools to perform systematic annotations and analyses, PhageScope provides annotations on genome completeness, host range, lifestyle information, taxonomy classification, nine types of structural and functional genetic elements, and three types of comparative genomic studies for curated phages. Additionally, PhageScope incorporates automatic analyses and visualizations for curated and customized phages, serving as an efficient platform for phage study.",
                        "date": "2024-01-05T00:00:00Z",
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                        "abstract": "Examining the intricate association between parasites and their hosts, particularly at the codon level, assumes paramount importance in comprehending evolutionary processes and forecasting the characteristics of novel parasites. While diverse metrics and statistical analyses are available to explore codon usage bias (CUB), there presently exists no dedicated tool for examining the co-adaptation of codon usage between parasites and hosts. Therefore, we introduce the parazitCUB R package to address this challenge in a scalable and efficient manner, as it is capable of handling extensive datasets and simultaneously analyzing of multiple parasites with optimized performance. parazitCUB enables the elucidation of parasite-host interactions and the evolutionary patterns of parasites through the implementation of various indices, cluster analysis, multivariate analysis, and data visualization techniques. The tool can be accessed at the following location: https://github.com/AliYoussef96/parazitCUB",
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                                "uri": "http://edamontology.org/data_0006",
                                "term": "Data"
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                        }
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                    "note": "Returns a list of xrefs that map to a given identifier, and data source. Optionally restrict results to a given data source.",
                    "cmd": null
                },
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_2422",
                            "term": "Data retrieval"
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                                "term": "Species name"
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                                "uri": "http://edamontology.org/data_0842",
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                        }
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                    "note": "Returns `true` or `false` based on whether or not an xref exists in the database given an identifier, data source, and organism.",
                    "cmd": null
                }
            ],
            "toolType": [
                "Web API"
            ],
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                    "uri": "http://edamontology.org/topic_3345",
                    "term": "Data identity and mapping"
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                {
                    "uri": "http://edamontology.org/topic_3325",
                    "term": "Rare diseases"
                }
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                "Windows",
                "Mac"
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                    "metadata": {
                        "title": "The BridgeDb framework: Standardized access to gene, protein and metabolite identifier mapping services",
                        "abstract": "Background: Many complementary solutions are available for the identifier mapping problem. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services.Results: Here we present BridgeDb, a software framework for gene, protein and metabolite identifier mapping. This framework provides a standardized interface layer through which bioinformatics tools can be connected to different identifier mapping services. This approach makes it easier for tool developers to support identifier mapping. Mapping services can be combined or merged to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb provides its own ready-to-go mapping services, both in webservice and local database forms. However, the framework is intended for customization and adaptation to any identifier mapping service. BridgeDb has already been integrated into several bioinformatics applications.Conclusion: By uncoupling bioinformatics tools from mapping services, BridgeDb improves capability and flexibility of those tools. All described software is open source and available at http://www.bridgedb.org. © 2010 van Iersel et al; licensee BioMed Central Ltd.",
                        "date": "2010-01-04T00:00:00Z",
                        "citationCount": 123,
                        "authors": [
                            {
                                "name": "van Iersel M.P."
                            },
                            {
                                "name": "Pico A.R."
                            },
                            {
                                "name": "Kelder T."
                            },
                            {
                                "name": "Gao J."
                            },
                            {
                                "name": "Ho I."
                            },
                            {
                                "name": "Hanspers K."
                            },
                            {
                                "name": "Conklin B.R."
                            },
                            {
                                "name": "Evelo C.T."
                            }
                        ],
                        "journal": "BMC Bioinformatics"
                    }
                }
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        {
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            "description": "Software tool for inferring the provenance of lions (Panthera leo) using mitochondrial DNA.",
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                            "term": "Haplotype mapping"
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                    "term": "Sequencing"
                },
                {
                    "uri": "http://edamontology.org/topic_0654",
                    "term": "DNA"
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                    "term": "Mapping"
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                        "title": "Lion Localizer: A software tool for inferring the provenance of lions (Panthera leo) using mitochondrial DNA",
                        "abstract": "The illegal poaching of lions for their body parts poses a severe threat to lion populations across Africa. Poaching accounts for 35% of all human-caused lion deaths, with 51% attributed to retaliatory killings following livestock predation. In nearly half of the retaliatory killings, lion body parts are removed, suggesting that high demand for lion body parts may fuel killings attributed to human-lion conflict. Trafficked items are often confiscated in transit or destination countries far from their country of origin. DNA from lion parts may in some cases be the only available means for examining their geographic origins. In this paper, we present the Lion Localizer, a full-stack software tool that houses a comprehensive database of lion mitochondrial DNA (mtDNA) sequences sourced from previously published studies. The database covers 146 localities from across the African continent and India, providing information on the potential provenance of seized lion body parts. Lion mtDNA sequences of 350 or 1,140 bp corresponding to the cytochrome b region can be generated from lion products and queried against the Lion Localizer database. Using the query sequence, the Lion Localizer generates a listing of exact or partial matches, which are displayed on an interactive map of Africa. This allows for the rapid identification of potential regions and localities where lions have been or are presently being targeted by poachers. By examining the potential provenance of lion samples, the Lion Localizer serves as a valuable resource in the fight against lion poaching. The software is available at https://lionlocalizer.org.",
                        "date": "2024-03-01T00:00:00Z",
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                        "authors": [
                            {
                                "name": "Au W.C."
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                            {
                                "name": "Dures S.G."
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                            {
                                "name": "Ishida Y."
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                            {
                                "name": "Green C.E."
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                            {
                                "name": "Zhao K."
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                            {
                                "name": "Ogden R."
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                            {
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                        "journal": "Journal of Heredity"
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