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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",
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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,
                    "orcidid": "https://orcid.org/0000-0003-1591-4721",
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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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            "function": [
                {
                    "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"
                }
            ],
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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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                    "url": null,
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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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            "relation": [],
            "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"
                },
                {
                    "uri": "http://edamontology.org/topic_3794",
                    "term": "RNA immunoprecipitation"
                }
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            "operatingSystem": [],
            "language": [
                "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",
                    "url": null,
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                {
                    "name": "Rolf Renne",
                    "email": "rrenne@ufl.edu",
                    "url": null,
                    "orcidid": "https://orcid.org/0000-0001-7391-8806",
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            "owner": "Pub2Tools",
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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
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            ],
            "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",
                        "citationCount": 1,
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                            {
                                "name": "Wang R.H."
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                            {
                                "name": "Yang S."
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                            {
                                "name": "Liu Z."
                            },
                            {
                                "name": "Zhang Y."
                            },
                            {
                                "name": "Wang X."
                            },
                            {
                                "name": "Xu Z."
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                            {
                                "name": "Wang J."
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                            {
                                "name": "Li S.C."
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                        "journal": "Nucleic Acids Research"
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                    "name": "Jianping Wang",
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            "description": "An R package to streamline the process of investigating the adaptations of parasites' codon usage bias.",
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                            "uri": "http://edamontology.org/operation_0284",
                            "term": "Codon usage table generation"
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                        {
                            "uri": "http://edamontology.org/operation_0285",
                            "term": "Codon usage table comparison"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0335",
                            "term": "Formatting"
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                            "term": "Essential dynamics"
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                {
                    "uri": "http://edamontology.org/topic_0203",
                    "term": "Gene expression"
                },
                {
                    "uri": "http://edamontology.org/topic_3302",
                    "term": "Parasitology"
                },
                {
                    "uri": "http://edamontology.org/topic_3945",
                    "term": "Molecular evolution"
                },
                {
                    "uri": "http://edamontology.org/topic_3500",
                    "term": "Zoology"
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                    "term": "Model organisms"
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                {
                    "doi": "10.12688/f1000research.143223.1",
                    "pmid": "38021405",
                    "pmcid": "PMC10682597",
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                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "parazitCUB: An R package to streamline the process of investigating the adaptations of parasites' codon usage bias",
                        "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",
                        "date": "2023-01-01T00:00:00Z",
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                        "authors": [
                            {
                                "name": "Anwar A.M."
                            },
                            {
                                "name": "Bayoumi S."
                            },
                            {
                                "name": "Elzalabany S."
                            },
                            {
                                "name": "Magdeldin S."
                            },
                            {
                                "name": "Ahmed A.E."
                            }
                        ],
                        "journal": "F1000Research"
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                    "name": "Amr E. Ahmed",
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        {
            "name": "Lion Localizer",
            "description": "Software tool for inferring the provenance of lions (Panthera leo) using mitochondrial DNA.",
            "homepage": "https://lionlocalizer.org",
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                {
                    "operation": [
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                            "uri": "http://edamontology.org/operation_3192",
                            "term": "Sequence trimming"
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                            "uri": "http://edamontology.org/operation_0224",
                            "term": "Query and retrieval"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0487",
                            "term": "Haplotype mapping"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
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            ],
            "toolType": [
                "Web application"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_3168",
                    "term": "Sequencing"
                },
                {
                    "uri": "http://edamontology.org/topic_0654",
                    "term": "DNA"
                },
                {
                    "uri": "http://edamontology.org/topic_0102",
                    "term": "Mapping"
                },
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                    "uri": "http://edamontology.org/topic_0621",
                    "term": "Model organisms"
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                "Mac",
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                {
                    "doi": "10.1093/JHERED/ESAD072",
                    "pmid": "37952226",
                    "pmcid": null,
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                    "version": null,
                    "note": null,
                    "metadata": {
                        "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",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Au W.C."
                            },
                            {
                                "name": "Dures S.G."
                            },
                            {
                                "name": "Ishida Y."
                            },
                            {
                                "name": "Green C.E."
                            },
                            {
                                "name": "Zhao K."
                            },
                            {
                                "name": "Ogden R."
                            },
                            {
                                "name": "Roca A.L."
                            }
                        ],
                        "journal": "Journal of Heredity"
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                }
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                    "name": "Alfred L Roca",
                    "email": "roca@illinois.edu",
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                },
                {
                    "name": "Wesley C Au",
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        {
            "name": "MetGENE",
            "description": "Gene-centric metabolomics information retrieval tool.",
            "homepage": "https://bdcw.org/MetGENE/index.php",
            "biotoolsID": "metgene",
            "biotoolsCURIE": "biotools:metgene",
            "version": [],
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                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_2422",
                            "term": "Data retrieval"
                        },
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                            "uri": "http://edamontology.org/operation_3436",
                            "term": "Aggregation"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3695",
                            "term": "Filtering"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3803",
                            "term": "Natural product identification"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
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                }
            ],
            "toolType": [
                "Database portal"
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            "topic": [
                {
                    "uri": "http://edamontology.org/topic_3172",
                    "term": "Metabolomics"
                },
                {
                    "uri": "http://edamontology.org/topic_0154",
                    "term": "Small molecules"
                },
                {
                    "uri": "http://edamontology.org/topic_0602",
                    "term": "Molecular interactions, pathways and networks"
                },
                {
                    "uri": "http://edamontology.org/topic_0625",
                    "term": "Genotype and phenotype"
                },
                {
                    "uri": "http://edamontology.org/topic_3067",
                    "term": "Anatomy"
                }
            ],
            "operatingSystem": [
                "Mac",
                "Linux",
                "Windows"
            ],
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                "PHP",
                "R"
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            "cost": "Free of charge",
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            "link": [
                {
                    "url": "https://github.com/metabolomicsworkbench/MetGENE",
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                        "Repository"
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            ],
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            "publication": [
                {
                    "doi": "10.1093/GIGASCIENCE/GIAD089",
                    "pmid": "37983749",
                    "pmcid": "PMC10659118",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "MetGENE: gene-centric metabolomics information retrieval tool",
                        "abstract": "Background: Biomedical research often involves contextual integration of multimodal and multiomic data in search of mechanisms for improved diagnosis, treatment, and monitoring. Researchers need to access information from diverse sources, comprising data in various and sometimes incongruent formats. The downstream processing of the data to decipher mechanisms by reconstructing networks and developing quantitative models warrants considerable effort. Results: MetGENE is a knowledge-based, gene-centric data aggregator that hierarchically retrieves information about the gene(s), their related pathway(s), reaction(s), metabolite(s), and metabolomic studies from standard data repositories under one dashboard to enable ease of access through centralization of relevant information. We note that MetGENE focuses only on those genes that encode for proteins directly associated with metabolites. All other gene–metabolite associations are beyond the current scope of MetGENE. Further, the information can be contextualized by filtering by species, anatomy (tissue), and condition (disease or phenotype). Conclusions: MetGENE is an open-source tool that aggregates metabolite information for a given gene(s) and presents them in different computable formats (e.g., JSON) for further integration with other omics studies. MetGENE is available at https://bdcw.org/MetGENE/index.php.",
                        "date": "2023-01-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Srinivasan S."
                            },
                            {
                                "name": "Maurya M.R."
                            },
                            {
                                "name": "Ramachandran S."
                            },
                            {
                                "name": "Fahy E."
                            },
                            {
                                "name": "Subramaniam S."
                            }
                        ],
                        "journal": "GigaScience"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Shankar Subramaniam",
                    "email": "shsubramaniam@ucsd.edu",
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                },
                {
                    "name": "Sumana Srinivasan",
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        },
        {
            "name": "MESPEUS",
            "description": "Database of metal coordination groups in proteins.",
            "homepage": "http://mespeus.nchu.edu.tw/",
            "biotoolsID": "mespeus",
            "biotoolsCURIE": "biotools:mespeus",
            "version": [],
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                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3898",
                            "term": "Metal-binding site prediction"
                        },
                        {
                            "uri": "http://edamontology.org/operation_1834",
                            "term": "Protein-metal contact calculation"
                        },
                        {
                            "uri": "http://edamontology.org/operation_1831",
                            "term": "Metal-bound cysteine detection"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3431",
                            "term": "Deposition"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0337",
                            "term": "Visualisation"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Database portal"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0078",
                    "term": "Proteins"
                },
                {
                    "uri": "http://edamontology.org/topic_3071",
                    "term": "Biological databases"
                },
                {
                    "uri": "http://edamontology.org/topic_0593",
                    "term": "NMR"
                },
                {
                    "uri": "http://edamontology.org/topic_2828",
                    "term": "X-ray diffraction"
                },
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                    "uri": "http://edamontology.org/topic_0154",
                    "term": "Small molecules"
                }
            ],
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            "publication": [
                {
                    "doi": "10.1093/NAR/GKAD1009",
                    "pmid": "37941148",
                    "pmcid": "PMC10767821",
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                    "note": null,
                    "metadata": {
                        "title": "MESPEUS:ã database of metal coordination groups in proteins",
                        "abstract": "MESPEUS isã freelyãccessible database which uses carefully selected metal coordination groups found in metalloprotein str uct ures taken from the Protein Data Bãnk. T he datãbase contãins geometrical information of metal sites within proteins, including 40 metãl t ypes. In order to completely determine the metal coordination, the symmetry-related units ofã given protein str uct ureãre taken intoãccountãndãre generated using theãppropriate space group symmetry operations. This permitsã more complete description of the metal coordination geometry by includingãll coordinatingãtoms. The user-friendly web interfaceãllows users to directly search forã metal site of interest using se v eral useful options, including searching for metal elements, metal-donor distances, coordination number, donor residue group,ãnd str uct ural resolution. These searches can be carried out singly or in combination. The details ofã metal siteãnd the metal site(s) in the whole str uct ure can be graphically displa y ed using the interactiv e w eb interfãce. MESPEUS isãutomatically updated monthly b y synchronizing with the PDB database. An in v estigation f or the Mg-ATP interaction is giv en to demonstrate how MESPEUS can be used to e xtract inf ormationãbout metal sites by selecting str uct ureãnd coordination feat ures. MESPEUS isã vãilableãt ht tp://mespeus.nc hu.edu.tw/.",
                        "date": "2024-01-05T00:00:00Z",
                        "citationCount": 1,
                        "authors": [
                            {
                                "name": "Lin G.-Y."
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                            {
                                "name": "Su Y.-C."
                            },
                            {
                                "name": "Huang Y.L."
                            },
                            {
                                "name": "Hsin K.-Y."
                            }
                        ],
                        "journal": "Nucleic Acids Research"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Kun-Yi Hsin",
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                {
                    "name": "Geng-Yu Lin",
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        },
        {
            "name": "DeepHLAPred",
            "description": "Deep learning-based method for non-classical HLA binder prediction.",
            "homepage": "http://www.biolscience.cn/DeepHLApred/",
            "biotoolsID": "deephlapred",
            "biotoolsCURIE": "biotools:deephlapred",
            "version": [],
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            "function": [
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                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_0252",
                            "term": "Peptide immunogenicity prediction"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0440",
                            "term": "Promoter prediction"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3435",
                            "term": "Standardisation and normalisation"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Web application"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_2830",
                    "term": "Immunoproteins and antigens"
                },
                {
                    "uri": "http://edamontology.org/topic_3474",
                    "term": "Machine learning"
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                {
                    "uri": "http://edamontology.org/topic_0154",
                    "term": "Small molecules"
                }
            ],
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                "Windows"
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            "link": [
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            "publication": [
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                    "doi": "10.1186/S12864-023-09796-2",
                    "pmid": "37993812",
                    "pmcid": "PMC10666343",
                    "type": [],
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                    "note": null,
                    "metadata": {
                        "title": "DeepHLAPred: a deep learning-based method for non-classical HLA binder prediction",
                        "abstract": "Human leukocyte antigen (HLA) is closely involved in regulating the human immune system. Despite great advance in detecting classical HLA Class I binders, there are few methods or toolkits for recognizing non-classical HLA Class I binders. To fill in this gap, we have developed a deep learning-based tool called DeepHLAPred. The DeepHLAPred used electron-ion interaction pseudo potential, integer numerical mapping and accumulated amino acid frequency as initial representation of non-classical HLA binder sequence. The deep learning module was used to further refine high-level representations. The deep learning module comprised two parallel convolutional neural networks, each followed by maximum pooling layer, dropout layer, and bi-directional long short-term memory network. The experimental results showed that the DeepHLAPred reached the state-of-the-art performanceson the cross-validation test and the independent test. The extensive test demonstrated the rationality of the DeepHLAPred. We further analyzed sequence pattern of non-classical HLA class I binders by information entropy. The information entropy of non-classical HLA binder sequence implied sequence pattern to a certain extent. In addition, we have developed a user-friendly webserver for convenient use, which is available at http://www.biolscience.cn/DeepHLApred/ . The tool and the analysis is helpful to detect non-classical HLA Class I binder. The source code and data is available at https://github.com/tangxingyu0/DeepHLApred .",
                        "date": "2023-12-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Huang G."
                            },
                            {
                                "name": "Tang X."
                            },
                            {
                                "name": "Zheng P."
                            }
                        ],
                        "journal": "BMC Genomics"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Guohua Huang",
                    "email": "guohuahhn@163.com",
                    "url": null,
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                },
                {
                    "name": "Xingyu Tang",
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                    "note": null
                },
                {
                    "name": "Peijie Zheng",
                    "email": null,
                    "url": null,
                    "orcidid": null,
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                    "typeEntity": "Person",
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                    "note": null
                }
            ],
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            "owner": "Pub2Tools",
            "additionDate": "2024-04-19T10:04:52.539998Z",
            "lastUpdate": "2024-04-19T10:04:52.542062Z",
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            },
            "validated": 0,
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}