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            "name": "MCPtaggR",
            "description": "R package for accurate genotype calling in reduced representation sequencing data by eliminating error-prone markers based on genome comparison.",
            "homepage": "https://github.com/tomoyukif/MCPtaggR",
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                            "uri": "http://edamontology.org/operation_3196",
                            "term": "Genotyping"
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                            "uri": "http://edamontology.org/operation_3933",
                            "term": "Demultiplexing"
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                            "uri": "http://edamontology.org/operation_0484",
                            "term": "SNP detection"
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                        {
                            "uri": "http://edamontology.org/operation_0524",
                            "term": "De-novo assembly"
                        }
                    ],
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                    "note": null,
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                {
                    "uri": "http://edamontology.org/topic_0625",
                    "term": "Genotype and phenotype"
                },
                {
                    "uri": "http://edamontology.org/topic_0780",
                    "term": "Plant biology"
                },
                {
                    "uri": "http://edamontology.org/topic_3168",
                    "term": "Sequencing"
                },
                {
                    "uri": "http://edamontology.org/topic_2885",
                    "term": "DNA polymorphism"
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                    "uri": "http://edamontology.org/topic_3175",
                    "term": "Structural variation"
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                    "url": "https://tomoyukif.github.io/MCPtaggR/",
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                {
                    "doi": "10.1093/DNARES/DSAD027",
                    "pmid": "38134958",
                    "pmcid": "PMC10799318",
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                    "metadata": {
                        "title": "MCPtaggR: R package for accurate genotype calling in reduced representation sequencing data by eliminating error-prone markers based on genome comparison",
                        "abstract": "Reduced representation sequencing (RRS) offers cost-effective, high-throughput genotyping platforms such as genotyping-by-sequencing (GBS). RRS reads are typically mapped onto a reference genome. However, mapping reads harbouring mismatches against the reference can potentially result in mismapping and biased mapping, leading to the detection of error-prone markers that provide incorrect genotype information. We established a genotype-calling pipeline named mappable collinear polymorphic tag genotyping (MCPtagg) to achieve accurate genotyping by eliminating error-prone markers. MCPtagg was designed for the RRS-based genotyping of a population derived from a biparental cross. The MCPtagg pipeline filters out error-prone markers prior to genotype calling based on marker collinearity information obtained by comparing the genome sequences of the parents of a population to be genotyped. A performance evaluation on real GBS data from a rice F2 population confirmed its effectiveness. Furthermore, our performance test using a genome assembly that was obtained by genome sequence polishing on an available genome assembly suggests that our pipeline performs well with converted genomes, rather than necessitating de novo assembly. This demonstrates its flexibility and scalability. The R package, MCPtaggR, was developed to provide functions for the pipeline and is available at https://github.com/tomoyukif/MCPtaggR.",
                        "date": "2024-02-01T00:00:00Z",
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                        "authors": [
                            {
                                "name": "Furuta T."
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                            {
                                "name": "Yamamoto T."
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                        "journal": "DNA Research"
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                    "name": "Tomoyuki Furuta",
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                            "uri": "http://edamontology.org/operation_3938",
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                            "uri": "http://edamontology.org/operation_0331",
                            "term": "Variant effect prediction"
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                            "uri": "http://edamontology.org/operation_3227",
                            "term": "Variant calling"
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                    "uri": "http://edamontology.org/topic_2640",
                    "term": "Oncology"
                },
                {
                    "uri": "http://edamontology.org/topic_3577",
                    "term": "Personalised medicine"
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                {
                    "uri": "http://edamontology.org/topic_0199",
                    "term": "Genetic variation"
                },
                {
                    "uri": "http://edamontology.org/topic_0634",
                    "term": "Pathology"
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                    "uri": "http://edamontology.org/topic_3474",
                    "term": "Machine learning"
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            "documentation": [
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                    "url": "https://loschmidt.chemi.muni.cz/predictonco/help",
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                {
                    "doi": "10.1093/BIB/BBAD441",
                    "pmid": "38066711",
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                    "metadata": {
                        "title": "PredictONCO: A web tool supporting decision-making in precision oncology by extending the bioinformatics predictions with advanced computing and machine learning",
                        "abstract": "PredictONCO 1.0 is a unique web server that analyzes effects of mutations on proteins frequently altered in various cancer types. The server can assess the impact of mutations on the protein sequential and structural properties and apply a virtual screening to identify potential inhibitors that could be used as a highly individualized therapeutic approach, possibly based on the drug repurposing. PredictONCO integrates predictive algorithms and state-of-the-art computational tools combined with information from established databases. The user interface was carefully designed for the target specialists in precision oncology, molecular pathology, clinical genetics and clinical sciences. The tool summarizes the effect of the mutation on protein stability and function and currently covers 44 common oncological targets. The binding affinities of Food and Drug Administration/ European Medicines Agency -approved drugs with the wild-type and mutant proteins are calculated to facilitate treatment decisions. The reliability of predictions was confirmed against 108 clinically validated mutations. The server provides a fast and compact output, ideal for the often time-sensitive decision-making process in oncology. Three use cases of missense mutations, (i) K22A in cyclin-dependent kinase 4 identified in melanoma, (ii) E1197K mutation in anaplastic lymphoma kinase 4 identified in lung carcinoma and (iii) V765A mutation in epidermal growth factor receptor in a patient with congenital mismatch repair deficiency highlight how the tool can increase levels of confidence regarding the pathogenicity of the variants and identify the most effective inhibitors. The server is available at https://loschmidt.chemi.muni.cz/predictonco.",
                        "date": "2024-01-01T00:00:00Z",
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                        "authors": [
                            {
                                "name": "Stourac J."
                            },
                            {
                                "name": "Borko S."
                            },
                            {
                                "name": "Khan R.T."
                            },
                            {
                                "name": "Pokorna P."
                            },
                            {
                                "name": "Dobias A."
                            },
                            {
                                "name": "Planas-Iglesias J."
                            },
                            {
                                "name": "Mazurenko S."
                            },
                            {
                                "name": "Pinto G."
                            },
                            {
                                "name": "Szotkowska V."
                            },
                            {
                                "name": "Sterba J."
                            },
                            {
                                "name": "Slaby O."
                            },
                            {
                                "name": "Damborsky J."
                            },
                            {
                                "name": "Bednar D."
                            }
                        ],
                        "journal": "Briefings in Bioinformatics"
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                }
            ],
            "credit": [
                {
                    "name": "Jiri Damborsky",
                    "email": "jiri@chemi.muni.cz",
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                    "name": "David Bednar",
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        {
            "name": "Scipion-chem",
            "description": "An open platform for virtual drug screening.",
            "homepage": "https://github.com/scipion-chem",
            "biotoolsID": "scipion_chem",
            "biotoolsCURIE": "biotools:scipion_chem",
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                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3938",
                            "term": "Virtual screening"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3899",
                            "term": "Protein-protein docking"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0416",
                            "term": "Epitope mapping"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
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            ],
            "toolType": [
                "Plug-in"
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            "topic": [
                {
                    "uri": "http://edamontology.org/topic_2275",
                    "term": "Molecular modelling"
                },
                {
                    "uri": "http://edamontology.org/topic_3336",
                    "term": "Drug discovery"
                },
                {
                    "uri": "http://edamontology.org/topic_0202",
                    "term": "Pharmacology"
                },
                {
                    "uri": "http://edamontology.org/topic_0769",
                    "term": "Workflows"
                },
                {
                    "uri": "http://edamontology.org/topic_2258",
                    "term": "Cheminformatics"
                }
            ],
            "operatingSystem": [
                "Mac",
                "Linux",
                "Windows"
            ],
            "language": [
                "Python"
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            "documentation": [
                {
                    "url": "https://scipion-chem.github.io/docs/publications/scipion-chem_vds",
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                    "note": null
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            ],
            "publication": [
                {
                    "doi": "10.1021/ACS.JCIM.3C01085",
                    "pmid": "38052452",
                    "pmcid": "PMC10751785",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Scipion-Chem: An Open Platform for Virtual Drug Screening",
                        "abstract": "Virtual drug screening (VDS) tackles the problem of drug discovery by computationally reducing the number of potential pharmacological molecules that need to be tested experimentally to find a new drug. To do so, several approaches have been developed through the years, typically focusing on either the physicochemical characteristics of the receptor structure (structure-based virtual screening) or those of the potential ligands (ligand-based virtual screening). Scipion is a workflow engine well suited for structural studies of biological macromolecules. Here, we present Scipion-chem, a new branch oriented to VDS. A total of 11 plugins have already been integrated from the most common programs used in the field. They can be used through the Scipion graphical user interface to execute and analyze typical VDS tasks. In addition, we have developed several consensus protocols that combine results from the different integrated programs to generate more robust predictions. Backstage, Scipion also facilitates the interoperability of those different software packages while tracking all of the intermediate files, parameters, and user decisions. In summary, in this article, we present Scipion-chem. This accessible, interoperable, and traceable platform provides the user with all of the tools to carry out a successful VDS workflow. Scipion-chem is openly available at https://github.com/scipion-chem.",
                        "date": "2023-12-25T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Del Hoyo D."
                            },
                            {
                                "name": "Salinas M."
                            },
                            {
                                "name": "Lomas A."
                            },
                            {
                                "name": "Ulzurrun E."
                            },
                            {
                                "name": "Campillo N.E."
                            },
                            {
                                "name": "Sorzano C.O."
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                        ],
                        "journal": "Journal of Chemical Information and Modeling"
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                    "name": "Daniel Del Hoyo",
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            "name": "TCGAplot",
            "description": "An R package for integrative pan-cancer analysis and visualization of TCGA multi-omics data.",
            "homepage": "https://github.com/tjhwangxiong/TCGAplot",
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                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_2436",
                            "term": "Gene-set enrichment analysis"
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                        {
                            "uri": "http://edamontology.org/operation_2940",
                            "term": "Scatter plot plotting"
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                        {
                            "uri": "http://edamontology.org/operation_3223",
                            "term": "Differential gene expression profiling"
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                        {
                            "uri": "http://edamontology.org/operation_3463",
                            "term": "Expression correlation analysis"
                        },
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                            "uri": "http://edamontology.org/operation_0490",
                            "term": "Dot plot plotting"
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            "toolType": [
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            "topic": [
                {
                    "uri": "http://edamontology.org/topic_2885",
                    "term": "DNA polymorphism"
                },
                {
                    "uri": "http://edamontology.org/topic_2640",
                    "term": "Oncology"
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                {
                    "uri": "http://edamontology.org/topic_0203",
                    "term": "Gene expression"
                },
                {
                    "uri": "http://edamontology.org/topic_0622",
                    "term": "Genomics"
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                {
                    "uri": "http://edamontology.org/topic_0602",
                    "term": "Molecular interactions, pathways and networks"
                }
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                "Linux",
                "Windows"
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                "R"
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            "download": [
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                    "url": "https://github.com/tjhwangxiong/TCGAplot/blob/main/vignettes/TCGAplot",
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            "publication": [
                {
                    "doi": "10.1186/S12859-023-05615-3",
                    "pmid": "38105215",
                    "pmcid": "PMC10726608",
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                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "TCGAplot: an R package for integrative pan-cancer analysis and visualization of TCGA multi-omics data",
                        "abstract": "Background: Pan-cancer analysis examines both the commonalities and heterogeneity among genomic and cellular alterations across numerous types of tumors. Pan-cancer analysis of gene expression, tumor mutational burden (TMB), microsatellite instability (MSI), and tumor immune microenvironment (TIME), and methylation becomes available based on the multi-omics data from The Cancer Genome Atlas Program (TCGA). Some online tools provide analysis of gene and protein expression, mutation, methylation, and survival for TCGA data. However, these online tools were either Uni-functional or were not able to perform analysis of user-defined functions. Therefore, we created the TCGAplot R package to facilitate perform pan-cancer analysis and visualization of the built-in multi-omic TCGA data. Results: TCGAplot provides several functions to perform pan-cancer paired/unpaired differential gene expression analysis, pan-cancer correlation analysis between gene expression and TMB, MSI, TIME, and promoter methylation. Functions for visualization include paired/unpaired boxplot, survival plot, ROC curve, heatmap, scatter, radar chart, and forest plot. Moreover, gene set based pan-cancer and tumor specific analyses were also available. Finally, all these built-in multi-omic data could be extracted for implementation for user-defined functions, making the pan-cancer analysis much more convenient.\\ Conclusions: We developed an R-package for integrative pan-cancer analysis and visualization of TCGA multi-omics data. The source code and pre-built package are available at GitHub (https://github.com/tjhwangxiong/TCGAplot).",
                        "date": "2023-12-01T00:00:00Z",
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                        "authors": [
                            {
                                "name": "Liao C."
                            },
                            {
                                "name": "Wang X."
                            }
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                        "journal": "BMC Bioinformatics"
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                    "name": "Xiong Wang",
                    "email": "wangxiong@tjh.tjmu.edu.cn",
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        {
            "name": "hictk",
            "description": "Blazing fast toolkit to work with .hic and .cool files",
            "homepage": "https://github.com/paulsengroup/hictk",
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                    "uri": "http://edamontology.org/topic_0091",
                    "term": "Bioinformatics"
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                {
                    "uri": "http://edamontology.org/topic_0080",
                    "term": "Sequence analysis"
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        {
            "name": "oggmap",
            "description": "Python package to extract gene ages per orthogroup and link them with single-cell RNA data.",
            "homepage": "https://github.com/kullrich/oggmap",
            "biotoolsID": "oggmap",
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                            "term": "Data retrieval"
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                            "uri": "http://edamontology.org/operation_0314",
                            "term": "Gene expression profiling"
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                    "uri": "http://edamontology.org/topic_3308",
                    "term": "Transcriptomics"
                },
                {
                    "uri": "http://edamontology.org/topic_0621",
                    "term": "Model organisms"
                },
                {
                    "uri": "http://edamontology.org/topic_0623",
                    "term": "Gene and protein families"
                },
                {
                    "uri": "http://edamontology.org/topic_2229",
                    "term": "Cell biology"
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                {
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                    "term": "Phylogenetics"
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                    "url": "https://oggmap.readthedocs.io/en/latest/",
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                        "User manual"
                    ],
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            ],
            "publication": [
                {
                    "doi": "10.1093/BIOINFORMATICS/BTAD657",
                    "pmid": "37952198",
                    "pmcid": "PMC10663984",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "oggmap: a Python package to extract gene ages per orthogroup and link them with single-cell RNA data",
                        "abstract": "Summary: For model species, single-cell RNA-based cell atlases are available. A good cell atlas includes all major stages in a species’ ontogeny, and soon, they will be standard even for nonmodel species. Here, we propose a Python package called oggmap, which allows for the easy extraction of an orthomap (gene ages per orthogroup) for any given query species from OrthoFinder and other gene family data resources, like homologous groups from eggNOG or PLAZA. oggmap provides extracted gene ages for more than thousand eukaryotic species which can be further used to calculate gene age-weighted expression data from scRNA sequencing objects using the Python Scanpy toolkit. Not limited to one transcriptome evolutionary index, oggmap can visualize the individual gene category (e.g. age class, nucleotide diversity bin) and their corresponding expression profiles to investigate scRNA-based cell type assignments in an evolutionary context.",
                        "date": "2023-11-01T00:00:00Z",
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                        "authors": [
                            {
                                "name": "Ullrich K.K."
                            },
                            {
                                "name": "Glytnasi N.E."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Kristian K Ullrich",
                    "email": "ullrich@evolbio.mpg.de",
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                    "name": "Nikoleta E Glytnasi",
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        {
            "name": "STOmicsDB",
            "description": "Comprehensive database for spatial transcriptomics data sharing, analysis and visualization.",
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            "biotoolsID": "stomicsdb",
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                            "term": "Database search"
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                            "uri": "http://edamontology.org/operation_3891",
                            "term": "Essential dynamics"
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                    ],
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            "toolType": [
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                    "uri": "http://edamontology.org/topic_3308",
                    "term": "Transcriptomics"
                },
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                    "uri": "http://edamontology.org/topic_3068",
                    "term": "Literature and language"
                },
                {
                    "uri": "http://edamontology.org/topic_3071",
                    "term": "Biological databases"
                },
                {
                    "uri": "http://edamontology.org/topic_3170",
                    "term": "RNA-Seq"
                },
                {
                    "uri": "http://edamontology.org/topic_0602",
                    "term": "Molecular interactions, pathways and networks"
                }
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            "documentation": [
                {
                    "url": "https://stomics-data-archive.readthedocs.io/en/latest/",
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                }
            ],
            "publication": [
                {
                    "doi": "10.1093/NAR/GKAD933",
                    "pmid": "37953328",
                    "pmcid": "PMC10767841",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization",
                        "abstract": "Recent technological developments in spatial transcriptomics allow researchers to measure gene expression of cells and their spatial locations at the single-cell level, generating detailed biological insight into biological processes. A comprehensive database could facilitate the sharing of spatial transcriptomic data and streamline the data acquisition process for researchers. Here, we present the Spatial TranscriptOmics DataBase (STOmicsDB), a database that serves as a one-stop hub for spatial transcriptomics. STOmicsDB integrates 218 manually curated datasets representing 17 species. We annotated cell types, identified spatial regions and genes, and performed cell-cell interaction analysis for these datasets. STOmicsDB features a user-friendly interface for the rapid visualization of millions of cells. To further facilitate the reusability and interoperability of spatial transcriptomic data, we developed standards for spatial transcriptomic data archiving and constructed a spatial transcriptomic data archiving system. Additionally, we offer a distinctive capability of customizing dedicated sub-databases in STOmicsDB for researchers, assisting them in visualizing their spatial transcriptomic analyses. We believe that STOmicsDB could contribute to research insights in the spatial transcriptomics field, including data archiving, sharing, visualization and analysis. STOmicsDB is freely accessible at https://db.cngb.org/stomics/.",
                        "date": "2024-01-05T00:00:00Z",
                        "citationCount": 6,
                        "authors": [
                            {
                                "name": "Xu Z."
                            },
                            {
                                "name": "Wang W."
                            },
                            {
                                "name": "Yang T."
                            },
                            {
                                "name": "Li L."
                            },
                            {
                                "name": "Ma X."
                            },
                            {
                                "name": "Chen J."
                            },
                            {
                                "name": "Wang J."
                            },
                            {
                                "name": "Huang Y."
                            },
                            {
                                "name": "Gould J."
                            },
                            {
                                "name": "Lu H."
                            },
                            {
                                "name": "Du W."
                            },
                            {
                                "name": "Sahu S.K."
                            },
                            {
                                "name": "Yang F."
                            },
                            {
                                "name": "Li Z."
                            },
                            {
                                "name": "Hu Q."
                            },
                            {
                                "name": "Hua C."
                            },
                            {
                                "name": "Hu S."
                            },
                            {
                                "name": "Liu Y."
                            },
                            {
                                "name": "Cai J."
                            },
                            {
                                "name": "You L."
                            },
                            {
                                "name": "Zhang Y."
                            },
                            {
                                "name": "Li Y."
                            },
                            {
                                "name": "Zeng W."
                            },
                            {
                                "name": "Chen A."
                            },
                            {
                                "name": "Wang B."
                            },
                            {
                                "name": "Liu L."
                            },
                            {
                                "name": "Chen F."
                            },
                            {
                                "name": "Ma K."
                            },
                            {
                                "name": "Xu X."
                            },
                            {
                                "name": "Wei X."
                            }
                        ],
                        "journal": "Nucleic Acids Research"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Kailong Ma",
                    "email": "makailong@cngb.org",
                    "url": null,
                    "orcidid": "https://orcid.org/0000-0002-9351-104X",
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                },
                {
                    "name": "Xun Xu",
                    "email": "xuxun@genomics.cn",
                    "url": null,
                    "orcidid": "https://orcid.org/0000-0002-5338-5173",
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                    "name": "Xiaofeng Wei",
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        {
            "name": "SAMtools",
            "description": "SAMtools and BCFtools are widely used programs for processing and analysing high-throughput sequencing data. They include tools for file format conversion and manipulation, sorting, querying, statistics, variant calling, and effect analysis amongst other methods.",
            "homepage": "http://www.htslib.org/",
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                            "term": "Editing"
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                        {
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                            "term": "Visualisation"
                        },
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                            "uri": "http://edamontology.org/operation_0335",
                            "term": "Formatting"
                        },
                        {
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                            "term": "Sorting"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3695",
                            "term": "Filtering"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0924",
                                "term": "Sequence trace"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_2572",
                                    "term": "BAM"
                                },
                                {
                                    "uri": "http://edamontology.org/format_2573",
                                    "term": "SAM"
                                },
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                                    "term": "CRAM"
                                }
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                        }
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                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0924",
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                                    "uri": "http://edamontology.org/format_2572",
                                    "term": "BAM"
                                },
                                {
                                    "uri": "http://edamontology.org/format_2573",
                                    "term": "SAM"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3462",
                                    "term": "CRAM"
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                        }
                    ],
                    "note": null,
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                }
            ],
            "toolType": [
                "Suite",
                "Command-line tool"
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            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0102",
                    "term": "Mapping"
                },
                {
                    "uri": "http://edamontology.org/topic_0080",
                    "term": "Sequence analysis"
                },
                {
                    "uri": "http://edamontology.org/topic_3168",
                    "term": "Sequencing"
                },
                {
                    "uri": "http://edamontology.org/topic_3325",
                    "term": "Rare diseases"
                }
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                "Windows",
                "Mac"
            ],
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                "Rare Disease",
                "Animal and Crop Genomics",
                "SAMtools"
            ],
            "maturity": "Mature",
            "cost": "Free of charge",
            "accessibility": "Open access",
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            "link": [
                {
                    "url": "https://github.com/samtools/samtools",
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                        "Repository"
                    ],
                    "note": null
                },
                {
                    "url": "http://www.htslib.org/support/#lists",
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                        "Mailing list"
                    ],
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                },
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                    "url": "https://github.com/samtools/samtools/issues",
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                        "Issue tracker"
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                {
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            "documentation": [
                {
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                        "Other"
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                },
                {
                    "url": "http://www.htslib.org/doc/#manual-pages",
                    "type": [
                        "User manual"
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                {
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                    "type": [
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            ],
            "publication": [
                {
                    "doi": "10.1093/bioinformatics/btp352",
                    "pmid": "19505943",
                    "pmcid": "PMC2723002",
                    "type": [
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                    ],
                    "version": null,
                    "note": "The Sequence Alignment/Map format and SAMtools.",
                    "metadata": {
                        "title": "The Sequence Alignment/Map format and SAMtools",
                        "abstract": "Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAM tools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. © 2009 The Author(s).",
                        "date": "2009-08-01T00:00:00Z",
                        "citationCount": 37126,
                        "authors": [
                            {
                                "name": "Li H."
                            },
                            {
                                "name": "Handsaker B."
                            },
                            {
                                "name": "Wysoker A."
                            },
                            {
                                "name": "Fennell T."
                            },
                            {
                                "name": "Ruan J."
                            },
                            {
                                "name": "Homer N."
                            },
                            {
                                "name": "Marth G."
                            },
                            {
                                "name": "Abecasis G."
                            },
                            {
                                "name": "Durbin R."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                },
                {
                    "doi": "10.1093/gigascience/giab008",
                    "pmid": "33590861",
                    "pmcid": "PMC7931819",
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": "Twelve years of SAMtools and BCFtools.",
                    "metadata": {
                        "title": "Twelve years of SAMtools and BCFtools",
                        "abstract": "Background: SAMtools and BCFtools are widely used programs for processing and analysing high-throughput sequencing data. They include tools for file format conversion and manipulation, sorting, querying, statistics, variant calling, and effect analysis amongst other methods. Findings: The first version appeared online 12 years ago and has been maintained and further developed ever since, with many new features and improvements added over the years. The SAMtools and BCFtools packages represent a unique collection of tools that have been used in numerous other software projects and countless genomic pipelines. Conclusion: Both SAMtools and BCFtools are freely available on GitHub under the permissive MIT licence, free for both non-commercial and commercial use. Both packages have been installed >1 million times via Bioconda. The source code and documentation are available from https://www.htslib.org.",
                        "date": "2021-02-01T00:00:00Z",
                        "citationCount": 3084,
                        "authors": [
                            {
                                "name": "Danecek P."
                            },
                            {
                                "name": "Bonfield J.K."
                            },
                            {
                                "name": "Liddle J."
                            },
                            {
                                "name": "Marshall J."
                            },
                            {
                                "name": "Ohan V."
                            },
                            {
                                "name": "Pollard M.O."
                            },
                            {
                                "name": "Whitwham A."
                            },
                            {
                                "name": "Keane T."
                            },
                            {
                                "name": "McCarthy S.A."
                            },
                            {
                                "name": "Davies R.M."
                            }
                        ],
                        "journal": "GigaScience"
                    }
                },
                {
                    "doi": "10.1093/bioinformatics/btr509",
                    "pmid": "21903627",
                    "pmcid": "PMC3198575",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data",
                        "abstract": "Motivation: Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. Results: We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. © The Author 2011. Published by Oxford University Press. All rights reserved.",
                        "date": "2011-11-01T00:00:00Z",
                        "citationCount": 3826,
                        "authors": [
                            {
                                "name": "Li H."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Richard Durbin",
                    "email": "rd@sanger.ac.uk",
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                {
                    "name": "Wellcome Sanger Institute",
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                    ],
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                {
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                }
            ],
            "community": {
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            "description": "The main purpose of HTSlib is to provide access to genomic information files, both alignment data (SAM, BAM, and CRAM formats) and variant data (VCF and BCF formats). The library also provides interfaces to access and index genome reference data in FASTA format and tab-delimited files with genomic coordinates. It is utilized and incorporated into both SAMtools and BCFtools.",
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            "biotoolsID": "htslib",
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                "1.6",
                "1.7",
                "1.8",
                "1.9",
                "1.10",
                "1.10.1",
                "1.10.2",
                "1.11",
                "1.12",
                "1.13",
                "1.14",
                "1.15",
                "1.15.1",
                "1.16",
                "1.17",
                "1.18",
                "1.19",
                "1.20"
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                            "term": "Data handling"
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                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0924",
                                "term": "Sequence trace"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_2573",
                                    "term": "SAM"
                                },
                                {
                                    "uri": "http://edamontology.org/format_2572",
                                    "term": "BAM"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3462",
                                    "term": "CRAM"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1929",
                                    "term": "FASTA"
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                                    "uri": "http://edamontology.org/format_1930",
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                                }
                            ]
                        },
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                            "data": {
                                "uri": "http://edamontology.org/data_3498",
                                "term": "Sequence variations"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_3016",
                                    "term": "VCF"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3020",
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                                "term": "Sequence variations"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_3016",
                                    "term": "VCF"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3020",
                                    "term": "BCF"
                                }
                            ]
                        }
                    ],
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                "Library"
            ],
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                    "uri": "http://edamontology.org/topic_3071",
                    "term": "Data management"
                }
            ],
            "operatingSystem": [
                "Linux",
                "Windows",
                "Mac"
            ],
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                "C"
            ],
            "license": "MIT",
            "collectionID": [
                "Animal and Crop Genomics"
            ],
            "maturity": "Mature",
            "cost": "Free of charge",
            "accessibility": "Open access",
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            "link": [
                {
                    "url": "https://github.com/samtools/htslib",
                    "type": [
                        "Repository"
                    ],
                    "note": null
                },
                {
                    "url": "http://www.htslib.org/support/#lists",
                    "type": [
                        "Mailing list"
                    ],
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                },
                {
                    "url": "https://github.com/samtools/htslib/issues",
                    "type": [
                        "Issue tracker"
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            ],
            "download": [
                {
                    "url": "http://www.htslib.org/download/",
                    "type": "Downloads page",
                    "note": null,
                    "version": null
                }
            ],
            "documentation": [
                {
                    "url": "http://www.htslib.org/doc/#manual-pages",
                    "type": [
                        "User manual"
                    ],
                    "note": null
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            ],
            "publication": [
                {
                    "doi": "10.1093/gigascience/giab007",
                    "pmid": "33594436",
                    "pmcid": "PMC7931820",
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": "HTSlib: C library for reading/writing high-throughput sequencing data.",
                    "metadata": {
                        "title": "HTSlib: C library for reading/writing high-Throughput sequencing data",
                        "abstract": "Background: Since the original publication of the VCF and SAM formats, an explosion of software tools have been created to process these data files. To facilitate this a library was produced out of the original SAMtools implementation, with a focus on performance and robustness. The file formats themselves have become international standards under the jurisdiction of the Global Alliance for Genomics and Health. Findings: We present a software library for providing programmatic access to sequencing alignment and variant formats. It was born out of the widely used SAMtools and BCFtools applications. Considerable improvements have been made to the original code plus many new features including newer access protocols, the addition of the CRAM file format, better indexing and iterators, and better use of threading. Conclusion: Since the original Samtools release, performance has been considerably improved, with a BAM read-write loop running 5 times faster and BAM to SAM conversion 13 times faster (both using 16 threads, compared to Samtools 0.1.19). Widespread adoption has seen HTSlib downloaded >1 million times from GitHub and conda. The C library has been used directly by an estimated 900 GitHub projects and has been incorporated into Perl, Python, Rust, and R, significantly expanding the number of uses via other languages. HTSlib is open source and is freely available from htslib.org under MIT/BSD license.",
                        "date": "2021-02-01T00:00:00Z",
                        "citationCount": 116,
                        "authors": [
                            {
                                "name": "Bonfield J.K."
                            },
                            {
                                "name": "Marshall J."
                            },
                            {
                                "name": "Danecek P."
                            },
                            {
                                "name": "Li H."
                            },
                            {
                                "name": "Ohan V."
                            },
                            {
                                "name": "Whitwham A."
                            },
                            {
                                "name": "Keane T."
                            }
                        ],
                        "journal": "GigaScience"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Wellcome Sanger Institute",
                    "email": "samtools@sanger.ac.uk",
                    "url": "https://www.sanger.ac.uk/",
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                    "url": "https://lists.sourceforge.net/lists/listinfo/samtools-help",
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                    "typeEntity": "Project",
                    "typeRole": [
                        "Support"
                    ],
                    "note": null
                }
            ],
            "community": null,
            "owner": "awhitwham",
            "additionDate": "2017-08-20T16:07:58Z",
            "lastUpdate": "2024-04-16T10:19:42.968075Z",
            "editPermission": {
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                "authors": [
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                    "smoe"
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        },
        {
            "name": "PhenPath",
            "description": "A tool for characterizing biological functions underlying different phenotypes.\n\na web server for associating phenotypes with molecular functional annotations.\n\nPhenPath includes a database and a tool:.\n'",
            "homepage": "http://phenpath.biocomp.unibo.it",
            "biotoolsID": "phenpath",
            "biotoolsCURIE": "biotools:phenpath",
            "version": [],
            "otherID": [],
            "relation": [],
            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_2422",
                            "term": "Data retrieval"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3501",
                            "term": "Enrichment analysis"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3672",
                            "term": "Gene functional annotation"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1150",
                                "term": "Disease ID"
                            },
                            "format": []
                        },
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_3668",
                                "term": "Disease name"
                            },
                            "format": []
                        },
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_3275",
                                "term": "Phenotype name"
                            },
                            "format": []
                        }
                    ],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1622",
                                "term": "Disease report"
                            },
                            "format": []
                        }
                    ],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Database portal"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0625",
                    "term": "Genotype and phenotype"
                },
                {
                    "uri": "http://edamontology.org/topic_0602",
                    "term": "Molecular interactions, pathways and networks"
                },
                {
                    "uri": "http://edamontology.org/topic_0634",
                    "term": "Pathology"
                },
                {
                    "uri": "http://edamontology.org/topic_3305",
                    "term": "Public health and epidemiology"
                },
                {
                    "uri": "http://edamontology.org/topic_3325",
                    "term": "Rare diseases"
                }
            ],
            "operatingSystem": [
                "Linux",
                "Mac",
                "Windows"
            ],
            "language": [],
            "license": "CC-BY-NC-4.0",
            "collectionID": [
                "Rare Disease",
                "Bologna Biocomputing Group"
            ],
            "maturity": "Mature",
            "cost": "Free of charge",
            "accessibility": "Open access",
            "elixirPlatform": [],
            "elixirNode": [
                "Italy"
            ],
            "elixirCommunity": [],
            "link": [],
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            "documentation": [
                {
                    "url": "http://phenpath.biocomp.unibo.it/phenpath/help_page.html",
                    "type": [
                        "User manual"
                    ],
                    "note": null
                }
            ],
            "publication": [
                {
                    "doi": "10.1186/S12864-019-5868-X",
                    "pmid": "31307376",
                    "pmcid": "PMC6631446",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "PhenPath: A tool for characterizing biological functions underlying different phenotypes",
                        "abstract": "Background: Many diseases are associated with complex patterns of symptoms and phenotypic manifestations. Parsimonious explanations aim at reconciling the multiplicity of phenotypic traits with the perturbation of one or few biological functions. For this, it is necessary to characterize human phenotypes at the molecular and functional levels, by exploiting gene annotations and known relations among genes, diseases and phenotypes. This characterization makes it possible to implement tools for retrieving functions shared among phenotypes, co-occurring in the same patient and facilitating the formulation of hypotheses about the molecular causes of the disease. Results: We introduce PhenPath, a new resource consisting of two parts: PhenPathDB and PhenPathTOOL. The former is a database collecting the human genes associated with the phenotypes described in Human Phenotype Ontology (HPO) and OMIM Clinical Synopses. Phenotypes are then associated with biological functions and pathways by means of NET-GE, a network-based method for functional enrichment of sets of genes. The present version considers only phenotypes related to diseases. PhenPathDB collects information for 18 OMIM Clinical synopses and 7137 HPO phenotypes, related to 4292 diseases and 3446 genes. Enrichment of Gene Ontology annotations endows some 87.7, 86.9 and 73.6% of HPO phenotypes with Biological Process, Molecular Function and Cellular Component terms, respectively. Furthermore, 58.8 and 77.8% of HPO phenotypes are also enriched for KEGG and Reactome pathways, respectively. Based on PhenPathDB, PhenPathTOOL analyzes user-defined sets of phenotypes retrieving diseases, genes and functional terms which they share. This information can provide clues for interpreting the co-occurrence of phenotypes in a patient. Conclusions: The resource allows finding molecular features useful to investigate diseases characterized by multiple phenotypes, and by this, it can help researchers and physicians in identifying molecular mechanisms and biological functions underlying the concomitant manifestation of phenotypes. The resource is freely available at http://phenpath.biocomp.unibo.it.",
                        "date": "2019-07-16T00:00:00Z",
                        "citationCount": 8,
                        "authors": [
                            {
                                "name": "Babbi G."
                            },
                            {
                                "name": "Martelli P.L."
                            },
                            {
                                "name": "Casadio R."
                            }
                        ],
                        "journal": "BMC Genomics"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Pier Luigi Martelli",
                    "email": "pierluigi.martelli@unibo.it",
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                {
                    "name": "Giulia Babbi",
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                }
            ],
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            "owner": "ELIXIR-ITA-BOLOGNA",
            "additionDate": "2021-01-20T10:58:38Z",
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}