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        {
            "name": "Maast",
            "description": "Genotyping thousands of microbial strains. Type SNPs from a set of whole genome assemblies and sequencing reads from beginning to end in one single command line.",
            "homepage": "https://github.com/zjshi/Maast",
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                            "uri": "http://edamontology.org/operation_3196",
                            "term": "Genotyping"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0484",
                            "term": "SNP detection"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0525",
                            "term": "Genome assembly"
                        }
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                    "output": [],
                    "note": null,
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                }
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                "Command-line tool",
                "Workflow"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_2885",
                    "term": "DNA polymorphism"
                },
                {
                    "uri": "http://edamontology.org/topic_0625",
                    "term": "Genotype and phenotype"
                },
                {
                    "uri": "http://edamontology.org/topic_3673",
                    "term": "Whole genome sequencing"
                },
                {
                    "uri": "http://edamontology.org/topic_3174",
                    "term": "Metagenomics"
                },
                {
                    "uri": "http://edamontology.org/topic_0196",
                    "term": "Sequence assembly"
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            "publication": [
                {
                    "doi": "10.1186/S13059-023-03030-8",
                    "pmid": "37563669",
                    "pmcid": "PMC10416524",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Maast: genotyping thousands of microbial strains efficiently",
                        "abstract": "Existing single nucleotide polymorphism (SNP) genotyping algorithms do not scale for species with thousands of sequenced strains, nor do they account for conspecific redundancy. Here we present a bioinformatics tool, Maast, which empowers population genetic meta-analysis of microbes at an unrivaled scale. Maast implements a novel algorithm to heuristically identify a minimal set of diverse conspecific genomes, then constructs a reliable SNP panel for each species, and enables rapid and accurate genotyping using a hybrid of whole-genome alignment and k-mer exact matching. We demonstrate Maast’s utility by genotyping thousands of Helicobacter pylori strains and tracking SARS-CoV-2 diversification.",
                        "date": "2023-12-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Shi Z.J."
                            },
                            {
                                "name": "Nayfach S."
                            },
                            {
                                "name": "Pollard K.S."
                            }
                        ],
                        "journal": "Genome Biology"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Katherine S. Pollard",
                    "email": "kpollard@gladstone.ucsf.edu",
                    "url": null,
                    "orcidid": "https://orcid.org/0000-0002-9870-6196",
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                {
                    "name": "Zhou Jason Shi",
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                    "name": "Stephen Nayfach",
                    "email": null,
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            "name": "BLAST (EBI)",
            "description": "Find regions of sequence similarity and alignments between a query sequence and database sequences.",
            "homepage": "https://www.ebi.ac.uk/jdispatcher/sss/ncbiblast",
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                            "uri": "http://edamontology.org/operation_0346",
                            "term": "Sequence similarity search"
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                            "uri": "http://edamontology.org/operation_0292",
                            "term": "Sequence alignment"
                        }
                    ],
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                        {
                            "data": {
                                "uri": "http://edamontology.org/data_2044",
                                "term": "Sequence"
                            },
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                        }
                    ],
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                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0857",
                                "term": "Sequence search results"
                            },
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                    "note": null,
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                "Web service"
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                    "uri": "http://edamontology.org/topic_0080",
                    "term": "Sequence analysis"
                },
                {
                    "uri": "http://edamontology.org/topic_0622",
                    "term": "Genomics"
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                {
                    "url": "https://blast.ncbi.nlm.nih.gov/Blast.cgi?CMD=Web&PAGE_TYPE=BlastDocs&DOC_TYPE=Download",
                    "type": "Downloads page",
                    "note": null,
                    "version": null
                }
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            "documentation": [
                {
                    "url": "http://www.ebi.ac.uk/about/terms-of-use",
                    "type": [
                        "Terms of use"
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                    "note": null
                },
                {
                    "url": "https://www.ebi.ac.uk/jdispatcher/help",
                    "type": [
                        "General"
                    ],
                    "note": null
                },
                {
                    "url": "https://blast.ncbi.nlm.nih.gov/Blast.cgi",
                    "type": [
                        "General"
                    ],
                    "note": null
                }
            ],
            "publication": [
                {
                    "doi": "10.1186/1471-2105-10-421",
                    "pmid": "20003500",
                    "pmcid": "PMC2803857",
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "BLAST+: Architecture and applications",
                        "abstract": "Background: Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications.Results: We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site.Conclusion: The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications. © 2009 Camacho et al; licensee BioMed Central Ltd.",
                        "date": "2009-12-15T00:00:00Z",
                        "citationCount": 10984,
                        "authors": [
                            {
                                "name": "Camacho C."
                            },
                            {
                                "name": "Coulouris G."
                            },
                            {
                                "name": "Avagyan V."
                            },
                            {
                                "name": "Ma N."
                            },
                            {
                                "name": "Papadopoulos J."
                            },
                            {
                                "name": "Bealer K."
                            },
                            {
                                "name": "Madden T.L."
                            }
                        ],
                        "journal": "BMC Bioinformatics"
                    }
                },
                {
                    "doi": "10.1093/nar/gkac240",
                    "pmid": null,
                    "pmcid": null,
                    "type": [
                        "Other"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Search and sequence analysis tools services from EMBL-EBI in 2022",
                        "abstract": "The EMBL-EBI search and sequence analysis tools frameworks provide integrated access to EMBL-EBI's data resources and core bioinformatics analytical tools. EBI Search (https://www.ebi.ac.uk/ebisearch) provides a full-text search engine across nearly 5 billion entries, while the Job Dispatcher tools framework (https://www.ebi.ac.uk/services) enables the scientific community to perform a diverse range of sequence analysis using popular bioinformatics applications. Both allow users to interact through user-friendly web applications, as well as via RESTful and SOAP-based APIs. Here, we describe recent improvements to these services and updates made to accommodate the increasing data requirements during the COVID-19 pandemic.",
                        "date": "2022-07-05T00:00:00Z",
                        "citationCount": 651,
                        "authors": [
                            {
                                "name": "Madeira F."
                            },
                            {
                                "name": "Pearce M."
                            },
                            {
                                "name": "Tivey A.R.N."
                            },
                            {
                                "name": "Basutkar P."
                            },
                            {
                                "name": "Lee J."
                            },
                            {
                                "name": "Edbali O."
                            },
                            {
                                "name": "Madhusoodanan N."
                            },
                            {
                                "name": "Kolesnikov A."
                            },
                            {
                                "name": "Lopez R."
                            }
                        ],
                        "journal": "Nucleic Acids Research"
                    }
                }
            ],
            "credit": [
                {
                    "name": "EMBL-EBI",
                    "email": null,
                    "url": null,
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                },
                {
                    "name": "NCBI",
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                    "orcidid": null,
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                    ],
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                },
                {
                    "name": "Job Dispatcher",
                    "email": null,
                    "url": "https://www.ebi.ac.uk/jdispatcher",
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                    "typeEntity": "Project",
                    "typeRole": [
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                }
            ],
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            "additionDate": "2015-01-29T15:47:52Z",
            "lastUpdate": "2024-01-12T16:24:54.401987Z",
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                "authors": [
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        {
            "name": "FLUST",
            "description": "A fast, open source framework for ultrasound blood flow simulations.",
            "homepage": "http://www.ustb.no/flust",
            "biotoolsID": "flust",
            "biotoolsCURIE": "biotools:flust",
            "version": [],
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                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3454",
                            "term": "Phasing"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3214",
                            "term": "Spectral analysis"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3435",
                            "term": "Standardisation and normalisation"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
                    "cmd": null
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            ],
            "toolType": [
                "Suite"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_3954",
                    "term": "Echography"
                },
                {
                    "uri": "http://edamontology.org/topic_3444",
                    "term": "MRI"
                },
                {
                    "uri": "http://edamontology.org/topic_3384",
                    "term": "Medical imaging"
                }
            ],
            "operatingSystem": [
                "Mac",
                "Linux",
                "Windows"
            ],
            "language": [
                "MATLAB"
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            "link": [
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                    "note": null
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            ],
            "download": [],
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            "publication": [
                {
                    "doi": "10.1016/J.CMPB.2023.107604",
                    "pmid": "37220679",
                    "pmcid": null,
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "FLUST: A fast, open source framework for ultrasound blood flow simulations",
                        "abstract": "Background and objective:Ultrasound based blood velocity estimation is a continuously developing frontier, where the vast number of possible acquisition setups and velocity estimators makes it challenging to assess which combination is better suited for a given imaging application. FLUST, the Flow-Line based Ultrasound Simulation Tool, may be used to address this challenge, providing a common platform for evaluation of velocity estimation schemes on in silico data. However, the FLUST approach had some limitations in its original form, including reduced robustness for phase sensitive setups and the need for manual selection of integrity parameters. In addition, implementation of the technique and therefore also documentation of signal integrity was left to potential users of the approach. Methods: In this work, several improvements to the FLUST technique are proposed and investigated, and a robust, open source simulation framework developed. The software supports several transducer types and acquisition setups, in addition to a range of different flow phantoms. The main goal of this work is to offer a robust, computationally cheap and user-friendly framework to simulate ultrasound data from stationary blood velocity fields and thereby facilitate design and evaluation of estimation schemes, including acquisition design, velocity estimation and other post-processing steps. Results: The technical improvements proposed in this work resulted in reduced interpolation errors, reduced variability in signal power, and also automatic selection of spatial and temporal discretization parameters. Results are presented illustrating the challenges and the effectiveness of the solutions. The integrity of the improved simulation framework is validated in an extensive study, with results indicating that speckle statistics, spatial and temporal correlation and frequency content all correspond well with theoretical predictions. Finally, an illustrative example shows how FLUST may be used throughout the design and optimization process of a velocity estimator. Conclusions: The FLUST framework is available as a part of the UltraSound ToolBox (USTB), and the results in this paper demonstrate that it can be used as an efficient and reliable tool for the development and validation of ultrasound-based velocity estimation schemes.",
                        "date": "2023-08-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Ekroll I.K."
                            },
                            {
                                "name": "Saris A.E.C.M."
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                            {
                                "name": "Avdal J."
                            }
                        ],
                        "journal": "Computer Methods and Programs in Biomedicine"
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                {
                    "name": "Ingvild Kinn Ekroll",
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                            "term": "Quantification"
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                            "term": "Base-calling"
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                        {
                            "uri": "http://edamontology.org/operation_0314",
                            "term": "Gene expression profiling"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3200",
                            "term": "DNA barcoding"
                        }
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                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_3495",
                                "term": "RNA sequence"
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                    "uri": "http://edamontology.org/topic_3170",
                    "term": "RNA-Seq"
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                    "uri": "http://edamontology.org/topic_2229",
                    "term": "Cell biology"
                },
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                    "uri": "http://edamontology.org/topic_0099",
                    "term": "RNA"
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                    "doi": "10.1186/S13059-023-02907-Y",
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                    "pmcid": "PMC10077662",
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                    "metadata": {
                        "title": "Identification of cell barcodes from long-read single-cell RNA-seq with BLAZE",
                        "abstract": "Long-read single-cell RNA sequencing (scRNA-seq) enables the quantification of RNA isoforms in individual cells. However, long-read scRNA-seq using the Oxford Nanopore platform has largely relied upon matched short-read data to identify cell barcodes. We introduce BLAZE, which accurately and efficiently identifies 10x cell barcodes using only nanopore long-read scRNA-seq data. BLAZE outperforms the existing tools and provides an accurate representation of the cells present in long-read scRNA-seq when compared to matched short reads. BLAZE simplifies long-read scRNA-seq while improving the results, is compatible with downstream tools accepting a cell barcode file, and is available at https://github.com/shimlab/BLAZE.",
                        "date": "2023-12-01T00:00:00Z",
                        "citationCount": 2,
                        "authors": [
                            {
                                "name": "You Y."
                            },
                            {
                                "name": "Prawer Y.D.J."
                            },
                            {
                                "name": "De Paoli-Iseppi R."
                            },
                            {
                                "name": "Hunt C.P.J."
                            },
                            {
                                "name": "Parish C.L."
                            },
                            {
                                "name": "Shim H."
                            },
                            {
                                "name": "Clark M.B."
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                        "journal": "Genome Biology"
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            "credit": [
                {
                    "name": "Heejung Shim",
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            "name": "Boost",
            "description": "Boost is a set of libraries for the C++ programming language that provides support for tasks and structures such as linear algebra, pseudorandom number generation, multithreading, image processing, regular expressions, and unit testing.",
            "homepage": "https://www.boost.org/",
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                            "term": "Image analysis"
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                            "data": {
                                "uri": "http://edamontology.org/data_1352",
                                "term": "Regular expression"
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                            "term": "Phylogenetic tree visualisation"
                        },
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                            "term": "Data retrieval"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
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            ],
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            ],
            "topic": [
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                    "term": "Bioinformatics"
                },
                {
                    "uri": "http://edamontology.org/topic_0797",
                    "term": "Comparative genomics"
                },
                {
                    "uri": "http://edamontology.org/topic_3293",
                    "term": "Phylogenetics"
                },
                {
                    "uri": "http://edamontology.org/topic_0092",
                    "term": "Data visualisation"
                }
            ],
            "operatingSystem": [
                "Linux",
                "Windows",
                "Mac"
            ],
            "language": [
                "Java"
            ],
            "license": "AGPL-3.0",
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                "BLAST utility"
            ],
            "maturity": "Mature",
            "cost": "Free of charge",
            "accessibility": "Open access",
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            "elixirNode": [],
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            "link": [
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            ],
            "download": [
                {
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                    "type": "Software package",
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            ],
            "documentation": [
                {
                    "url": "https://github.com/pgdurand/BlastViewer/wiki",
                    "type": [
                        "User manual"
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                    "note": null
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            ],
            "publication": [],
            "credit": [
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                    "email": null,
                    "url": "https://github.com/pgdurand/BlastViewer/issues",
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        {
            "name": "BLAST",
            "description": "A tool that finds regions of similarity between biological sequences. The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance.",
            "homepage": "https://blast.ncbi.nlm.nih.gov/Blast.cgi",
            "biotoolsID": "blast",
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            "version": [],
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            "function": [
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                            "uri": "http://edamontology.org/operation_0346",
                            "term": "Sequence similarity search"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0292",
                            "term": "Sequence alignment"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_2044",
                                "term": "Sequence"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_1929",
                                    "term": "FASTA"
                                }
                            ]
                        }
                    ],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0857",
                                "term": "Sequence search results"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_3331",
                                    "term": "BLAST XML results format"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3836",
                                    "term": "BLAST XML v2 results format"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3475",
                                    "term": "TSV"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3752",
                                    "term": "CSV"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1966",
                                    "term": "ASN.1 sequence format"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3464",
                                    "term": "JSON"
                                },
                                {
                                    "uri": "http://edamontology.org/format_2333",
                                    "term": "Binary format"
                                },
                                {
                                    "uri": "http://edamontology.org/format_2330",
                                    "term": "Textual format"
                                }
                            ]
                        }
                    ],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Command-line tool",
                "Web application",
                "Web API"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0080",
                    "term": "Sequence analysis"
                },
                {
                    "uri": "http://edamontology.org/topic_0091",
                    "term": "Bioinformatics"
                }
            ],
            "operatingSystem": [
                "Linux",
                "Windows",
                "Mac"
            ],
            "language": [],
            "license": null,
            "collectionID": [
                "BLAST"
            ],
            "maturity": "Mature",
            "cost": "Free of charge",
            "accessibility": "Open access",
            "elixirPlatform": [],
            "elixirNode": [],
            "elixirCommunity": [],
            "link": [],
            "download": [],
            "documentation": [
                {
                    "url": "https://blast.ncbi.nlm.nih.gov/Blast.cgi?CMD=Web&PAGE_TYPE=BlastDocs",
                    "type": [
                        "General"
                    ],
                    "note": null
                },
                {
                    "url": "https://blast.ncbi.nlm.nih.gov/Blast.cgi?CMD=Web&PAGE_TYPE=BlastDocs&DOC_TYPE=References",
                    "type": [
                        "Citation instructions"
                    ],
                    "note": null
                }
            ],
            "publication": [
                {
                    "doi": "10.1016/S0022-2836(05)80360-2",
                    "pmid": "2231712",
                    "pmcid": null,
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Basic local alignment search tool",
                        "abstract": "A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straight-forward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity. © 1990, Academic Press Limited. All rights reserved.",
                        "date": "1990-01-01T00:00:00Z",
                        "citationCount": 67988,
                        "authors": [
                            {
                                "name": "Altschul S.F."
                            },
                            {
                                "name": "Gish W."
                            },
                            {
                                "name": "Miller W."
                            },
                            {
                                "name": "Myers E.W."
                            },
                            {
                                "name": "Lipman D.J."
                            }
                        ],
                        "journal": "Journal of Molecular Biology"
                    }
                },
                {
                    "doi": "10.1093/bioinformatics/btw305",
                    "pmid": "27256311",
                    "pmcid": "PMC5013910",
                    "type": [
                        "Benchmarking study"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Benchmarking the next generation of homology inference tools",
                        "abstract": "© 2016 The Author 2016. Published by Oxford University Press.Motivation: Over the last decades, vast numbers of sequences were deposited in public databases. Bioinformatics tools allow homology and consequently functional inference for these sequences. New profile-based homology search tools have been introduced, allowing reliable detection of remote homologs, but have not been systematically benchmarked. To provide such a comparison, which can guide bioinformatics workflows, we extend and apply our previously developed benchmark approach to evaluate the 'next generation' of profile-based approaches, including CS-BLAST, HHSEARCH and PHMMER, in comparison with the non-profile based search tools NCBI-BLAST, USEARCH, UBLAST and FASTA. Method: We generated challenging benchmark datasets based on protein domain architectures within either the PFAM + Clan, SCOP/Superfamily or CATH/Gene3D domain definition schemes. From each dataset, homologous and non-homologous protein pairs were aligned using each tool, and standard performance metrics calculated. We further measured congruence of domain architecture assignments in the three domain databases. Results: CSBLAST and PHMMER had overall highest accuracy. FASTA, UBLAST and USEARCH showed large trade-offs of accuracy for speed optimization. Conclusion: Profile methods are superior at inferring remote homologs but the difference in accuracy between methods is relatively small. PHMMER and CSBLAST stand out with the highest accuracy, yet still at a reasonable computational cost. Additionally, we show that less than 0.1% of Swiss-Prot protein pairs considered homologous by one database are considered non-homologous by another, implying that these classifications represent equivalent underlying biological phenomena, differing mostly in coverage and granularity. Availability and Implementation: Benchmark datasets and all scripts are placed at (http://sonnhammer.org/download/Homology-benchmark).",
                        "date": "2016-09-01T00:00:00Z",
                        "citationCount": 6,
                        "authors": [
                            {
                                "name": "Saripella G.V."
                            },
                            {
                                "name": "Sonnhammer E.L.L."
                            },
                            {
                                "name": "Forslund K."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                },
                {
                    "doi": "10.1093/nar/gkn201",
                    "pmid": "18440982",
                    "pmcid": "PMC2447716",
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "NCBI BLAST: a better web interface.",
                        "abstract": "Basic Local Alignment Search Tool (BLAST) is a sequence similarity search program. The public interface of BLAST, http://www.ncbi.nlm.nih.gov/blast, at the NCBI website has recently been reengineered to improve usability and performance. Key new features include simplified search forms, improved navigation, a list of recent BLAST results, saved search strategies and a documentation directory. Here, we describe the BLAST web application's new features, explain design decisions and outline plans for future improvement.",
                        "date": "2008-01-01T00:00:00Z",
                        "citationCount": 1931,
                        "authors": [
                            {
                                "name": "Johnson M."
                            },
                            {
                                "name": "Zaretskaya I."
                            },
                            {
                                "name": "Raytselis Y."
                            },
                            {
                                "name": "Merezhuk Y."
                            },
                            {
                                "name": "McGinnis S."
                            },
                            {
                                "name": "Madden T.L."
                            }
                        ],
                        "journal": "Nucleic acids research"
                    }
                },
                {
                    "doi": "10.1093/nar/gkt282",
                    "pmid": "23609542",
                    "pmcid": "PMC3692093",
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "BLAST: a more efficient report with usability improvements.",
                        "abstract": "The Basic Local Alignment Search Tool (BLAST) website at the National Center for Biotechnology (NCBI) is an important resource for searching and aligning sequences. A new BLAST report allows faster loading of alignments, adds navigation aids, allows easy downloading of subject sequences and reports and has improved usability. Here, we describe these improvements to the BLAST report, discuss design decisions, describe other improvements to the search page and database documentation and outline plans for future development. The NCBI BLAST URL is http://blast.ncbi.nlm.nih.gov.",
                        "date": "2013-01-01T00:00:00Z",
                        "citationCount": 579,
                        "authors": [
                            {
                                "name": "Boratyn G.M."
                            },
                            {
                                "name": "Camacho C."
                            },
                            {
                                "name": "Cooper P.S."
                            },
                            {
                                "name": "Coulouris G."
                            },
                            {
                                "name": "Fong A."
                            },
                            {
                                "name": "Ma N."
                            },
                            {
                                "name": "Madden T.L."
                            },
                            {
                                "name": "Matten W.T."
                            },
                            {
                                "name": "McGinnis S.D."
                            },
                            {
                                "name": "Merezhuk Y."
                            },
                            {
                                "name": "Raytselis Y."
                            },
                            {
                                "name": "Sayers E.W."
                            },
                            {
                                "name": "Tao T."
                            },
                            {
                                "name": "Ye J."
                            },
                            {
                                "name": "Zaretskaya I."
                            }
                        ],
                        "journal": "Nucleic acids research"
                    }
                }
            ],
            "credit": [
                {
                    "name": "BLAST Support",
                    "email": "blast-help@ncbi.nlm.nih.gov",
                    "url": null,
                    "orcidid": null,
                    "gridid": null,
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                    ],
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                }
            ],
            "community": null,
            "owner": "seqwiki_import",
            "additionDate": "2017-01-13T13:13:50Z",
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            },
            "validated": 1,
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            "confidence_flag": null
        },
        {
            "name": "Blast2GO",
            "description": "Bioinformatics platform for high-quality functional annotation and analysis of genomic datasets. It allows analyzing and visualizing newly sequenced genomes by combining state-of-the-art methodologies, standard resources and algorithms. It allows to gain biological insights fast and easy even for completely novel genomes. Perform out-of-the-box the entire workflow of functional annotation of your transcriptomic datasets including its analysis and biological interpretation.",
            "homepage": "https://www.blast2go.com/",
            "biotoolsID": "blast2go",
            "biotoolsCURIE": "biotools:blast2go",
            "version": [],
            "otherID": [],
            "relation": [],
            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3672",
                            "term": "Gene functional annotation"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1383",
                                "term": "Sequence alignment (nucleic acid)"
                            },
                            "format": []
                        }
                    ],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_3753",
                                "term": "Over-representation data"
                            },
                            "format": []
                        }
                    ],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Command-line tool",
                "Desktop application"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_3511",
                    "term": "Nucleic acid sites, features and motifs"
                }
            ],
            "operatingSystem": [
                "Linux",
                "Windows",
                "Mac"
            ],
            "language": [],
            "license": null,
            "collectionID": [
                "BLAST"
            ],
            "maturity": null,
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            "link": [],
            "download": [],
            "documentation": [
                {
                    "url": "https://www.blast2go.com/blast2go-pro",
                    "type": [
                        "General"
                    ],
                    "note": null
                }
            ],
            "publication": [
                {
                    "doi": "10.1093/bioinformatics/bti610",
                    "pmid": "16081474",
                    "pmcid": null,
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Blast2GO: A universal tool for annotation, visualization and analysis in functional genomics research",
                        "abstract": "Summary: We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one application GO annotation based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. This tool offers a suitable platform for functional genomics research in non-model species. B2G is an intuitive and interactive desktop application that allows monitoring and comprehension of the whole annotation and analysis process. © The Author 2005. Published by Oxford University Press. All rights reserved.",
                        "date": "2005-09-15T00:00:00Z",
                        "citationCount": 8122,
                        "authors": [
                            {
                                "name": "Conesa A."
                            },
                            {
                                "name": "Gotz S."
                            },
                            {
                                "name": "Garcia-Gomez J.M."
                            },
                            {
                                "name": "Terol J."
                            },
                            {
                                "name": "Talon M."
                            },
                            {
                                "name": "Robles M."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                },
                {
                    "doi": "10.1093/nar/gkn176",
                    "pmid": "18445632",
                    "pmcid": "PMC2425479",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "High-throughput functional annotation and data mining with the Blast2GO suite",
                        "abstract": "Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologist-oriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) high-throughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data. © 2008 The Author(s).",
                        "date": "2008-06-01T00:00:00Z",
                        "citationCount": 2670,
                        "authors": [
                            {
                                "name": "Gotz S."
                            },
                            {
                                "name": "Garcia-Gomez J.M."
                            },
                            {
                                "name": "Terol J."
                            },
                            {
                                "name": "Williams T.D."
                            },
                            {
                                "name": "Nagaraj S.H."
                            },
                            {
                                "name": "Nueda M.J."
                            },
                            {
                                "name": "Robles M."
                            },
                            {
                                "name": "Talon M."
                            },
                            {
                                "name": "Dopazo J."
                            },
                            {
                                "name": "Conesa A."
                            }
                        ],
                        "journal": "Nucleic Acids Research"
                    }
                }
            ],
            "credit": [
                {
                    "name": null,
                    "email": "contact@biobam.com",
                    "url": "https://www.biobam.com/biobam-contact/",
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                    "typeEntity": "Person",
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                        "Primary contact"
                    ],
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                }
            ],
            "community": null,
            "owner": "ELIXIR-EE",
            "additionDate": "2017-03-01T15:34:10Z",
            "lastUpdate": "2022-06-27T14:51:01.924474Z",
            "editPermission": {
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                ]
            },
            "validated": 1,
            "homepage_status": 0,
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            "confidence_flag": null
        },
        {
            "name": "BEAST",
            "description": "The Bayesian Evolutionary Analysis Sampling Trees is a cross-platform program for Bayesian analysis of molecular sequences using MCMC (Markov chain Monte Carlo). It is entirely orientated towards rooted, time-measured phylogenies inferred using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology.",
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                            "term": "Phylogenetic tree generation (from molecular sequences)"
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                    "term": "Phylogenetics"
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                {
                    "doi": "10.1093/molbev/mss075",
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                    "metadata": {
                        "title": "Bayesian phylogenetics with BEAUti and the BEAST 1.7",
                        "abstract": "Computational evolutionary biology, statistical phylogenetics and coalescent-based population genetics are becoming increasingly central to the analysis and understanding of molecular sequence data. We present the Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package version 1.7, which implements a family of Markov chain Monte Carlo (MCMC) algorithms for Bayesian phylogenetic inference, divergence time dating, coalescent analysis, phylogeography and related molecular evolutionary analyses. This package includes an enhanced graphical user interface program called Bayesian Evolutionary Analysis Utility (BEAUti) that enables access to advanced models for molecular sequence and phenotypic trait evolution that were previously available to developers only. The package also provides new tools for visualizing and summarizing multispecies coalescent and phylogeographic analyses. BEAUti and BEAST 1.7 are open source under the GNU lesser general public license and available at http://beast-mcmc.googlecode.com and http://beast.bio.ed.ac.uk. © The Author 2012. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved.",
                        "date": "2012-08-01T00:00:00Z",
                        "citationCount": 7434,
                        "authors": [
                            {
                                "name": "Drummond A.J."
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                            {
                                "name": "Suchard M.A."
                            },
                            {
                                "name": "Xie D."
                            },
                            {
                                "name": "Rambaut A."
                            }
                        ],
                        "journal": "Molecular Biology and Evolution"
                    }
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                    "pmid": "29942656",
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                    "type": [],
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                },
                {
                    "doi": "10.1186/1471-2148-7-214",
                    "pmid": "17996036",
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                    "metadata": {
                        "title": "BEAST: Bayesian evolutionary analysis by sampling trees",
                        "abstract": "Background. The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented. Results. BEAST version 1.4.6 consists of 81000 lines of Java source code, 779 classes and 81 packages. It provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions. BEAST source code is object-oriented, modular in design and freely available at http://beast-mcmc.googlecode.com/ under the GNU LGPL license. Conclusion. BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis. © 2007 Drummond and Rambaut; licensee BioMed Central Ltd.",
                        "date": "2007-12-01T00:00:00Z",
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                        "authors": [
                            {
                                "name": "Drummond A.J."
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                            {
                                "name": "Rambaut A."
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                        "journal": "BMC Evolutionary Biology"
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