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                        "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.",
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                                "name": "Madeira F."
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                                "name": "Basutkar P."
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                                "name": "Madeira F."
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                            {
                                "name": "Pearce M."
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                            {
                                "name": "Tivey A.R.N."
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                            {
                                "name": "Basutkar P."
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                        "journal": "Nucleic Acids Research"
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                        "title": "Predicting active site residue annotations in the Pfam database",
                        "abstract": "Background: Approximately 5% of Pfam families are enzymatic, but only a small fraction of the sequences within these families (<0.5%) have had the residues responsible for catalysis determined. To increase the active site annotations in the Pfam database, we have developed a strict set of rules, chosen to reduce the rate of false positives, which enable the transfer of experimentally determined active site residue data to other sequences within the same Pfam family. Description: We have created a large database of predicted active site residues. On comparing our active site predictions to those found in UniProtKB, Catalytic Site Atlas, PROSITE and MEROPS we find that we make many novel predictions. On investigating the small subset of predictions made by these databases that are not predicted by us, we found these sequences did not meet our strict criteria for prediction. We assessed the sensitivity and specificity of our methodology and estimate that only 3% of our predicted sequences are false positives. Conclusion: We have predicted 606110 active site residues, of which 94% are not found in UniProtKB, and have increased the active site annotations in Pfam by more than 200 fold. Although implemented for Pfam, the tool we have developed for transferring the data can be applied to any alignment with associated experimental active site data and is available for download. Our active site predictions are re-calculated at each Pfam release to ensure they are comprehensive and up to date. They provide one of the largest available databases of active site annotation. © 2007 Mistry et al; licensee BioMed Central Ltd.",
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                            {
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                        "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.",
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                                "name": "Basutkar P."
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                            {
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                    "url": "https://www.ebi.ac.uk/jdispatcher/help",
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                {
                    "url": "https://tcoffee.org/Projects/tcoffee/index.html",
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                        "General"
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            "publication": [
                {
                    "doi": "10.1006/jmbi.2000.4042",
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                    "metadata": {
                        "title": "T-coffee: A novel method for fast and accurate multiple sequence alignment",
                        "abstract": "We describe a new method (T-Coffee) for multiple sequence alignment that provides a dramatic improvement in accuracy with a modest sacrifice in speed as compared to the most commonly used alternatives. The method is broadly based on the popular progressive approach to multiple alignment but avoids the most serious pitfalls caused by the greedy nature of this algorithm. With T-Coffee we pre-process a data set of all pair-wise alignments between the sequences. This provides us with a library of alignment information that can be used to guide the progressive alignment. Intermediate alignments are then based not only on the sequences to be aligned next but also on how all of the sequences align with each other. This alignment information can be derived from heterogeneous sources such as a mixture of alignment programs and/or structure superposition. Here, we illustrate the power of the approach by using a combination of local and global pair-wise alignments to generate the library. The resulting alignments are significantly more reliable, as determined by comparison with a set of 141 test cases, than any of the popular alternatives that we tried. The improvement, especially clear with the more difficult test cases, is always visible, regardless of the phylogenetic spread of the sequences in the tests. (C) 2000 Academic Press.",
                        "date": "2000-09-08T00:00:00Z",
                        "citationCount": 5714,
                        "authors": [
                            {
                                "name": "Notredame C."
                            },
                            {
                                "name": "Higgins D.G."
                            },
                            {
                                "name": "Heringa J."
                            }
                        ],
                        "journal": "Journal of Molecular Biology"
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                },
                {
                    "doi": "10.1093/nar/gkae241",
                    "pmid": "38597606",
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                        "Other"
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                },
                {
                    "doi": "10.1093/nar/gkac240",
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                    "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": 867,
                        "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"
                    }
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            ],
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                {
                    "name": "Cedric Notredame",
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        {
            "name": "MegaSSR",
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                    "operation": [
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                            "uri": "http://edamontology.org/operation_0308",
                            "term": "PCR primer design"
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                            "uri": "http://edamontology.org/operation_0237",
                            "term": "Repeat sequence analysis"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0337",
                            "term": "Visualisation"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3196",
                            "term": "Genotyping"
                        }
                    ],
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                "Web application"
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            "topic": [
                {
                    "uri": "http://edamontology.org/topic_2885",
                    "term": "DNA polymorphism"
                },
                {
                    "uri": "http://edamontology.org/topic_0632",
                    "term": "Probes and primers"
                },
                {
                    "uri": "http://edamontology.org/topic_0769",
                    "term": "Workflows"
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                {
                    "uri": "http://edamontology.org/topic_0780",
                    "term": "Plant biology"
                }
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                    "doi": "10.3389/fpls.2023.1219055",
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                    "metadata": {
                        "title": "MegaSSR: a web server for large scale microsatellite identification, classification, and marker development",
                        "abstract": "Next-generation sequencing technologies have opened new avenues for using genomic data to study and develop molecular markers and improve genetic resources. Simple Sequence Repeats (SSRs) as genetic markers are increasingly used in molecular diversity and molecular breeding programs that require bioinformatics pipelines to analyze the large amounts of data. Therefore, there is an ongoing need for online tools that provide computational resources with minimal effort and maximum efficiency, including automated development of SSR markers. These tools should be flexible, customizable, and able to handle the ever-increasing amount of genomic data. Here we introduce MegaSSR (https://bioinformatics.um6p.ma/MegaSSR), a web server and a standalone pipeline that enables the design of SSR markers in any target genome. MegaSSR allows users to design targeted PCR-based primers for their selected SSR repeats and includes multiple tools that initiate computational pipelines for SSR mining, classification, comparisons, PCR primer design, in silico PCR validation, and statistical visualization. MegaSSR results can be accessed, searched, downloaded, and visualized with user-friendly web-based tools. These tools provide graphs and tables showing various aspects of SSR markers and corresponding PCR primers. MegaSSR will accelerate ongoing research in plant species and assist breeding programs in their efforts to improve current genomic resources.",
                        "date": "2023-01-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Mokhtar M.M."
                            },
                            {
                                "name": "Alsamman A.M."
                            },
                            {
                                "name": "El Allali A."
                            }
                        ],
                        "journal": "Frontiers in Plant Science"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Morad M. Mokhtar",
                    "email": "morad.mokhtar@ageri.sci.eg",
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            "name": "SynLinker",
            "description": "An integrated system to provide suitable linker candidates for novel recombinant fusion proteins.",
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            "biotoolsCURIE": "biotools:synlinker",
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                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_2479",
                            "term": "Protein sequence analysis"
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            ],
            "toolType": [
                "Web application"
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            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0078",
                    "term": "Proteins"
                },
                {
                    "uri": "http://edamontology.org/topic_0108",
                    "term": "Protein expression"
                },
                {
                    "uri": "http://edamontology.org/topic_0123",
                    "term": "Protein properties"
                },
                {
                    "uri": "http://edamontology.org/topic_3053",
                    "term": "Genetics"
                }
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            "link": [
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                    "url": "http://www.mybiosoftware.com/synlinker-designing-linkers-and-synthetic-fusion-proteins.html",
                    "type": [
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                }
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                {
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                    "pmid": "26227144",
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                    "note": null,
                    "metadata": {
                        "title": "SynLinker: An integrated system for designing linkers and synthetic fusion proteins",
                        "abstract": "Summary: Synthetic fusion proteins have shown great potential in various biotechnological and (bio)pharmaceutical applications. They usually contain more than two protein domains joined by a linker peptide sequence which is often selected intuitively or in ad hoc manner. Thus, we developed an integrated web-based system, SynLinker, to provide appropriate linker candidates for constructing fusion proteins. We compiled a total of 2260 linker sequences comprising of natural linkers extracted from a set of non-redundant multi-domain proteins in Protein Data Bank and artificial/empirical linkers collected from literature and patents. Multiple query interface allows users to search for the desired linker candidates based on selection criteria and their preferences. In addition, a selected linker can be combined with two domain structures which are uploaded and appended at its N and C terminals, thereby predicting a de novo structure of the fusion protein. Hence, SynLinker can serve as a systematic tool for researchers who are interested in designing synthetic fusion proteins. Availability and implementation: SynLinker is freely available at http://bioinfo.bti.a-star.edu.sg/synlinker.",
                        "date": "2015-05-25T00:00:00Z",
                        "citationCount": 30,
                        "authors": [
                            {
                                "name": "Liu C."
                            },
                            {
                                "name": "Chin J.X."
                            },
                            {
                                "name": "Lee D.-Y."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
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                {
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        },
        {
            "name": "COVIDep",
            "description": "COVIDep provides an up-to-date set of B-cell and T-cell epitopes that can serve as potential vaccine targets for SARS-CoV-2. The identified epitopes are experimentally-derived from the 2003 SARS virus and have a close genetic match with the available SARS-CoV-2 sequences. COVIDep is flexible and user-friendly, comprising an intuitive graphical interface and interactive visualizations.",
            "homepage": "https://covidep.ust.hk",
            "biotoolsID": "covidep",
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                            "term": "Sequence analysis"
                        },
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                            "uri": "http://edamontology.org/operation_0337",
                            "term": "Visualisation"
                        },
                        {
                            "uri": "http://edamontology.org/operation_2423",
                            "term": "Prediction and recognition"
                        },
                        {
                            "uri": "http://edamontology.org/operation_2479",
                            "term": "Protein sequence analysis"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0416",
                            "term": "Epitope mapping"
                        }
                    ],
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                    "note": null,
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            ],
            "toolType": [
                "Web application"
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            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0080",
                    "term": "Sequence analysis"
                },
                {
                    "uri": "http://edamontology.org/topic_0092",
                    "term": "Data visualisation"
                },
                {
                    "uri": "http://edamontology.org/topic_2269",
                    "term": "Statistics and probability"
                },
                {
                    "uri": "http://edamontology.org/topic_3948",
                    "term": "Immunoinformatics"
                },
                {
                    "uri": "http://edamontology.org/topic_3474",
                    "term": "Machine learning"
                }
            ],
            "operatingSystem": [
                "Linux",
                "Windows",
                "Mac"
            ],
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                "R"
            ],
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            "link": [
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                }
            ],
            "download": [
                {
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                    "type": "Source code",
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                    "version": null
                }
            ],
            "documentation": [
                {
                    "url": "https://covidep.ust.hk",
                    "type": [
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                    ],
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                }
            ],
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                {
                    "doi": "10.1038/s41596-020-0358-9",
                    "pmid": "32555466",
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                    ],
                    "version": null,
                    "note": "Ahmed, S.F., Quadeer, A.A. & McKay, M.R. COVIDep: a web-based platform for real-time reporting of vaccine target recommendations for SARS-CoV-2. Nature Protocols (2020).",
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                        "date": "2020-07-01T00:00:00Z",
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                            {
                                "name": "McKay M.R."
                            }
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        {
            "name": "EasySSR",
            "description": "A user-friendly web application with full command-line features for large-scale batch microsatellite mining and samples comparison.",
            "homepage": "https://github.com/engbiopct/EasySSR",
            "biotoolsID": "easyssr",
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                            "term": "Repeat sequence analysis"
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                    "term": "DNA polymorphism"
                },
                {
                    "uri": "http://edamontology.org/topic_0160",
                    "term": "Sequence sites, features and motifs"
                },
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                    "uri": "http://edamontology.org/topic_0091",
                    "term": "Bioinformatics"
                },
                {
                    "uri": "http://edamontology.org/topic_3168",
                    "term": "Sequencing"
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                    "uri": "http://edamontology.org/topic_0621",
                    "term": "Model organisms"
                }
            ],
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                {
                    "doi": "10.3389/FGENE.2023.1228552",
                    "pmid": "37693309",
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                    "note": null,
                    "metadata": {
                        "title": "EasySSR: a user-friendly web application with full command-line features for large-scale batch microsatellite mining and samples comparison",
                        "abstract": "Microsatellites, also known as SSRs or STRs, are polymorphic DNA regions with tandem repetitions of a nucleotide motif of size 1–6 base pairs with a broad range of applications in many fields, such as comparative genomics, molecular biology, and forensics. However, the majority of researchers do not have computational training and struggle while running command-line tools or very limited web tools for their SSR research, spending a considerable amount of time learning how to execute the software and conducting the post-processing data tabulation in other tools or manually—time that could be used directly in data analysis. We present EasySSR, a user-friendly web tool with command-line full functionality, designed for practical use in batch identifying and comparing SSRs in sequences, draft, or complete genomes, not requiring previous bioinformatic skills to run. EasySSR requires only a FASTA and an optional GENBANK file of one or more genomes to identify and compare STRs. The tool can automatically analyze and compare SSRs in whole genomes, convert GenBank to PTT files, identify perfect and imperfect SSRs and coding and non-coding regions, compare their frequencies, abundancy, motifs, flanking sequences, and iterations, producing many outputs ready for download such as PTT files, interactive charts, and Excel tables, giving the user the data ready for further analysis in minutes. EasySSR was implemented as a web application, which can be executed from any browser and is available for free at https://computationalbiology.ufpa.br/easyssr/. Tutorials, usage notes, and download links to the source code can be found at https://github.com/engbiopct/EasySSR.",
                        "date": "2023-01-01T00:00:00Z",
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                            {
                                "name": "Alves S.I.A."
                            },
                            {
                                "name": "Ferreira V.B.C."
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                                "name": "Dantas C.W.D."
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                            {
                                "name": "Silva A.L.D.C.D."
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                            {
                                "name": "Ramos R.T.J."
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                        "journal": "Frontiers in Genetics"
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                    "name": "Rommel Thiago Jucá Ramos",
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