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UNLABELLED: The Plant rDNA database (www.plantrdnadatabase.com) is an open access online resource providing detailed information on numbers, structures and positions of 5S and 18S-5.8S-26S (35S) ribosomal DNA loci. The data have been obtained from >600 publications on plant molecular cytogenetics, mostly based on fluorescent in situ hybridization (FISH). This edition of the database contains information on 1609 species derived from 2839 records, which means an expansion of 55.76 and 94.45%, respectively. It holds the data for angiosperms, gymnosperms, bryophytes and pteridophytes available as of June 2013. Information from publications reporting data for a single rDNA (either 5S or 35S alone) and annotation regarding transcriptional activity of 35S loci now appears in the database. Preliminary analyses suggest greater variability in the number of rDNA loci in gymnosperms than in angiosperms. New applications provide ideograms of the species showing the positions of rDNA loci as well as a visual representation of their genome sizes. We have also introduced other features to boost the usability of the Web interface, such as an application for convenient data export and a new section with rDNA-FISH-related information (mostly detailing protocols and reagents). In addition, we upgraded and/or proofread tabs and links and modified the website for a more dynamic appearance. This manuscript provides a synopsis of these changes and developments. DATABASE URL: http://www.plantrdnadatabase.com.
Secondary data structure of RNA molecules provides insights into the identity and function of RNAs. With RNAs readily sequenced, the question of their structural characterization is increasingly important. However, RNA structure is difficult to acquire. Its experimental identification is extremely technically demanding, while computational prediction is not accurate enough, especially for large structures of long sequences. We address this difficult situation with rPredictorDB, a predictive database of RNA secondary structures that aims to form a middle ground between experimentally identified structures in PDB and predicted consensus secondary structures in Rfam. The database contains individual secondary structures predicted using a tool for template-based prediction of RNA secondary structure for the homologs of the RNA families with at least one homolog with experimentally solved structure. Experimentally identified structures are used as the structural templates and thus the prediction has higher reliability than de novo predictions in Rfam. The sequences are downloaded from public resources. So far rPredictorDB covers 7365 RNAs with their secondary structures. Plots of the secondary structures use the Traveler package for readable display of RNAs with long sequences and complex structures, such as ribosomal RNAs. The RNAs in the output of rPredictorDB are extensively annotated and can be viewed, browsed, searched and downloaded according to taxonomic, sequence and structure data. Additionally, structure of user-provided sequences can be predicted using the templates stored in rPredictorDB.
- MeSH
- informační systémy MeSH
- lékařská informatika MeSH
- počítačové komunikační sítě MeSH
- veřejné zdravotnictví MeSH
- Geografické názvy
- Evropa MeSH
Národní databáze genotypů je projekt, jehož cílem je navržení struktury a pravidel fungování databáze genotypů jednotlivých osob. Tato databáze by měla sloužit výhradně pro potřeby zdravotní péče. Jejím účelem je umožnit lékařům snadný a rychlý přístup k informacím o osobách vyžadujících specializovanou péči z důvodu jejich genetické výbavy. V budoucnu lze předpokládat zavádění dalších genetických vyšetření do klinické praxe, databáze genotypů by proto měla umožnit dosáhnout i značných finančních úspor vyloučením zbytečných opakování nákladných genetických vyšetření. Etické otázky, které jsou se vznikem a provozem takovéto databáze spjaty, se týkají především ochrany soukromí, důvěrnosti citlivých osobních údajů, zabezpečení databáze proti možnému zneužití, souhlasu se zařazením do databáze a veřejných zájmů. Diskutována je i určitá kategorizace genetických údajů v rámci Národní databáze genotypů vzhledem k nutnosti jejich správné interpretace kvalifikovaným odborníkem. Kromě řešení těchto etických otázek je vznik a provoz databáze nutné podřídit obecně závazným právním předpisům a vyřešit možnost postupů v rámci českého právního řádu.
The aim of the project National Database of Genotypes is to outline structure and rules for the database operation collecting information about genotypes of individual persons. The database should be used entirely for health care. Its purpose is to enable physicians to gain quick and easy access to the information about persons requiring specialized care due to their genetic constitution. In the future, another introduction of new genetic tests into the clinical practice can be expected thus the database of genotypes facilitates substantial financial savings by exclusion of duplicates of the expensive genetic testing. Ethical questions connected with the creating and functioning of such database concern mainly privacy protection, confidentiality of personal sensitive data, protection of database from misuse, consent with participation and public interests. Due to necessity of correct interpretation by qualified professional (= clinical geneticist), particular categorization of genetic data within the database is discussed. The function of proposed database has to be governed in concordance with the Czech legislation together with solving ethical problems.
- Klíčová slova
- právní rámec v České republice,
- MeSH
- bioetická témata MeSH
- databáze genetické etika zákonodárství a právo MeSH
- genotyp MeSH
- lidé MeSH
- ochrana genetických informací etika zákonodárství a právo MeSH
- Check Tag
- lidé MeSH
- Geografické názvy
- Česká republika MeSH
The presence of SARS-CoV-2 RNA in wastewater was first reported in March 2020. Over the subsequent months, the potential for wastewater surveillance to contribute to COVID-19 mitigation programmes has been the focus of intense national and international research activities, gaining the attention of policy makers and the public. As a new application of an established methodology, focused collaboration between public health practitioners and wastewater researchers is essential to developing a common understanding on how, when and where the outputs of this non-invasive community-level approach can deliver actionable outcomes for public health authorities. Within this context, the NORMAN SCORE "SARS-CoV-2 in sewage" database provides a platform for rapid, open access data sharing, validated by the uploading of 276 data sets from nine countries to-date. Through offering direct access to underpinning meta-data sets (and describing its use in data interpretation), the NORMAN SCORE database is a resource for the development of recommendations on minimum data requirements for wastewater pathogen surveillance. It is also a tool to engage public health practitioners in discussions on use of the approach, providing an opportunity to build mutual understanding of the demand and supply for data and facilitate the translation of this promising research application into public health practice.
- MeSH
- COVID-19 * MeSH
- lidé MeSH
- odpadní voda MeSH
- RNA virová MeSH
- SARS-CoV-2 * MeSH
- veřejné zdravotnictví MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
IRESite is an exhaustive, manually annotated non-redundant relational database focused on the IRES elements (Internal Ribosome Entry Site) and containing information not available in the primary public databases. IRES elements were originally found in eukaryotic viruses hijacking initiation of translation of their host. Later on, they were also discovered in 5'-untranslated regions of some eukaryotic mRNA molecules. Currently, IRESite presents up to 92 biologically relevant aspects of every experiment, e.g. the nature of an IRES element, its functionality/defectivity, origin, size, sequence, structure, its relative position with respect to surrounding protein coding regions, positive/negative controls used in the experiment, the reporter genes used to monitor IRES activity, the measured reporter protein yields/activities, and references to original publications as well as cross-references to other databases, and also comments from submitters and our curators. Furthermore, the site presents the known similarities to rRNA sequences as well as RNA-protein interactions. Special care is given to the annotation of promoter-like regions. The annotated data in IRESite are bound to mostly complete, full-length mRNA, and whenever possible, accompanied by original plasmid vector sequences. New data can be submitted through the publicly available web-based interface at http://www.iresite.org and are curated by a team of lab-experienced biologists.
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- databáze nukleových kyselin MeSH
- financování organizované MeSH
- iniciace translace peptidového řetězce MeSH
- iniciační faktory metabolismus MeSH
- internet MeSH
- messenger RNA chemie MeSH
- nepřekládané oblasti chemie MeSH
- plazmidy chemie MeSH
- promotorové oblasti (genetika) MeSH
- regulační sekvence ribonukleových kyselin MeSH
- RNA virová chemie MeSH
- uživatelské rozhraní počítače MeSH
The European Chemical Biology Database (ECBD, https://ecbd.eu) serves as the central repository for data generated by the EU-OPENSCREEN research infrastructure consortium. It is developed according to FAIR principles, which emphasize findability, accessibility, interoperability and reusability of data. This data is made available to the scientific community following open access principles. The ECBD stores both positive and negative results from the entire chemical biology project pipeline, including data from primary or counter-screening assays. The assays utilize a defined and diverse library of over 107 000 compounds, the annotations of which are continuously enriched by external user supported screening projects and by internal EU-OPENSCREEN bioprofiling efforts. These compounds were screened in 89 currently deposited datasets (assays), with 48 already being publicly accessible, while the remaining will be published after a publication embargo period of up to 3 years. Together these datasets encompass ∼4.3 million experimental data points. All public data within ECBD can be accessed through its user interface, API or by database dump under the CC-BY 4.0 license.
OBJECTIVE: The purpose of this article is to describe current research trends in medical tourism and implications for public health, especially in destination countries. METHODS: The methods used for this article include a literature review of available sources on the research topic in the world's acknowledged databases Web of Science, Scopus, MEDLINE, and ScienceDirect. RESULTS: The findings indicate that there is no consensus on the definition of medical tourism. However, there are a few conceptual models which can be used in further medical tourism research and practice. The findings also reveal that there are still certain issues, which hinder the fast growth of medical tourism, such as unclear impact on healthcare systems, ethical concerns or a lack of effective tools for the measurement of quality assurance of the medical tourism services and their products. CONCLUSIONS: There is a need for data collection on medical tourism, both at national and worldwide level to provide a realistic picture of this evolving field of tourism as well as implications for public health in destination countries.
- MeSH
- lidé MeSH
- veřejné zdravotnictví MeSH
- výzkum trendy MeSH
- zdravotní turistika * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Emerging infectious diseases (EIDs) are a severe problem caused by fungi in human and plant species across the world. They pose a worldwide threat to food security as well as human health. Fungal infections are increasing now day by day worldwide, and the current antimycotic drugs are not effective due to the emergence of resistant strains. Therefore, it is an urgent need for the finding of new plant-origin antifungal peptides (PhytoAFPs). Huge numbers of peptides were extracted from different plant species which play a protective role against fungal infection. Hundreds of plant-origin peptides with antifungal activity have already been reported. So there is a requirement of a dedicated platform which systematically catalogs plant-origin peptides along with their antifungal properties. PlantAFP database is a resource of experimentally verified plant-origin antifungal peptides, collected from research articles, patents, and public databases. The current release of PlantAFP database contains 2585 peptide entries among which 510 are unique peptides. Each entry provides comprehensive information of a peptide that includes its peptide sequence, peptide name, peptide class, length of the peptide, molecular mass, antifungal activity, and origin of peptides. Besides this primary information, PlantAFP stores peptide sequences in SMILES format. In order to facilitate the user, many tools have been integrated into this database that includes BLAST search, peptide search, SMILES search, and peptide-mapping is also included in the database. PlantAFP database is accessible at http://bioinformatics.cimap.res.in/sharma/PlantAFP/.
