ArticleJournal of integrative bioinformatics2020
Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB).
Article in Journal of integrative bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- DNA-based occurrence dataset on peatland fungal communities studied by metabarcoding in north-western Siberia.Biodiversity data journal · 2024Article
- Multiple graphical views for automatically generating SQL for the MycoDiversity DB; making fungal biodiversity studies accessible.Biodiversity data journal · 2024Article
- How Deep Can the Endophytic Mycobiome Go? A Case Study on Six Woody Species from the Brazilian Cerrado.Journal of fungi (Basel, Switzerland) · 2023Article
- A roadmap to understanding diversity and function of coral reef-associated fungi.FEMS microbiology reviews · 2022Article
- FAIR Genomes metadata schema promoting Next Generation Sequencing data reuse in Dutch healthcare and research.Scientific data · 2022Article
- DNA Metabarcoding for the Characterization of Terrestrial Microbiota-Pitfalls and Solutions.Microorganisms · 2021Review
Corrections and comments
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Authors and funding
10 authors.
Funding
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Abstract
Fungi have crucial roles in ecosystems, and are important associates for many organisms. They are adapted to a wide variety of habitats, however their global distribution and diversity remains poorly documented. The exponential growth of DNA barcode information retrieved from the environment is assisting considerably the traditional ways for unraveling fungal diversity and detection. The raw DNA data in association to environmental descriptors of metabarcoding studies are made available in public sequence read archives. While this is potentially a valuable source of information for the investigation of Fungi across diverse environmental conditions, the annotation used to describe environment is heterogenous. Moreover, a uniform processing pipeline still needs to be applied to the available raw DNA data. Hence, a comprehensive framework to analyses these data in a large context is still lacking. We introduce the MycoDiversity DataBase, a database which includes public fungal metabarcoding data of environmental samples for the study of biodiversity patterns of Fungi. The framework we propose will contribute to our understanding of fungal biodiversity and aims to become a valuable source for large-scale analyses of patterns in space and time, in addition to assisting evolutionary and ecological research on Fungi.
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