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Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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Ley,  R
Department Microbiome Science, Max Planck Institute for Developmental Biology, Max Planck Society;

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Walters,  W
Department Microbiome Science, Max Planck Institute for Developmental Biology, Max Planck Society;

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引用

Bolyen, E., Rideout, J., Dillon, M., Bokulich, N., Abnet, C., Al-Ghalith, G., Alexander, H., Alm, E., Arumugam, M., Asnicar, F., Bai, Y., Bisanz, J., Bittinger, K., Brejnrod, A., Brislawn, C., Brown, C., Callahan, B., Caraballo-Rodríguez, A., Chase, J., Cope, E., Da Silva, R., Diener, C., Dorrestein, P., Douglas, G., Durall, D., Duvallet, C., Edwardson, C., Ernst, M., Estaki, M., Fouquier, J., Gauglitz, J., Gibbons, S., Gibson, D., Gonzalez, A., Gorlick, K., Guo, J., Hillmann, B., Holmes, S., Holste, H., Huttenhower, C., Huttley, G., Janssen, S., Jarmusch, A., Jiang, L., Kaehler, B., Kang, K., Keefe, C., Keim, P., Kelley, S., Knights, D., Koester, I., Kosciolek, T., Kreps, J., Langille, M., Lee, J., Ley, R., Liu, Y.-X., Loftfield, E., Lozupone, C., Maher, M., Marotz, C., Martin, B., McDonald, D., McIver, L., Melnik, A., Metcalf, J., Morgan, S., Morton, J., Naimey, A., Navas-Molina, J., Nothias, L., Orchanian, S., Pearson, T., Peoples, S., Petras, D., Preuss, M., Pruesse, E., Rasmussen, L., Rivers, A., Robeson 2nd, M., Rosenthal, P., Segata, N., Shaffer, M., Shiffer, A., Sinha, R., Song, S., Spear, J., Swafford, A., Thompson, L., Torres, P., Trinh, P., Tripathi, A., Turnbaugh, P., Ul-Hasan, S., van der Hooft, J., Vargas, F., Vázquez-Baeza, Y., Vogtmann, E., von Hippel, M., Walters, W., Wan, Y., Wang, M., Warren, J., Weber, K., Williamson, C., Willis, A., Xu, Z., Zaneveld, J., Zhang, Y., Zhu, Q., Knight, R., & Caporaso, J. (2019). Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology, 37(8), 852-857. doi:10.1038/s41587-019-0209-9.


引用: https://hdl.handle.net/21.11116/0000-000A-6738-4
要旨
Rapid advances in DNA-sequencing and bioinformatics technologies in the past two decades have substantially improved understanding of the microbial world. This growing understanding relates to the vast diversity of microorganisms; how microbiota and microbiomes affect disease1 and medical treatment2; how microorganisms affect the health of the planet3; and the nascent exploration of the medical4, forensic5, environmental6 and agricultural7 applications of microbiome biotechnology. Much of this work has been driven by marker-gene surveys (for example, bacterial/archaeal 16S rRNA genes, fungal internal-transcribed-spacer regions and eukaryotic 18S rRNA genes), which profile microbiota with varying degrees of taxonomic specificity and phylogenetic information. The field is now transitioning to integrate other data types, such as metabolite8, metaproteome9 or metatranscriptome9,10 profiles.