KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples
Minich JJ, Zhu Q, Janssen S, Hendrickson R, Amir A, Vetter R, Hyde J, Doty MM, Stillwell K, Benardini J, Kim JH, et al. (2018)
mSystems 3(3): e00218-17.
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Autor*in
Minich, Jeremiah J.;
Zhu, Qiyun;
Janssen, StefanUniBi ;
Hendrickson, Ryan;
Amir, Amnon;
Vetter, Russ;
Hyde, John;
Doty, Megan M.;
Stillwell, Kristina;
Benardini, James;
Kim, Jae H.;
Allen, Eric E.
Alle
Alle
Einrichtung
Erscheinungsjahr
2018
Zeitschriftentitel
mSystems
Band
3
Ausgabe
3
Seite(n)
e00218-17
Urheberrecht / Lizenzen
ISSN
2379-5077
Page URI
https://pub.uni-bielefeld.de/record/2921270
Zitieren
Minich JJ, Zhu Q, Janssen S, et al. KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples. mSystems. 2018;3(3):e00218-17.
Minich, J. J., Zhu, Q., Janssen, S., Hendrickson, R., Amir, A., Vetter, R., Hyde, J., et al. (2018). KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples. mSystems, 3(3), e00218-17. https://doi.org/10.1128/msystems.00218-17
Minich, Jeremiah J., Zhu, Qiyun, Janssen, Stefan, Hendrickson, Ryan, Amir, Amnon, Vetter, Russ, Hyde, John, et al. 2018. “KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples”. mSystems 3 (3): e00218-17.
Minich, J. J., Zhu, Q., Janssen, S., Hendrickson, R., Amir, A., Vetter, R., Hyde, J., Doty, M. M., Stillwell, K., Benardini, J., et al. (2018). KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples. mSystems 3, e00218-17.
Minich, J.J., et al., 2018. KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples. mSystems, 3(3), p e00218-17.
J.J. Minich, et al., “KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples”, mSystems, vol. 3, 2018, pp. e00218-17.
Minich, J.J., Zhu, Q., Janssen, S., Hendrickson, R., Amir, A., Vetter, R., Hyde, J., Doty, M.M., Stillwell, K., Benardini, J., Kim, J.H., Allen, E.E., Venkateswaran, K., Knight, R.: KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples. mSystems. 3, e00218-17 (2018).
Minich, Jeremiah J., Zhu, Qiyun, Janssen, Stefan, Hendrickson, Ryan, Amir, Amnon, Vetter, Russ, Hyde, John, Doty, Megan M., Stillwell, Kristina, Benardini, James, Kim, Jae H., Allen, Eric E., Venkateswaran, Kasthuri, and Knight, Rob. “KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples”. mSystems 3.3 (2018): e00218-17.
Daten bereitgestellt von European Bioinformatics Institute (EBI)
9 Zitationen in Europe PMC
Daten bereitgestellt von Europe PubMed Central.
Microbiome 101: Studying, Analyzing, and Interpreting Gut Microbiome Data for Clinicians.
Allaband C, McDonald D, Vázquez-Baeza Y, Minich JJ, Tripathi A, Brenner DA, Loomba R, Smarr L, Sandborn WJ, Schnabl B, Dorrestein P, Zarrinpar A, Knight R., Clin Gastroenterol Hepatol 17(2), 2019
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Allaband C, McDonald D, Vázquez-Baeza Y, Minich JJ, Tripathi A, Brenner DA, Loomba R, Smarr L, Sandborn WJ, Schnabl B, Dorrestein P, Zarrinpar A, Knight R., Clin Gastroenterol Hepatol 17(2), 2019
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Performance of Microbiome Sequence Inference Methods in Environments with Varying Biomass.
Caruso V, Song X, Asquith M, Karstens L., mSystems 4(1), 2019
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Caruso V, Song X, Asquith M, Karstens L., mSystems 4(1), 2019
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Issues and current standards of controls in microbiome research.
Hornung BVH, Zwittink RD, Kuijper EJ., FEMS Microbiol Ecol 95(5), 2019
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Hornung BVH, Zwittink RD, Kuijper EJ., FEMS Microbiol Ecol 95(5), 2019
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Controlling for Contaminants in Low-Biomass 16S rRNA Gene Sequencing Experiments.
Karstens L, Asquith M, Davin S, Fair D, Gregory WT, Wolfe AJ, Braun J, McWeeney S., mSystems 4(4), 2019
PMID: 31164452
Karstens L, Asquith M, Davin S, Fair D, Gregory WT, Wolfe AJ, Braun J, McWeeney S., mSystems 4(4), 2019
PMID: 31164452
Quantifying and Understanding Well-to-Well Contamination in Microbiome Research.
Minich JJ, Sanders JG, Amir A, Humphrey G, Gilbert JA, Knight R., mSystems 4(4), 2019
PMID: 31239396
Minich JJ, Sanders JG, Amir A, Humphrey G, Gilbert JA, Knight R., mSystems 4(4), 2019
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Vive la Persistence: Engineering Human Microbiomes in the 21st Century.
Whiteson KL., mSystems 3(2), 2018
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Whiteson KL., mSystems 3(2), 2018
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Are microbiome studies ready for hypothesis-driven research?
Tripathi A, Marotz C, Gonzalez A, Vázquez-Baeza Y, Song SJ, Bouslimani A, McDonald D, Zhu Q, Sanders JG, Smarr L, Dorrestein PC, Knight R., Curr Opin Microbiol 44(), 2018
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Tripathi A, Marotz C, Gonzalez A, Vázquez-Baeza Y, Song SJ, Bouslimani A, McDonald D, Zhu Q, Sanders JG, Smarr L, Dorrestein PC, Knight R., Curr Opin Microbiol 44(), 2018
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de Goffau MC, Lager S, Salter SJ, Wagner J, Kronbichler A, Charnock-Jones DS, Peacock SJ, Smith GCS, Parkhill J., Nat Microbiol 3(8), 2018
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de Goffau MC, Lager S, Salter SJ, Wagner J, Kronbichler A, Charnock-Jones DS, Peacock SJ, Smith GCS, Parkhill J., Nat Microbiol 3(8), 2018
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High-Throughput Miniaturized 16S rRNA Amplicon Library Preparation Reduces Costs while Preserving Microbiome Integrity.
Minich JJ, Humphrey G, Benitez RAS, Sanders J, Swafford A, Allen EE, Knight R., mSystems 3(6), 2018
PMID: 30417111
Minich JJ, Humphrey G, Benitez RAS, Sanders J, Swafford A, Allen EE, Knight R., mSystems 3(6), 2018
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