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dc.contributor.authorMabwi, H.A.-
dc.contributor.authorKim, Eun jung-
dc.contributor.authorSong, Dae-Geun-
dc.contributor.authorYoon, Hyo Shin-
dc.contributor.authorPAN, CHEOL HO-
dc.contributor.authorKomba, E.V.G.-
dc.contributor.authorKo, Gwangpyo-
dc.contributor.authorCha, Kwang Hyun-
dc.date.accessioned2024-01-19T15:34:11Z-
dc.date.available2024-01-19T15:34:11Z-
dc.date.created2021-09-02-
dc.date.issued2021-01-
dc.identifier.issn2001-0370-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/117589-
dc.description.abstractAn exponential rise in studies regarding the association among human gut microbial communities, human health, and diseases is currently attracting the attention of researchers to focus on human gut microbiome research. However, even with the ever-growing number of studies on the human gut microbiome, translation into improved health is progressing slowly. This hampering is due to the complexities of the human gut microbiome, which is composed of >1,000 species of microorganisms, such as bacteria, archaea, viruses, and fungi. To overcome this complexity, it is necessary to reduce the gut microbiome, which can help simplify experimental variables to an extent, such that they can be deliberately manipulated and controlled. Reconstruction of synthetic or established gut microbial communities would make it easier to understand the structure, stability, and functional activities of the complex microbial community of the human gut. Here, we provide an overview of the developments and challenges of the synthetic human gut microbiome, and propose the incorporation of multi-omics and mathematical methods in a better synthetic gut ecosystem design, for easy translation of microbiome information to therapies. ? 2020 The Author(s)-
dc.languageEnglish-
dc.publisherElsevier B.V.-
dc.titleSynthetic gut microbiome: Advances and challenges-
dc.typeArticle-
dc.identifier.doi10.1016/j.csbj.2020.12.029-
dc.description.journalClass1-
dc.identifier.bibliographicCitationComputational and Structural Biotechnology Journal, v.19, pp.363 - 371-
dc.citation.titleComputational and Structural Biotechnology Journal-
dc.citation.volume19-
dc.citation.startPage363-
dc.citation.endPage371-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000684869700007-
dc.identifier.scopusid2-s2.0-85098722169-
dc.relation.journalWebOfScienceCategoryBiochemistry & Molecular Biology-
dc.relation.journalWebOfScienceCategoryBiotechnology & Applied Microbiology-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaBiotechnology & Applied Microbiology-
dc.type.docTypeArticle-
dc.subject.keywordPlusBiotechnology-
dc.subject.keywordPlusMedicine-
dc.subject.keywordPlusArchaea-
dc.subject.keywordPlusFunctional activities-
dc.subject.keywordPlusHuman guts-
dc.subject.keywordPlusHuman health-
dc.subject.keywordPlusMathematical method-
dc.subject.keywordPlusMicrobial communities-
dc.subject.keywordPlusMicrobiome-
dc.subject.keywordPlusViruses-
dc.subject.keywordPlusclinical feature-
dc.subject.keywordPlusecosystem-
dc.subject.keywordPlushuman-
dc.subject.keywordPlusintestine flora-
dc.subject.keywordPlusmathematical model-
dc.subject.keywordPlusmultiomics-
dc.subject.keywordPlusnonhuman-
dc.subject.keywordPlusomics-
dc.subject.keywordPluspriority journal-
dc.subject.keywordPlusReview-
dc.subject.keywordAuthorGut ecosystem-
dc.subject.keywordAuthorMathematical modelling-
dc.subject.keywordAuthorOmics-
dc.subject.keywordAuthorSynthetic microbiota-
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KIST Article > 2021
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