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- Publisher Website: 10.1007/s12551-020-00724-2
- Scopus: eid_2-s2.0-85087653705
- PMID: 32638331
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Article: Challenges and emerging systems biology approaches to discover how the human gut microbiome impact host physiology
Title | Challenges and emerging systems biology approaches to discover how the human gut microbiome impact host physiology |
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Authors | |
Keywords | Metagenomic Microbiome Big data Systems biology Ecological modelling |
Issue Date | 2020 |
Publisher | Springer (part of Springer Nature). The Journal's web site is located at https://www.springer.com/journal/12551 |
Citation | Biophysical Reviews, 2020, v. 12, p. 851-863 How to Cite? |
Abstract | Research in the human gut microbiome has bloomed with advances in next generation sequencing (NGS) and other high-throughput molecular profiling technologies. This has enabled the generation of multi-omics datasets which holds promises for big data–enabled knowledge acquisition in the form of understanding the normal physiological and pathological involvement of gut microbiomes. Ample evidence suggests that distinct microbial compositions in the human gut are associated with different diseases. However, the biological mechanisms underlying these associations are often unclear. There is a need to move beyond statistical associations to discover how changes in the gut microbiota mechanistically affect host physiology and disease development. This review summarises state-of-the-art big data and systems biology approaches for mechanism discovery. |
Persistent Identifier | http://hdl.handle.net/10722/284001 |
ISSN | 2023 Impact Factor: 4.9 2023 SCImago Journal Rankings: 1.145 |
PubMed Central ID |
DC Field | Value | Language |
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dc.contributor.author | Qian, G | - |
dc.contributor.author | Ho, JWK | - |
dc.date.accessioned | 2020-07-20T05:55:14Z | - |
dc.date.available | 2020-07-20T05:55:14Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Biophysical Reviews, 2020, v. 12, p. 851-863 | - |
dc.identifier.issn | 1867-2450 | - |
dc.identifier.uri | http://hdl.handle.net/10722/284001 | - |
dc.description.abstract | Research in the human gut microbiome has bloomed with advances in next generation sequencing (NGS) and other high-throughput molecular profiling technologies. This has enabled the generation of multi-omics datasets which holds promises for big data–enabled knowledge acquisition in the form of understanding the normal physiological and pathological involvement of gut microbiomes. Ample evidence suggests that distinct microbial compositions in the human gut are associated with different diseases. However, the biological mechanisms underlying these associations are often unclear. There is a need to move beyond statistical associations to discover how changes in the gut microbiota mechanistically affect host physiology and disease development. This review summarises state-of-the-art big data and systems biology approaches for mechanism discovery. | - |
dc.language | eng | - |
dc.publisher | Springer (part of Springer Nature). The Journal's web site is located at https://www.springer.com/journal/12551 | - |
dc.relation.ispartof | Biophysical Reviews | - |
dc.subject | Metagenomic | - |
dc.subject | Microbiome | - |
dc.subject | Big data | - |
dc.subject | Systems biology | - |
dc.subject | Ecological modelling | - |
dc.title | Challenges and emerging systems biology approaches to discover how the human gut microbiome impact host physiology | - |
dc.type | Article | - |
dc.identifier.email | Ho, JWK: jwkho@hku.hk | - |
dc.identifier.authority | Ho, JWK=rp02436 | - |
dc.description.nature | link_to_OA_fulltext | - |
dc.identifier.doi | 10.1007/s12551-020-00724-2 | - |
dc.identifier.pmid | 32638331 | - |
dc.identifier.pmcid | PMC7429608 | - |
dc.identifier.scopus | eid_2-s2.0-85087653705 | - |
dc.identifier.hkuros | 311052 | - |
dc.identifier.volume | 12 | - |
dc.identifier.spage | 851 | - |
dc.identifier.epage | 863 | - |
dc.publisher.place | Germany | - |
dc.identifier.issnl | 1867-2450 | - |