Machine learning-assisted identification of bioindicators predicts medium-chain carboxylate production performance of an anaerobic mixed culture (2022)
- Authors:
- Autor USP: KASMANAS, JONAS COELHO - ICMC
- Unidade: ICMC
- DOI: 10.1186/s40168-021-01219-2
- Subjects: APRENDIZADO COMPUTACIONAL; REATORES BIOQUÍMICOS; BIOINDICADORES
- Keywords: Predictive biology; Carboxylate platform; Model ecosystems; Reactor microbiota; Microbial chain elongation
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Microbiome
- ISSN: 2049-2618
- Volume/Número/Paginação/Ano: v. 10, p. 1-21, 2022
- Status:
- Artigo publicado em periódico de acesso aberto (Gold Open Access)
- Versão do Documento:
- Versão publicada (Published version)
- Acessar versão aberta:
-
ABNT
LIU, Bin et al. Machine learning-assisted identification of bioindicators predicts medium-chain carboxylate production performance of an anaerobic mixed culture. Microbiome, v. 10, p. 1-21, 2022Tradução . . Disponível em: https://doi.org/10.1186/s40168-021-01219-2. Acesso em: 02 abr. 2026. -
APA
Liu, B., Sträuber, H., Saraiva, J. P., Harms, H., Silva, S. G., Kasmanas, J. C., et al. (2022). Machine learning-assisted identification of bioindicators predicts medium-chain carboxylate production performance of an anaerobic mixed culture. Microbiome, 10, 1-21. doi:10.1186/s40168-021-01219-2 -
NLM
Liu B, Sträuber H, Saraiva JP, Harms H, Silva SG, Kasmanas JC, Kleinsteuber S, Rocha UN da. Machine learning-assisted identification of bioindicators predicts medium-chain carboxylate production performance of an anaerobic mixed culture [Internet]. Microbiome. 2022 ; 10 1-21.[citado 2026 abr. 02 ] Available from: https://doi.org/10.1186/s40168-021-01219-2 -
Vancouver
Liu B, Sträuber H, Saraiva JP, Harms H, Silva SG, Kasmanas JC, Kleinsteuber S, Rocha UN da. Machine learning-assisted identification of bioindicators predicts medium-chain carboxylate production performance of an anaerobic mixed culture [Internet]. Microbiome. 2022 ; 10 1-21.[citado 2026 abr. 02 ] Available from: https://doi.org/10.1186/s40168-021-01219-2 - MuDoGeR: multi-domain genome recovery from metagenomes made easy
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