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  • Artigo de periodico

    Machine learning-assisted identification of bioindicators predicts medium-chain carboxylate production performance of an anaerobic mixed culture (2022)

    Liu, Bin; Sträuber, Heike ; Saraiva, João Pedro ; Harms, Hauke ; Silva, Sandra Godinho ; Kasmanas, Jonas Coelho ; Kleinsteuber, Sabine ; Rocha, Ulisses Nunes da

    Fonte: Microbiome. Unidade: ICMC

    Assuntos: APRENDIZADO COMPUTACIONAL, REATORES BIOQUÍMICOS, BIOINDICADORES

    Versão PublicadaAcesso à fonteDOIComo citar
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • 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: 05 dez. 2025.

    • 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 2025 dez. 05 ] 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 2025 dez. 05 ] Available from: https://doi.org/10.1186/s40168-021-01219-2

  • Artigo de periodico

    Exploring nucleation pathways in distinct physicochemical environments unveiling novel options to modulate and optimize protein crystallization (2022)

    Wang, Mengying; Barra, Angélica Luana Carrilho ; Brognaro, Hévila; Betzel, Christian

    Fonte: Crystals. Unidade: IFSC

    Assuntos: NUCLEAÇÃO, CRISTALIZAÇÃO

    Versão PublicadaAcesso à fonteDOIComo citar
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      WANG, Mengying et al. Exploring nucleation pathways in distinct physicochemical environments unveiling novel options to modulate and optimize protein crystallization. Crystals, v. 12, n. 3, p. 437-1-437-22, 2022Tradução . . Disponível em: https://doi.org/10.3390/cryst12030437. Acesso em: 05 dez. 2025.

    • APA

      Wang, M., Barra, A. L. C., Brognaro, H., & Betzel, C. (2022). Exploring nucleation pathways in distinct physicochemical environments unveiling novel options to modulate and optimize protein crystallization. Crystals, 12( 3), 437-1-437-22. doi:10.3390/cryst12030437

    • NLM

      Wang M, Barra ALC, Brognaro H, Betzel C. Exploring nucleation pathways in distinct physicochemical environments unveiling novel options to modulate and optimize protein crystallization [Internet]. Crystals. 2022 ; 12( 3): 437-1-437-22.[citado 2025 dez. 05 ] Available from: https://doi.org/10.3390/cryst12030437

    • Vancouver

      Wang M, Barra ALC, Brognaro H, Betzel C. Exploring nucleation pathways in distinct physicochemical environments unveiling novel options to modulate and optimize protein crystallization [Internet]. Crystals. 2022 ; 12( 3): 437-1-437-22.[citado 2025 dez. 05 ] Available from: https://doi.org/10.3390/cryst12030437
  • 1

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