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  • Source: Computational Biology and Chemistry. Unidade: IQSC

    Subjects: NEOPLASIAS, PRÓSTATA, HIPERPLASIAS

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    • ABNT

      SANABRIA-CHANAGA, Elkin e ROZO, Edwin Leonel Bonilla. Insights from computational studies about structural determinants of steroidal inhibitors in 5-alpha-reductase type II. Computational Biology and Chemistry, v. 118, p. 108446, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.compbiolchem.2025.108446. Acesso em: 07 out. 2025.
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      Sanabria-Chanaga, E., & Rozo, E. L. B. (2025). Insights from computational studies about structural determinants of steroidal inhibitors in 5-alpha-reductase type II. Computational Biology and Chemistry, 118, 108446. doi:10.1016/j.compbiolchem.2025.108446
    • NLM

      Sanabria-Chanaga E, Rozo ELB. Insights from computational studies about structural determinants of steroidal inhibitors in 5-alpha-reductase type II [Internet]. Computational Biology and Chemistry. 2025 ;118 108446.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2025.108446
    • Vancouver

      Sanabria-Chanaga E, Rozo ELB. Insights from computational studies about structural determinants of steroidal inhibitors in 5-alpha-reductase type II [Internet]. Computational Biology and Chemistry. 2025 ;118 108446.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2025.108446
  • Source: Computational Biology and Chemistry. Unidade: EACH

    Assunto: INIBIDORES QUÍMICOS

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    • ABNT

      FLORES, Robert Malory Alarcon et al. Structural analysis of factors related to FAM3C/ILEI dimerization and identification of inhibitor candidates targeting cancer treatment. Computational Biology and Chemistry, v. 104, p. 01-16, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.compbiolchem.2023.107869. Acesso em: 07 out. 2025.
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      Flores, R. M. A., Pantaleão, S. Q., Araujo, S. C., Malpartida, H. M. G., & Honorio, K. M. (2023). Structural analysis of factors related to FAM3C/ILEI dimerization and identification of inhibitor candidates targeting cancer treatment. Computational Biology and Chemistry, 104, 01-16. doi:10.1016/j.compbiolchem.2023.107869
    • NLM

      Flores RMA, Pantaleão SQ, Araujo SC, Malpartida HMG, Honorio KM. Structural analysis of factors related to FAM3C/ILEI dimerization and identification of inhibitor candidates targeting cancer treatment [Internet]. Computational Biology and Chemistry. 2023 ; 104 01-16.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2023.107869
    • Vancouver

      Flores RMA, Pantaleão SQ, Araujo SC, Malpartida HMG, Honorio KM. Structural analysis of factors related to FAM3C/ILEI dimerization and identification of inhibitor candidates targeting cancer treatment [Internet]. Computational Biology and Chemistry. 2023 ; 104 01-16.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2023.107869
  • Source: Computational Biology and Chemistry. Unidades: FM, EACH

    Assunto: ANIMAIS

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    • ABNT

      FEITOSA, Rayssa Maria de Melo Wanderley et al. MicroRNA target prediction tools for animals: Where we are at and where we are going to -a systematic review. Computational Biology and Chemistry, p. 01-27, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.compbiolchem.2022.107729. Acesso em: 07 out. 2025.
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      Feitosa, R. M. de M. W., Oliveira, P. P., Brentani, H. P., & Lima, A. M. (2022). MicroRNA target prediction tools for animals: Where we are at and where we are going to -a systematic review. Computational Biology and Chemistry, 01-27. doi:10.1016/j.compbiolchem.2022.107729
    • NLM

      Feitosa RM de MW, Oliveira PP, Brentani HP, Lima AM. MicroRNA target prediction tools for animals: Where we are at and where we are going to -a systematic review [Internet]. Computational Biology and Chemistry. 2022 ; 01-27.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2022.107729
    • Vancouver

      Feitosa RM de MW, Oliveira PP, Brentani HP, Lima AM. MicroRNA target prediction tools for animals: Where we are at and where we are going to -a systematic review [Internet]. Computational Biology and Chemistry. 2022 ; 01-27.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2022.107729
  • Source: Computational Biology and Chemistry. Unidade: IQSC

    Assunto: TUBERCULOSE

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      MAY, Elebeoba E. e LEITÃO, Andrei e TROPSHA, Alexander. A systems chemical biology study of malate synthase and isocitrate lyase inhibition in mycobacterium tuberculosis during active and NRP growth. Computational Biology and Chemistry, v. 47, p. 167-180, 2013Tradução . . Disponível em: https://doi.org/10.1016/j.compbiolchem.2013.07.002. Acesso em: 07 out. 2025.
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      May, E. E., Leitão, A., & Tropsha, A. (2013). A systems chemical biology study of malate synthase and isocitrate lyase inhibition in mycobacterium tuberculosis during active and NRP growth. Computational Biology and Chemistry, 47, 167-180. doi:10.1016/j.compbiolchem.2013.07.002
    • NLM

      May EE, Leitão A, Tropsha A. A systems chemical biology study of malate synthase and isocitrate lyase inhibition in mycobacterium tuberculosis during active and NRP growth [Internet]. Computational Biology and Chemistry. 2013 ; 47 167-180.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2013.07.002
    • Vancouver

      May EE, Leitão A, Tropsha A. A systems chemical biology study of malate synthase and isocitrate lyase inhibition in mycobacterium tuberculosis during active and NRP growth [Internet]. Computational Biology and Chemistry. 2013 ; 47 167-180.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2013.07.002
  • Source: Computational Biology and Chemistry. Unidade: IF

    Subjects: ENZIMAS (ESTRUTURA), BIOINFORMÁTICA, FÍSICO-QUÍMICA

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    • ABNT

      BOARETO, Marcelo et al. Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction. Computational Biology and Chemistry, v. 40, p. 15-19, 2012Tradução . . Disponível em: https://doi.org/10.1016/j.compbiolchem.2012.06.003. Acesso em: 07 out. 2025.
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      Boareto, M., Yamagishi, M. E. B., Leite, V. B. P., & Caticha, N. (2012). Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction. Computational Biology and Chemistry, 40, 15-19. doi:10.1016/j.compbiolchem.2012.06.003
    • NLM

      Boareto M, Yamagishi MEB, Leite VBP, Caticha N. Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction [Internet]. Computational Biology and Chemistry. 2012 ;40 15-19.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2012.06.003
    • Vancouver

      Boareto M, Yamagishi MEB, Leite VBP, Caticha N. Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction [Internet]. Computational Biology and Chemistry. 2012 ;40 15-19.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2012.06.003

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