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Artigo de periodico
Insights from computational studies about structural determinants of steroidal inhibitors in 5-alpha-reductase type II (2025)
Sanabria-Chanaga, Elkin; Rozo, Edwin Leonel Bonilla
Fonte: Computational Biology and Chemistry. Unidade: IQSC
Assuntos: 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.
APA
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
Artigo de periodico
A Boolean model of the oncogene role of FAM111B in lung adenocarcinoma (2023)
Gupta, Shantanu ; Silveira, Daner Acunha; Hashimoto, Ronaldo Fumio
Fonte: Computational Biology and Chemistry. Unidade: IME
Assuntos: ÁLGEBRAS DE BOOLE, COMPUTAÇÃO APLICADA, NEOPLASIAS PULMONARES
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ABNT
GUPTA, Shantanu e SILVEIRA, Daner Acunha e HASHIMOTO, Ronaldo Fumio. A Boolean model of the oncogene role of FAM111B in lung adenocarcinoma. Computational Biology and Chemistry, v. 106, p. 1-6, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.compbiolchem.2023.107926. Acesso em: 07 out. 2025.
APA
Gupta, S., Silveira, D. A., & Hashimoto, R. F. (2023). A Boolean model of the oncogene role of FAM111B in lung adenocarcinoma. Computational Biology and Chemistry, 106, 1-6. doi:10.1016/j.compbiolchem.2023.107926
NLM
Gupta S, Silveira DA, Hashimoto RF. A Boolean model of the oncogene role of FAM111B in lung adenocarcinoma [Internet]. Computational Biology and Chemistry. 2023 ; 106 1-6.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2023.107926
Vancouver
Gupta S, Silveira DA, Hashimoto RF. A Boolean model of the oncogene role of FAM111B in lung adenocarcinoma [Internet]. Computational Biology and Chemistry. 2023 ; 106 1-6.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compbiolchem.2023.107926
Artigo de periodico
Structural analysis of factors related to FAM3C/ILEI dimerization and identification of inhibitor candidates targeting cancer treatment (2023)
Flores, Robert Malory Alarcon; Pantaleão, Simone Queiroz ; Araujo, Sheila Cruz; Malpartida, Humberto Miguel Garay ; Honorio, Kathia Maria
Fonte: 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.
APA
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
Artigo de periodico
MicroRNA target prediction tools for animals: Where we are at and where we are going to -a systematic review (2022)
Feitosa, Rayssa Maria de Melo Wanderley; Oliveira, Paula Prieto; Brentani, Helena Paula ; Lima, Ariane Machado
Fonte: 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.
APA
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
Artigo de periodico
A systems chemical biology study of malate synthase and isocitrate lyase inhibition in mycobacterium tuberculosis during active and NRP growth (2013)
May, Elebeoba E.; Leitão, Andrei ; Tropsha, Alexander
Fonte: Computational Biology and Chemistry. Unidade: IQSC
Assunto: TUBERCULOSE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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.
APA
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
Artigo de periodico
Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction (2012)
Boareto, Marcelo; Yamagishi, Michel E B; Leite, Vitor B P; Caticha, Nestor
Fonte: Computational Biology and Chemistry. Unidade: IF
Assuntos: ENZIMAS (ESTRUTURA), BIOINFORMÁTICA, FÍSICO-QUÍMICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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.
APA
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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