Source: Genetics and Molecular Biology. Unidade: EACH
Assunto: AUTÔMATOS FINITOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LAVEZZO, Guilherme Miura et al. Position weight matrix or acyclic probabilistic finite automaton: which model to use? a decision rule inferred for the prediction of transcription factor binding sites. Genetics and Molecular Biology, v. 46, n. 4, p. 01-10, 2023Tradução . . Disponível em: http://dx.doi.org/10.1590/1678-4685-GMB-2023-0048. Acesso em: 30 ago. 2024.APA
Lavezzo, G. M., Lauretto, M. de S., Andrioli, L. P. M., & Lima, A. M. (2023). Position weight matrix or acyclic probabilistic finite automaton: which model to use? a decision rule inferred for the prediction of transcription factor binding sites. Genetics and Molecular Biology, 46( 4), 01-10. doi:10.1590/1678-4685-GMB-2023-0048NLM
Lavezzo GM, Lauretto M de S, Andrioli LPM, Lima AM. Position weight matrix or acyclic probabilistic finite automaton: which model to use? a decision rule inferred for the prediction of transcription factor binding sites [Internet]. Genetics and Molecular Biology. 2023 ; 46( 4): 01-10.[citado 2024 ago. 30 ] Available from: http://dx.doi.org/10.1590/1678-4685-GMB-2023-0048Vancouver
Lavezzo GM, Lauretto M de S, Andrioli LPM, Lima AM. Position weight matrix or acyclic probabilistic finite automaton: which model to use? a decision rule inferred for the prediction of transcription factor binding sites [Internet]. Genetics and Molecular Biology. 2023 ; 46( 4): 01-10.[citado 2024 ago. 30 ] Available from: http://dx.doi.org/10.1590/1678-4685-GMB-2023-0048