A tutorial to identify nonlinear associations in gene expression time series data (2014)
Fujita, André 
; Miyano, Satoru
Source: Transcription factor regulatory networks: methods and protocols. Unidade: IME
Subjects: BIOINFORMÁTICA, ANÁLISE DE SÉRIES TEMPORAIS, ANÁLISE MULTIVARIADA
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ABNT
FUJITA, André e MIYANO, Satoru. A tutorial to identify nonlinear associations in gene expression time series data. Transcription factor regulatory networks: methods and protocols. Tradução . New York: Humana Press, 2014. . Disponível em: https://doi.org/10.1007/978-1-4939-0805-9_8. Acesso em: 21 jan. 2026.APA
Fujita, A., & Miyano, S. (2014). A tutorial to identify nonlinear associations in gene expression time series data. In Transcription factor regulatory networks: methods and protocols. New York: Humana Press. doi:10.1007/978-1-4939-0805-9_8NLM
Fujita A, Miyano S. A tutorial to identify nonlinear associations in gene expression time series data [Internet]. In: Transcription factor regulatory networks: methods and protocols. New York: Humana Press; 2014. [citado 2026 jan. 21 ] Available from: https://doi.org/10.1007/978-1-4939-0805-9_8Vancouver
Fujita A, Miyano S. A tutorial to identify nonlinear associations in gene expression time series data [Internet]. In: Transcription factor regulatory networks: methods and protocols. New York: Humana Press; 2014. [citado 2026 jan. 21 ] Available from: https://doi.org/10.1007/978-1-4939-0805-9_8
