Edinburgh Research Explorer

Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics

Research output: Contribution to journalArticle

Standard

Hybrid regulatory models : a statistically tractable approach to model regulatory network dynamics. / Ocone, Andrea; Millar, Andrew J; Sanguinetti, Guido.

In: Bioinformatics, Vol. 29, No. 7, 2013, p. 910-916.

Research output: Contribution to journalArticle

Harvard

Ocone, A, Millar, AJ & Sanguinetti, G 2013, 'Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics', Bioinformatics, vol. 29, no. 7, pp. 910-916. https://doi.org/10.1093/bioinformatics/btt069

APA

Ocone, A., Millar, A. J., & Sanguinetti, G. (2013). Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics. Bioinformatics, 29(7), 910-916. https://doi.org/10.1093/bioinformatics/btt069

Vancouver

Ocone A, Millar AJ, Sanguinetti G. Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics. Bioinformatics. 2013;29(7):910-916. https://doi.org/10.1093/bioinformatics/btt069

Author

Ocone, Andrea ; Millar, Andrew J ; Sanguinetti, Guido. / Hybrid regulatory models : a statistically tractable approach to model regulatory network dynamics. In: Bioinformatics. 2013 ; Vol. 29, No. 7. pp. 910-916.