Cite
Efficient computation of adjoint sensitivities at steady-state in ODE models of biochemical reaction networks.
MLA
Lakrisenko, Polina, et al. “Efficient Computation of Adjoint Sensitivities at Steady-State in ODE Models of Biochemical Reaction Networks.” PLoS Computational Biology, vol. 19, no. 1, Jan. 2023, pp. 1–19. EBSCOhost, https://doi.org/10.1371/journal.pcbi.1010783.
APA
Lakrisenko, P., Stapor, P., Grein, S., Paszkowski, Ł., Pathirana, D., Fröhlich, F., Lines, G. T., Weindl, D., & Hasenauer, J. (2023). Efficient computation of adjoint sensitivities at steady-state in ODE models of biochemical reaction networks. PLoS Computational Biology, 19(1), 1–19. https://doi.org/10.1371/journal.pcbi.1010783
Chicago
Lakrisenko, Polina, Paul Stapor, Stephan Grein, Łukasz Paszkowski, Dilan Pathirana, Fabian Fröhlich, Glenn Terje Lines, Daniel Weindl, and Jan Hasenauer. 2023. “Efficient Computation of Adjoint Sensitivities at Steady-State in ODE Models of Biochemical Reaction Networks.” PLoS Computational Biology 19 (1): 1–19. doi:10.1371/journal.pcbi.1010783.