$\mathrm{LPS}=\begin{cases}\mathrm{time}\times 2 & \text{if \mathrm{time}\le 0.5}\\ 1-\frac{\mathrm{time}-0.5}{1.5} & \text{if (\mathrm{time}> 0.5)\land (\mathrm{time}< 2)}\\ 0 & \text{otherwise}\end{cases}\mathrm{v_1}=\mathrm{LPS}\mathrm{PIP_2}\mathrm{k_1}\mathrm{v_2}=\mathrm{PIP_2}\mathrm{k_2}\mathrm{v_3}=\mathrm{DG}\mathrm{k_3}\mathrm{v_4}=\mathrm{AA}\mathrm{k_4}\mathrm{v_5}=\mathrm{DG}\mathrm{GPCho}\mathrm{k_5}\mathrm{v_6}=\mathrm{LPS}\mathrm{GPCho}\mathrm{k_6}\mathrm{v_7}=\mathrm{GPCho}\mathrm{k_7}\mathrm{v_8}=\mathrm{AA}\mathrm{k_8}\mathrm{v_9}=\mathrm{HETE}\mathrm{k_9}\mathrm{v_10}=\mathrm{DG}\mathrm{AA}\mathrm{k_10}\mathrm{v_11}=\mathrm{LPS}\mathrm{AA}\mathrm{k_11}\mathrm{v_12}=\mathrm{AA}\mathrm{k_12}\mathrm{v_13}=\mathrm{PGH_2}\mathrm{k_13}\mathrm{v_14}=\mathrm{PGE_2}\mathrm{k_14}\mathrm{v_15}=\mathrm{PGH_2}\mathrm{k_15}\mathrm{v_16}=\mathrm{PGF_2a}\mathrm{k_16}\mathrm{v_17}=\mathrm{PGH_2}\mathrm{k_17}\mathrm{v_18}=\mathrm{PGD_2}\mathrm{k_18}\mathrm{v_19}=\mathrm{PGD_2}\mathrm{k_19}\mathrm{v_20}=\mathrm{dPGD_2}\mathrm{k_20}\mathrm{v_21}=\mathrm{PGJ_2}\mathrm{k_21}\mathrm{v_22}=\mathrm{dPGJ_2}\mathrm{k_22}\frac{d \mathrm{AA}}{d \mathrm{time}}}=\mathrm{v_1}+\mathrm{v_2}+\mathrm{v_3}-\mathrm{v_4}+\mathrm{v_5}+\mathrm{v_6}+\mathrm{v_7}-\mathrm{v_8}-\mathrm{v_10}-\mathrm{v_11}-\mathrm{v_12}\frac{d \mathrm{HETE}}{d \mathrm{time}}}=\mathrm{v_8}-\mathrm{v_9}\frac{d \mathrm{PGH_2}}{d \mathrm{time}}}=\mathrm{v_10}+\mathrm{v_11}+\mathrm{v_12}-\mathrm{v_13}-\mathrm{v_15}-\mathrm{v_17}\frac{d \mathrm{PGE_2}}{d \mathrm{time}}}=\mathrm{v_13}-\mathrm{v_14}\frac{d \mathrm{PGF_2a}}{d \mathrm{time}}}=\mathrm{v_15}-\mathrm{v_16}\frac{d \mathrm{PGD_2}}{d \mathrm{time}}}=\mathrm{v_17}-\mathrm{v_18}-\mathrm{v_19}\frac{d \mathrm{PGJ_2}}{d \mathrm{time}}}=\mathrm{v_18}-\mathrm{v_21}\frac{d \mathrm{dPGD_2}}{d \mathrm{time}}}=\mathrm{v_19}-\mathrm{v_20}\frac{d \mathrm{dPGJ_2}}{d \mathrm{time}}}=\mathrm{v_21}-\mathrm{v_22}$ Nunns Geoffrey Rogan gnunns1@jhu.edu The University of Auckland Auckland Bioengineering Institute 2010-05-11 The Gupta et al. 2009 integrated model of eicosanoid metabolism and signaling based on lipidomics flux analysis. This is the CellML description of Gupta et al.'s 2009 mathematical model of eicosanoid metabolism and signaling based on lipidomics flux analysis. Geoffrey Nunns keyword signal transduction metabolism lipid 19486676 Gupta S Maurya M R Stephens D L Dennis E A Subramaniam S An integrated model of eicosanoid metabolism and signaling based on lipidomics flux analysis 2009-06-03 Biophysical Journal 96 4542 4551