Prevalence of Multistationarity and Absolute Concentration Robustness in Reaction Networks
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Prevalence of Multistationarity and Absolute Concentration Robustness in Reaction Networks. / Joshi, Badal; Kaihnsa, Nidhi; Nguyen, Tung D.; Shiu, Anne.
In: SIAM Journal on Applied Mathematics, Vol. 83, No. 6, 2023, p. 2260-2283.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Prevalence of Multistationarity and Absolute Concentration Robustness in Reaction Networks
AU - Joshi, Badal
AU - Kaihnsa, Nidhi
AU - Nguyen, Tung D.
AU - Shiu, Anne
PY - 2023
Y1 - 2023
N2 - For reaction networks arising in systems biology, the capacity for two or more steady states, that is, multistationarity, is an important property that underlies biochemical switches. Another property receiving much attention recently is absolute concentration robustness (ACR), which means that some species concentration is the same at all positive steady states. In this work, we investigate the prevalence of each property while paying close attention to when the properties occur together. Specifically, we consider a stochastic block framework for generating random networks and prove edge-probability thresholds at which, with high probability, multistationarity appears and ACR becomes rare. We also show that the small window in which both properties occur only appears in networks with many species. Taken together, our results confirm that, in random reversible networks, ACR and multistationarity together, or even ACR on its own, is highly atypical. Our proofs rely on two prior results, one pertaining to the prevalence of networks with deficiency zero and the other ``lifting"" multistationarity from small networks to larger ones. © 2023 Society for Industrial and Applied Mathematics.
AB - For reaction networks arising in systems biology, the capacity for two or more steady states, that is, multistationarity, is an important property that underlies biochemical switches. Another property receiving much attention recently is absolute concentration robustness (ACR), which means that some species concentration is the same at all positive steady states. In this work, we investigate the prevalence of each property while paying close attention to when the properties occur together. Specifically, we consider a stochastic block framework for generating random networks and prove edge-probability thresholds at which, with high probability, multistationarity appears and ACR becomes rare. We also show that the small window in which both properties occur only appears in networks with many species. Taken together, our results confirm that, in random reversible networks, ACR and multistationarity together, or even ACR on its own, is highly atypical. Our proofs rely on two prior results, one pertaining to the prevalence of networks with deficiency zero and the other ``lifting"" multistationarity from small networks to larger ones. © 2023 Society for Industrial and Applied Mathematics.
U2 - 10.1137/23M1549316
DO - 10.1137/23M1549316
M3 - Journal article
VL - 83
SP - 2260
EP - 2283
JO - SIAM Journal on Applied Mathematics
JF - SIAM Journal on Applied Mathematics
SN - 0036-1399
IS - 6
ER -
ID: 380361201