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- W3102701430 abstract "Given that biochemical circuits can process information by using analog computation, a question is: What can biochemical circuits compute? This paper considers the problem of using biochemical circuits to distinguish persistent signals from transient ones. We define a statistical detection problem over a reaction pathway consisting of three species: an inducer, a transcription factor (TF) and a gene, where the inducer can activate the TF and an active TF can bind to the gene promoter. We model the pathway using the chemical master equation so the counts of bound promoters over time is a stochastic signal. We consider the problem of using the continuous-time stochastic signal of the counts of bound promoters to infer whether the inducer signal is persistent or not. We use statistical detection theory to derive the solution to this detection problem, which is to compute the log-likelihood ratio of observing a persistent signal to a transient one. We then show, under time-scale separation and other assumptions, that this log-likelihood can be approximately computed by using the continuous-time signals of the number of active TF molecules and the number of bound promoters when the input is persistent. Finally, we show that the coherent feedforward gene circuits can be used to approximately compute the mean of this log-likelihood ratio when the inducer signal is persistent." @default.
- W3102701430 created "2020-11-23" @default.
- W3102701430 creator A5086095673 @default.
- W3102701430 date "2019-07-23" @default.
- W3102701430 modified "2023-09-27" @default.
- W3102701430 title "The coherent feedforward gene circuit can be used to approximately compute log-likelihood ratio for detecting persistent signals" @default.
- W3102701430 hasPublicationYear "2019" @default.
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