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Maximum Entropy (MaxEnt) parameter inference in biological networks.

MATLAB 53.66% Python 20.78% M 25.56%
biological-network birth-death-process cell-heterogeneity cell-signalling heterogeneity-analysis markov-process matlab maximum-entropy python signaling-networks ecoli

maxent-parameter-inference's Introduction

Maximum Entropy Parameter Inference in Biological Networks

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Overview

  • Overarching Goal: Appoximate biological process networks - such as molecular signaling and protein inetractions - as Markov birth-death processes and infer their parameters using MaxEnt to quantitatively characterize and predict cell` population response heterogeneity.

  • Analysis of Bistability in the Lactose Utilization Network of E.coli as a model network.

  • Infer molecular abundance time-evolution trajectories using MaxEnt in the E.coli lactose utilization network.

Primary References

  • Dixit, Purushottam D., et al. "Maximum entropy framework for predictive inference of cell population heterogeneity and responses in signaling networks." Cell systems 10.2 (2020): 204-212.
  • Kim, Dae Wook, et al. "Systematic inference identifies a major source of heterogeneity in cell signaling dynamics: The rate-limiting step number." Science advances 8.11 (2022): eabl4598.

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