Why Biological Systems Suddenly Change State: An Intuitive Guide to Freidlin–Wentzell Theory

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  Stochasticity is ubiquitous in biology and neuroscience, manifesting in various forms, including ion channel noise, synaptic variability, gene regulatory fluctuations, noisy population dynamics, and more. Many biological systems spend long periods in a stable “state” and only rarely transition to another state due to noise. For instance, a neuron typically remains inactive but may occasionally trigger a spontaneous spike. Similarly, a gene can switch from the OFF state to the ON state due to rare bursts of transcription factors. Cells can also transition out of metabolic or epigenetic states, populations might shift between different ecological equilibria, and a viral infection can fluctuate between phases of control and uncontrollability. Freidlin–Wentzell theory provides a mathematically rigorous framework to study these phenomena when noise is small but nonzero . It tells you, firstly, h ow likely rare transitions are,    secondly,   h ow fast they occ...
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International Symposium on Computational Models for Life Sciences

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Call for Papers to the International Symposium on Computational Models for Life Sciences: CMLS 2013

Themes of Interest

  • Medical/biomedical and molecular image analysis and understanding
  • Computational systems biology and medicine
  • Computational psychology and physiology
  • Computational neuroscience
  • Bio-sensing
  • Bio-signals
  • e-Health

Topics include, but not limited to, the following:

Image analysis, computer vision, pattern analysis and classification, information visualization, signal processing, control theory, information theory, statistical analysis, information fusion, numerical analysis, fractals and chaos, biologically-inspired techniques, optimization, simulation and modeling, parallel computing, computational intelligence methods, machine learning, data mining, decision support systems, database integration and management.

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