Summary

Proceedings of the 2013 International Symposium on Nonlinear Theory and its Applications

2013

Session Number:C3L-B

Session:

Number:445

When Computational Mechanics Meets Single Molecule Time Series

Chun-Biu Li,  Tamiki Komatsuzaki,  

pp.445-447

Publication Date:

Online ISSN:2188-5079

DOI:10.15248/proc.2.445

PDF download (256.9KB)

Developed in the context of information theory, computational mechanics (CM) has been formulated to construct the minimal but the most predictive hidden Markov model, originally termed ε-machine, which is able to reproduce the causal structures statistically from time series. Here I will present several generalizations of CM to the study of complex dynamics and kinetics of single molecule (SM) time series. These include the incorporation of wavelet decomposition into CM to construct the multi-scale state-space networks for non-stationary SM time series, and the introduction of soft (or lossy) clustering in defining states when noise and measurement error present in the data.

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