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Non-Markovian properties and multiscale hidden Markovian network buried in single molecule time series
| Title: | Non-Markovian properties and multiscale hidden Markovian network buried in single molecule time series |
| Authors: | Sultana, Tahmina Browse this author | | Takagi, Hiroaki Browse this author →KAKEN DB | | Morimatsu, Miki Browse this author | | Teramoto, Hiroshi Browse this author →KAKEN DB | | Li, Chun-Biu Browse this author | | Sako, Yasushi Browse this author →KAKEN DB | | Komatsuzaki, Tamiki Browse this author →KAKEN DB |
| Issue Date: | 28-Dec-2013 |
| Publisher: | American Institute of Physics |
| Journal Title: | Journal of chemical physics |
| Volume: | 139 |
| Issue: | 24 |
| Start Page: | 245101-1 |
| End Page: | 245101-12 |
| Publisher DOI: | 10.1063/1.4848719 |
| PMID: | 24387402 |
| Abstract: | We present a novel scheme to extract a multiscale state space network (SSN) from single-molecule time series. The multiscale SSN is a type of hidden Markov model that takes into account both multiple states buried in the measurement and memory effects in the process of the observable whenever they exist. Most biological systems function in a nonstationary manner across multiple timescales. Combined with a recently established nonlinear time series analysis based on information theory, a simple scheme is proposed to deal with the properties of multiscale and nonstationarity for a discrete time series. We derived an explicit analytical expression of the autocorrelation function in terms of the SSN. To demonstrate the potential of our scheme, we investigated single-molecule time series of dissociation and association kinetics between epidermal growth factor receptor (EGFR) on the plasma membrane and its adaptor protein Ash/Grb2 (Grb2) in an in vitro reconstituted system. We found that our formula successfully reproduces their autocorrelation function for a wide range of timescales (up to 3 s), and the underlying SSNs change their topographical structure as a function of the timescale; while the corresponding SSN is simple at the short timescale (0.033-0.1 s), the SSN at the longer timescales (0.1 s to similar to 3 s) becomes rather complex in order to capture multiscale nonstationary kinetics emerging at longer timescales. It is also found that visiting the unbound form of the EGFR-Grb2 system approximately resets all information of history or memory of the process. |
| Rights: | Copyright 2013 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in J. Chem. Phys. 139, 245101 (2013) and may be found at http://dx.doi.org/10.1063/1.4848719. |
| Type: | article |
| URI: | http://hdl.handle.net/2115/54764 |
| Appears in Collections: | 電子科学研究所 (Research Institute for Electronic Science) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 小松崎 民樹
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