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Novel method developed to extract molecular states and their network from noisy single molecule time series data

Research Press Release | March 23, 2015

Figure. A SM time-series measurement is shown in the upper left along with a depiction of the AMPA receptor. Illustrations of finite sampling and measurement errors are shown to the bottom left. Quantification of these errors allows the measurements to be classified into microscopic states, which subsequently allows for the calculation of state probabilities (bottom center), free energy profiles (bottom right), and state-to-state connectivity (top left), leading to a detailed depiction of the processes and forces driving the system under observation.
Figure. A SM time-series measurement is shown in the upper left along with a depiction of the AMPA receptor. Illustrations of finite sampling and measurement errors are shown to the bottom left. Quantification of these errors allows the measurements to be classified into microscopic states, which subsequently allows for the calculation of state probabilities (bottom center), free energy profiles (bottom right), and state-to-state connectivity (top left), leading to a detailed depiction of the processes and forces driving the system under observation.


Press Release
Overview

Methods from statistics and information theory were used to quantify errors in the time-series measurements and extract valuable and detailed information about biological systems. It was applied to experimental single-molecule (SM) time-series acquired for a neurological protein known as the AMPA receptor, which mediates the transmission of calcium ions through the central nervous system. AMPA is the most abundant protein in our nervous system and has been implicated in disorders such as depression and epilepsy. Uncovering vital information about the AMPA receptor has deepened understanding of how the protein moves in response to various biological stimuli, which is also expected to be applicable for medical applications.


Read on here:

Successfully developed a novel method to extract molecular states and their network from noisy single molecule time series data: Laboratory of Molecule & Life Nonlinear Sciences
Inquiries

Tamiki Komatsuzaki, Professor, Laboratory of Molecule & Life Nonlinear Sciences, Research Institute for Electronic Science, Hokkaido University

TEL & FAX: +81-11-706-9434

E-mail: ries-sec@es.hokudai.ac.jp

Japanese

Link

  ノイズを含むデータから分子の状態とそれらのネットワークを 抽出する新しい手法の開発にはじめて成功 
Publications Error-based Extraction of States and Energy Landscapes from Experimental Single-Molecule Time-Series,  Scientific Reports (3.17.2015)

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