scholarly journals System Identification Using Compressed Sensing Reveals Signaling-Decoding System by Gene Expression

2017 ◽  
Author(s):  
Takaho Tsuchiya ◽  
Masashi Fujii ◽  
Naoki Matsuda ◽  
Katsuyuki Kunida ◽  
Shinsuke Uda ◽  
...  

SUMMARYCells decode information of signaling activation at a scale of tens of minutes by downstream gene expression with a scale of hours to days, leading to cell fate decisions such as cell differentiation. However, no system identification method with such different time scales exists. Here we used compressed sensing technology and developed a system identification method using data of different time scales by recovering signals of missing time points. We measured phosphorylation of ERK and CREB, immediate early gene expression products, and mRNAs of decoder genes for neurite elongation in PC12 cell differentiation and performed system identification, revealing the input–output relationships between signaling and gene expression with sensitivity such as graded or switch-like response and with time delay and gain, representing signal transfer efficiency. We predicted and validated the identified system using pharmacological perturbation. Thus, we provide a versatile method for system identification using data with different time scales.HighlightsWe developed a system identification method using compressed sensing.This method allowed us to find a pathway using data of different time scales.We identified a selective signaling-decoding system by gene expression.We validated the identified system by pharmacological perturbation.eTOC BlurbWe describe a system identification method of molecular networks with different time-scale data using a signal recovery technique in compressed sensing.

2006 ◽  
Vol 326-328 ◽  
pp. 1439-1442
Author(s):  
Irfan Ariyanto ◽  
Tae Sam Kang ◽  
Young Jae Lee

The efficiency of fish swimming dynamics has motivated researchers to develop fish-like robots. As a beginning step, a fish-like robot (boat) is built to simulate the fish swimming dynamics. By using data collected from inertial sensors, a suitable mathematical model explaining fish turning dynamics is obtained through system identification method. The identified model matches well with the experimental results and thus can be used for the design of controllers.


2000 ◽  
Vol 120 (4) ◽  
pp. 566-573
Author(s):  
Osamu Yamanaka ◽  
Akihiro Nagaiwa ◽  
Shinichiro Matsubara ◽  
Masajiro Nakada ◽  
Fumio Yamada

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