NDLI: Modeling and role of feedback controlled stochastic ratchets in cellular transport

Content Provider	IEEE Xplore Digital Library
Author	Salapaka, S. Rowchowdhury, S. Salapaka, M.
Copyright Year	2012
Description	Author affiliation: Electrical and Computer Engineering Department at University of Minnesota, Twin Cities, USA (Rowchowdhury, S.; Salapaka, M.) \|\| Faculty of Mechanical Engineering, University of Illinois at Urbana Champaign, USA (Salapaka, S.)
Abstract	This paper develops a model for Brownian ratchets to analyze the cases where the transport characteristics are affected by feedback mechanisms. One main application of this approach is to gain insights on the intracellular transport of motor proteins (such as Kinesin and Dynein) on a microtubular track, and on the role of feedback control on their transport. The model comprises of a stochastic system where the system switches between two stochastic differential systems, where the switching criteria is a state-dependent stochastic variable. Simulations demonstrate that the feedback mechanism helps achieve an increased average velocity of transport and corroborates the hypothesis that a motor protein can achieve higher speeds of transport by restricting or enabling attachment/detachment of ATP/ADP like molecules depending on conformational changes in the motor-protein.
Starting Page	374
Ending Page	379
File Size	1005084
Page Count	6
File Format	PDF
ISBN	9781467320658
ISSN	07431546
e-ISBN	9781467320665
e-ISBN	9781467320641
DOI	10.1109/CDC.2012.6426263
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Switches Stochastic processes Force Mathematical model Proteins Biological system modeling Steady-state switched/hybrid systems Brownian ratchets kinesin walk cellular transport Kolmogorov-Chapman differential equations stochastic differential equations
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Modeling and Simulation

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