Simulating Filament Dynamics in Cellular Systems

Channels, Wilbur E.; Iglesias, Pablo A.

doi:10.1002/9780470556757.ch6

Cited by 1 publication

(1 citation statement)

References 35 publications

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“…Implicit integration methods address the coupling between segments by treating all segments simultaneously in a multidimensional linear equation [128]. Solving this equation by matrix inversion is very computationally expensive, so it is typically solved with the biconjugate gradient stabilized method instead [130,131]. It is possible to include all of the same forces and interactions when using implicit integration methods as explicit ones, but the biconjugate gradient solution methods are much faster when the linear equation matrix is sparse.…”

Section: Computational Filament Dynamicsmentioning

confidence: 99%

Methods for modeling cytoskeletal and DNA filaments

Andrews

2014

Phys. Biol.

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This review summarizes the models that researchers use to represent the conformations and dynamics of cytoskeletal and DNA filaments. It focuses on models that address individual filaments in continuous space. Conformation models include the freely jointed, Gaussian, angle-biased chain (ABC), and wormlike chain (WLC) models, of which the first three bend at discrete joints and the last bends continuously. Predictions from the WLC model generally agree well with experiment. Dynamics models include the Rouse, Zimm, stiff rod, dynamic WLC, and reptation models, of which the first four apply to isolated filaments and the last to entangled filaments. Experiments show that the dynamic WLC and reptation models are most accurate. They also show that biological filaments typically experience strong hydrodynamic coupling and/or constrained motion. Computer simulation methods that address filament dynamics typically compute filament segment velocities from local forces using the Langevin equation and then integrate these velocities with explicit or implicit methods; the former are more versatile and the latter are more efficient. Much remains to be discovered in biological filament modeling. In particular, filament dynamics in living cells are not well understood, and current computational methods are too slow and not sufficiently versatile. Although primarily a review, this paper also presents new statistical calculations for the ABC and WLC models. Additionally, it corrects several discrepancies in the literature about bending and torsional persistence length definitions, and their relations to flexural and torsional rigidities.

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Section: Computational Filament Dynamicsmentioning

confidence: 99%

Methods for modeling cytoskeletal and DNA filaments

Andrews

2014

Phys. Biol.

View full text Add to dashboard Cite

show abstract

Simulating Filament Dynamics in Cellular Systems

Cited by 1 publication

References 35 publications

Methods for modeling cytoskeletal and DNA filaments

Methods for modeling cytoskeletal and DNA filaments

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