Brownian Motion of Lattice‐Model Polymer Chains

1969 ◽  
Vol 50 (9) ◽  
pp. 4008-4013 ◽  
Author(s):  
Kazuyoshi Iwata ◽  
Michio Kurata
1994 ◽  
Vol 26 (9) ◽  
pp. 1063-1069
Author(s):  
Linxi Zhang ◽  
Jianmin Xu ◽  
Longshao Zhao

2008 ◽  
Vol 128 (6) ◽  
pp. 064903 ◽  
Author(s):  
Jutta Luettmer-Strathmann ◽  
Federica Rampf ◽  
Wolfgang Paul ◽  
Kurt Binder

1990 ◽  
Vol 23 (15) ◽  
pp. 3584-3592 ◽  
Author(s):  
Arvind Hariharan ◽  
Sanat K. Kumar ◽  
Thomas P. Russell

1996 ◽  
Vol 10 (29) ◽  
pp. 1441-1446 ◽  
Author(s):  
M. LÓPEZ DE HARO ◽  
L. L. GONÇALVES ◽  
J. TAGÜEÑA-MARTÍNEZ

The relaxational heat capacity of an infinite linear polymer chain is computed. The result is derived within a kinetic Ising-like model previously introduced to provide for a dynamical generalization of the Gibbs-di Marzio lattice model. The questions of universality of the dynamic responses of the chain and of the existence of more than one relaxation time if one considers different probes are discussed.


2019 ◽  
Vol 20 (2) ◽  
pp. 295
Author(s):  
Luiz Otávio Rodrigues Alves Sereno ◽  
José Luiz Acebal

Among many structures in the cells of living beings, there are proteins called transcription factors (TF) that are responsible to inhibit or promote the transcription of the DNA. To accomplish their function, the transcription factors perform aleatory searches around the cytoplasm (for prokaryotic cells) and along the DNA chain as well for specific targets located in the DNA. Its movement fits into the class of anomalous Brownian. The efficiency in TFs search has implications in the cellular copy and in protection against viruses, hence the knowledge of the mechanism is of great interest. In the present work, we study the searching process of the TFs by simulating the anomalous Brownian motion through the cytoplasm and DNA chain by means of Levy flights through a lattice model and through a  free grid model. The final distribution of positions of the TF are obtained. The search efficiency is investigated in terms of the model parameters.


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