001     1005516
005     20230403201807.0
037 _ _ |a FZJ-2023-01516
041 _ _ |a English
100 1 _ |a Tan, Zihan
|0 P:(DE-Juel1)165875
|b 0
|e Corresponding author
|u fzj
111 2 _ |a Vortrag im Seminar Statistische Physik weicher Materie und biologischer Systeme
|c Berlin
|d 2023-03-17 - 2023-03-17
|w Germany
245 _ _ |a Quasi-two-dimensional protein dispersions:From monolayers with competing interactions to a protein-membrane-cytosol model of neuronal signal transduction
|f 2023-03-17 -
260 _ _ |c 2023
336 7 _ |a Conference Paper
|0 33
|2 EndNote
336 7 _ |a Other
|2 DataCite
336 7 _ |a INPROCEEDINGS
|2 BibTeX
336 7 _ |a LECTURE_SPEECH
|2 ORCID
336 7 _ |a Talk (non-conference)
|b talk
|m talk
|0 PUB:(DE-HGF)31
|s 1680526627_32182
|2 PUB:(DE-HGF)
|x Invited
336 7 _ |a Other
|2 DINI
502 _ _ |c TU Berlin
520 _ _ |a I first discuss the phase behavior, hexagonal clustering, and resultant intermediate-range structure order (IRO) of quasi-two-dimensional (Q2D) protein dispersions with competing short-range attractive (SA) and long-range repulsive (LR) interactions. Later on, in such Q2D-SALR systems, using Langevin dynamics and multiparticle collision dynamics (MPC), I address the questions regarding self- and collective diffusion, non-Gaussian dynamics, and (time-dependent) hydrodynamic interactions (HIs). At last, I present our modeling work on the lateral diffusion of membrane receptor proteins. From a top-down approach, we build a mesoscopic protein-membrane-cytosol model by extending MPC algorithm to layered binary fluids with viscosity contrast. In addition, lipid crowding effects are included to capture the viscoelasticity nature of biological membranes. This model is applied to study the diffusion of a G-protein coupled receptor protein with a dumbbell shape.
536 _ _ |a 5241 - Molecular Information Processing in Cellular Systems (POF4-524)
|0 G:(DE-HGF)POF4-5241
|c POF4-524
|f POF IV
|x 0
909 C O |o oai:juser.fz-juelich.de:1005516
|p VDB
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)165875
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-524
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Molecular and Cellular Information Processing
|9 G:(DE-HGF)POF4-5241
|x 0
914 1 _ |y 2023
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)IAS-5-20120330
|k IAS-5
|l Computational Biomedicine
|x 0
920 1 _ |0 I:(DE-Juel1)INM-9-20140121
|k INM-9
|l Computational Biomedicine
|x 1
980 _ _ |a talk
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)IAS-5-20120330
980 _ _ |a I:(DE-Juel1)INM-9-20140121
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21