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001005516 005__ 20230403201807.0
001005516 037__ $$aFZJ-2023-01516
001005516 041__ $$aEnglish
001005516 1001_ $$0P:(DE-Juel1)165875$$aTan, Zihan$$b0$$eCorresponding author$$ufzj
001005516 1112_ $$aVortrag im Seminar Statistische Physik weicher Materie und biologischer Systeme$$cBerlin$$d2023-03-17 - 2023-03-17$$wGermany
001005516 245__ $$aQuasi-two-dimensional protein dispersions:From monolayers with competing interactions to a protein-membrane-cytosol model of neuronal signal transduction$$f2023-03-17 - 
001005516 260__ $$c2023
001005516 3367_ $$033$$2EndNote$$aConference Paper
001005516 3367_ $$2DataCite$$aOther
001005516 3367_ $$2BibTeX$$aINPROCEEDINGS
001005516 3367_ $$2ORCID$$aLECTURE_SPEECH
001005516 3367_ $$0PUB:(DE-HGF)31$$2PUB:(DE-HGF)$$aTalk (non-conference)$$btalk$$mtalk$$s1680526627_32182$$xInvited
001005516 3367_ $$2DINI$$aOther
001005516 502__ $$cTU Berlin
001005516 520__ $$aI 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.
001005516 536__ $$0G:(DE-HGF)POF4-5241$$a5241 - Molecular Information Processing in Cellular Systems (POF4-524)$$cPOF4-524$$fPOF IV$$x0
001005516 909CO $$ooai:juser.fz-juelich.de:1005516$$pVDB
001005516 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)165875$$aForschungszentrum Jülich$$b0$$kFZJ
001005516 9131_ $$0G:(DE-HGF)POF4-524$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5241$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vMolecular and Cellular Information Processing$$x0
001005516 9141_ $$y2023
001005516 920__ $$lyes
001005516 9201_ $$0I:(DE-Juel1)IAS-5-20120330$$kIAS-5$$lComputational Biomedicine$$x0
001005516 9201_ $$0I:(DE-Juel1)INM-9-20140121$$kINM-9$$lComputational Biomedicine$$x1
001005516 980__ $$atalk
001005516 980__ $$aVDB
001005516 980__ $$aI:(DE-Juel1)IAS-5-20120330
001005516 980__ $$aI:(DE-Juel1)INM-9-20140121
001005516 980__ $$aUNRESTRICTED