Master.bib

@article{Berry2002,
abstract = {Conventional equations for enzyme kinetics are based on mass-action laws, that may fail in low-dimensional and disordered media such as biological membranes. We present Monte Carlo simulations of an isolated Michaelis-Menten enzyme reaction on two-dimensional lattices with varying obstacle densities, as models of biological membranes. The model predicts that, as a result of anomalous diffusion on these low-dimensional media, the kinetics are of the fractal type. Consequently, the conventional equations for enzyme kinetics fail to describe the reaction. In particular, we show that the quasi-stationary-state assumption can hardly be retained in these conditions. Moreover, the fractal characteristics of the kinetics are increasingly pronounced as obstacle density and initial substrate concentration increase. The simulations indicate that these two influences are mainly additive. Finally, the simulations show pronounced S-P segregation over the lattice at obstacle densities compatible with in vivo conditions. This phenomenon could be a source of spatial self organization in biological membranes.},
author = {Berry, Hugues},
doi = {10.1016/S0006-3495(02)73953-2},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Berry - 2002 - Monte carlo simulations of enzyme reactions in two dimensions fractal kinetics and spatial segregation.pdf:pdf},
isbn = {0006-3495},
issn = {00063495},
journal = {Biophysical journal},
number = {4},
pages = {1891--1901},
pmid = {12324410},
publisher = {Elsevier},
title = {{Monte carlo simulations of enzyme reactions in two dimensions: fractal kinetics and spatial segregation.}},
url = {http://dx.doi.org/10.1016/S0006-3495(02)73953-2},
volume = {83},
year = {2002}
}
@article{Craigmile2003,
abstract = {We demonstrate that the fast and exact Davies–Harte algorithm is valid for simulating a certain class of stationary Gaussian processes – those with a negative autocovariance sequence for all non-zero lags. The result applies to well known classes of long memory processes: Gaussian fractionally differenced (FD) processes, fractional Gaussian noise (fGn) and the nonstationary fractional Brownian Motion (fBm).},
author = {Craigmile, Peter F.},
doi = {10.1111/1467-9892.00318},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Craigmile - 2003 - Simulating a class of stationary Gaussian processes using the Davies-Harte algorithm, with application to long memory.pdf:pdf},
issn = {01439782},
journal = {Journal of Time Series Analysis},
keywords = {Circulant embedding,Davies-Harte algorithm,Long memory process,Negative autocovariance sequence,Simulation,Time series analysis},
number = {5},
pages = {505--511},
title = {{Simulating a class of stationary Gaussian processes using the Davies-Harte algorithm, with application to long memory processes}},
volume = {24},
year = {2003}
}
@article{Echeverria2015,
author = {Echeverria, Carlos and Kapral, Raymond},
doi = {10.1039/C5CP05056A},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Echeverria, Kapral - 2015 - Enzyme kinetics and transport in a system crowded by mobile macromolecules.pdf:pdf},
issn = {1463-9076},
journal = {Phys. Chem. Chem. Phys.},
number = {43},
pages = {29243--29250},
publisher = {Royal Society of Chemistry},
title = {{Enzyme kinetics and transport in a system crowded by mobile macromolecules}},
url = {http://xlink.rsc.org/?DOI=C5CP05056A},
volume = {17},
year = {2015}
}
@article{Havlin1987,
author = {Havlin, S and Avraham, D Ben},
file = {:home/mi/janekg89/Downloads/1-s2.0-016974399180040W-main.pdf:pdf},
journal = {Advances in Physics},
pages = {695--798},
title = {{Diffusion in Disordered Media}},
volume = {36},
year = {1987}
}
@article{Hofling2013,
author = {H{\"{o}}fling, Felix and Franosch, Thomas},
doi = {10.1088/0034-4885/76/4/046602},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/H{\"{o}}fling, Franosch - 2013 - Anomalous transport in the crowded world of biological cells.pdf:pdf},
issn = {0034-4885},
journal = {Reports on Progress in Physics},
month = {apr},
number = {4},
pages = {046602},
title = {{Anomalous transport in the crowded world of biological cells}},
url = {http://stacks.iop.org/0034-4885/76/i=4/a=046602?key=crossref.d72b9b76244e9222284e073065248855},
volume = {76},
year = {2013}
}
@phdthesis{Johannesschoneberg2014,
abstract = {We can see the faintest stars because rod cells in our eyes can detect single photons reliably and convert them reproducibly into an output current. Visual rhodopsin molecules respond to photon absorption by a change of their shape that sends a signal to other proteins. But how does this signal transduction cascade proceed in detail? How are the individual copies of all involved proteins orchestrated in space and time to give rise to cellular output? Experiments cannot simultaneously probe localizations and time sequences of all relevant molecular processes. A solution is to inte- grate experimental data in physically realistic computer models and simulating the spatiotemporal mechanism of signal transduction. The most detailed reaction kinetics simulation techniques are particle- based reaction-diffusion (PBRD) simulations. Here all molecules are represented as individual particles. Their diffusive motion and the reactions between them are simulated explicitly in space and time. However, existing PBRD techniques lack interaction potentials between particles that are needed to realistically model molecular aggregates, clusters or fibers/chains. Here a new class of reaction kinetics models is introduced that combines PBRD with interaction potentials. ReaDDy, a generic and platform-independent software package, has been developed to imple- ment this new class. ReaDDy has a modular and extensible software design, enabling straightforward implementations for different hard- ware (e.g. single-CPU, multithreading, GPU), and the incorporation of different models of particle dynamics (e.g. Langevin, overdamped Langevin, Metropolis Monte Carlo). Arbitrary particle interaction potentials (e.g. space exclusion, electrostatic interaction), and var- ious cellular geometries (e.g. disc membranes or vesicles) can be user-defined. ReaDDy was used to shed light on the spatiotemporal details of photoactivation in rod cell disc membranes. While the supramolecular architecture of rhodopsin (R) is controversial, it was shown here that various R-architectures are consistent with kinetic activation experi- ments performed by our experimental collaborators at Charit{\'{e}} (Berlin). Important mechanistic insights were produced, including: (1) The rate- limiting molecular steps in G-protein activation were identified. (2) Unproductive complexes between inactive R and G may exist, but their lifetime is limited to the 100 microseconds timescale. (3) Supramolecular structures of R (as opposed to uniformly distributed individual Rs) do not increase the speed of the activation kinetics. Such structures are likely to play an other regulatory role in the cascade. Simultaneously, experimentalists at Caesar (Bonn) have found new evidence of a specific and regular supramolecular structure, in which rhodopsin forms ’tracks’, i.e. double rows of dimers of approximately uniform length. A ReaDDy model confirms that this architecture is consistent with kinetic measurements, but also reveals a new regula- tion mechanism: The spatially separate and uniform track structures of R, combined with short-lived inactive R-G-precomplexes of R and G, lead to a time-scale separation of fast intra-track diffusion and activation and slow inter-track diffusion. As a result, the G-activation kinetics is biphasic, with a quick activation burst of {\~{}}4 G-proteins associated to one track. The subsequent slow activation phase is insensitive to the exact shutoff time of rhodopsin, thus ensuring a reliable output. While this insight from simulations must be confirmed experimentally, it may be an important component of single-photon response uniformity. The concepts and software developed in this thesis are not limited to rod cell phototransduction, but represent a general contribution towards a new generation of quantitative biology using physically real- istic models. In the future, together with super-resolution microscopy and single-molecule experiments, they could provide the foundation to reach for the stars in ’cellular dynamics’: Being able to simulate an entire cell.},
author = {Johannes sch{\"{o}}neberg},
file = {:home/mi/janekg89/Downloads/Schoeneberg{\_}dissertation{\_}compressed (2).pdf:pdf},
isbn = {9788578110796},
issn = {19454589},
pages = {162},
title = {{REACTION-DIFFUSION DYNAMICS IN BIOLOGICAL SYSTEMS}},
year = {2014}
}
@article{Kuttler2011,
author = {Kuttler, Christina},
file = {:home/mi/janekg89/.cache/evolution/tmp/evolution-janekg89-en4skp/script{\_}reaktdiff.pdf:pdf},
journal = {Www-M6.Ma.Tum.De},
pages = {105},
title = {{Reaction-Diffusion equations with applications}},
url = {http://www-m6.ma.tum.de/{~}kuttler/script{\_}reaktdiff.pdf},
year = {2011}
}
@article{Li2013,
abstract = {Brownian motion has played important roles in many different fields of science since its origin was first explained by Albert Einstein in 1905. Einstein's theory of Brownian motion, however, is only applicable at long time scales. At short time scales, Brownian motion of a suspended particle is not completely random, due to the inertia of the particle and the surrounding fluid. Moreover, the thermal force exerted on a particle suspended in a liquid is not a white noise, but is colored. Recent experimental developments in optical trapping and detection have made this new regime of Brownian motion accessible. This review summarizes related theories and recent experiments on Brownian motion at short time scales, with a focus on the measurement of the instantaneous velocity of a Brownian particle in a gas and the observation of the transition from ballistic to diffusive Brownian motion in a liquid.},
archivePrefix = {arXiv},
arxivId = {1211.1458},
author = {Li, Tongcang and Raizen, Mark G.},
doi = {10.1002/andp.201200232},
eprint = {1211.1458},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Li, Raizen - 2013 - Brownian motion at short time scales.pdf:pdf},
isbn = {00033804},
issn = {00033804},
journal = {Annalen der Physik},
keywords = {Brownian motion,Einstein,Langevin equation,instantaneous velocity,optical tweezers},
number = {4},
pages = {281--295},
title = {{Brownian motion at short time scales}},
volume = {525},
year = {2013}
}
@article{Lutz2001,
abstract = {We investigate fractional Brownian motion with a microscopic random-matrix model and introduce a fractional Langevin equation. We use the latter to study both subdiffusion and superdiffusion of a free particle coupled to a fractal heat bath. We further compare fractional Brownian motion with the fractal time process. The respective mean-square displacements of these two forms of anomalous diffusion exhibit the same power-law behavior. Here we show that their lowest moments are actually all identical, except the second moment of the velocity. This provides a simple criterion that enable us to distinguish these two non-Markovian processes.},
annote = {maybe nice fractional differential equation},
archivePrefix = {arXiv},
arxivId = {cond-mat/0103128},
author = {Lutz, Eric},
doi = {10.1103/PhysRevE.64.051106},
eprint = {0103128},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Lutz - 2001 - Fractional Langevin equation.pdf:pdf},
issn = {1063-651X},
journal = {Physical Review E},
number = {5},
pages = {051106},
pmid = {11735899},
primaryClass = {cond-mat},
title = {{Fractional Langevin equation}},
url = {http://link.aps.org/doi/10.1103/PhysRevE.64.051106},
volume = {64},
year = {2001}
}
@article{Minton2006,
abstract = {Nonspecific interactions between individual macro-molecules and their immediate surroundings ("background interactions") within a medium as heterogeneous and highly volume occupied as the interior of a living cell can greatly influence the equilibria and rates of reactions in which they participate. Background interactions may be either repulsive, leading to preferential size-and-shape-dependent exclusion from highly volume-occupied elements of volume, or attractive, leading to nonspecific associations or adsorption. Nonspecific interactions with different constituents of the cellular interior lead to three classes of phenomena: macromolecular crowding, confinement and adsorption. Theory and experiment have established that predominantly repulsive background interactions tend to enhance the rate and extent of macromolecular associations in solution, whereas predominantly attractive background interactions tend to enhance the tendency of macromolecules to associate on adsorbing surfaces. Greater than order-of-magnitude increases in association rate and equilibrium constants attributable to background interactions have been observed in simulated and actual intracellular environments.},
author = {Minton, Allen P},
doi = {10.1242/jcs.03063},
file = {:home/mi/janekg89/Dokumente/literatur/2863.full.pdf:pdf},
isbn = {0021-9533 (Print)$\backslash$r0021-9533 (Linking)},
issn = {0021-9533},
journal = {Journal of cell science},
keywords = {Animals,Cell-Free System,Cells,Cells: cytology,Cells: metabolism,Macromolecular Substances,Macromolecular Substances: metabolism,Thermodynamics,milton2006},
mendeley-tags = {milton2006},
number = {Pt 14},
pages = {2863--9},
pmid = {16825427},
title = {{How can biochemical reactions within cells differ from those in test tubes?}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/16825427},
volume = {119},
year = {2006}
}
@article{Mura2008,
abstract = {In this paper we introduce and analyze a class of diffusion type equations related to certain non-Markovian stochastic processes. We start from the forward drift equation which is made non-local in time by the introduction of a suitable chosen memory kernel K (t). The resulting non-Markovian equation can be interpreted in a natural way as the evolution equation of the marginal density function of a random time process l (t). We then consider the subordinated process Y (t) = X (l (t)) where X (t) is a Markovian diffusion. The corresponding time evolution of the marginal density function of Y (t) is governed by a non-Markovian Fokker-Planck equation which involves the memory kernel K (t). We develop several applications and derive the exact solutions. We consider different stochastic models for the given equations providing path simulations. ?? 2008 Elsevier B.V. All rights reserved.},
archivePrefix = {arXiv},
arxivId = {0712.0240},
author = {Mura, A. and Taqqu, M. S. and Mainardi, F.},
doi = {10.1016/j.physa.2008.04.035},
eprint = {0712.0240},
file = {:home/mi/janekg89/Downloads/0712.0240v2.pdf:pdf},
isbn = {978-3844392296},
issn = {03784371},
journal = {Physica A: Statistical Mechanics and its Applications},
keywords = {Anomalous diffusion,Fractional Brownian motion,Fractional derivatives,Non-Markovian processes,Subordination},
number = {21},
pages = {5033--5064},
title = {{Non-Markovian diffusion equations and processes: Analysis and simulations}},
volume = {387},
year = {2008}
}
@article{Qian2010,
abstract = {We develop the stochastic, chemical master equation as a unifying approach to the dynamics of biochemical reaction systems in a mesoscopic volume under a living environment. A living environment provides a continuous chemical energy input that sustains the reaction system in a nonequilibrium steady state with concentration fluctuations. We discuss the linear, unimolecular single-molecule enzyme kinetics, phosphorylation-dephosphorylation cycle (PdPC) with bistability, and network exhibiting oscillations. Emphasis is paid to the comparison between the stochastic dynamics and the prediction based on the traditional approach based on the Law of Mass Action. We introduce the difference between nonlinear bistability and stochastic bistability, the latter has no deterministic counterpart. For systems with nonlinear bistability, there are three different time scales: (a) individual biochemical reactions, (b) nonlinear network dynamics approaching to attractors, and (c) cellular evolution. For mesoscopic systems with size of a living cell, dynamics in (a) and (c) are stochastic while that with (b) is dominantly deterministic. Both (b) and (c) are emergent properties of a dynamic biochemical network; We suggest that the (c) is most relevant to major cellular biochemical processes such as epi-genetic regulation, apoptosis, and cancer immunoediting. The cellular evolution proceeds with transitions among the attractors of (b) in a "punctuated equilibrium" manner.},
author = {Qian, Hong and Bishop, Lisa M.},
doi = {10.3390/ijms11093472},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Qian, Bishop - 2010 - The chemical master equation approach to nonequilibrium Steady-state of open biochemical systems Linear Single-mol.pdf:pdf},
isbn = {10.3390/ijms11093472},
issn = {14220067},
journal = {International Journal of Molecular Sciences},
keywords = {Biochemical reaction,Chemical kinetics,Chemical master equation,Stochastic dynamics,Systems biology},
number = {9},
pages = {3472--3500},
pmid = {20957107},
title = {{The chemical master equation approach to nonequilibrium Steady-state of open biochemical systems: Linear Single-molecule enzyme kinetics and nonlinear biochemical reaction networks}},
volume = {11},
year = {2010}
}
@article{Schnell2004,
abstract = {We review recent evidence illustrating the fundamental difference between cytoplasmic and test tube biochemical kinetics and thermodynamics, and showing the breakdown of the law of mass action and power-law approximation in in vivo conditions. Simulations of biochemical reactions in non-homogeneous media show that as a result of anomalous diffusion and mixing of the biochemical species, reactions follow a fractal-like kinetics. Consequently, the conventional equations for biochemical pathways fail to describe the reactions in in vivo conditions. We present a modification to fractal-like kinetics following the Zipf-Mandelbrot distribution which will enable the modelling and analysis of biochemical reactions occurring in crowded intracellular environments. ?? 2004 Elsevier Ltd. All rights reserved.},
author = {Schnell, S. and Turner, T. E.},
doi = {10.1016/j.pbiomolbio.2004.01.012},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Schnell, Turner - 2004 - Reaction kinetics in intracellular environments with macromolecular crowding Simulations and rate laws.pdf:pdf},
isbn = {4418652868},
issn = {00796107},
journal = {Progress in Biophysics and Molecular Biology},
keywords = {Enzymatic reactions,Fractal-like kinetics,Intracellular environment,Macromolecular crowding,Reaction rate},
number = {2-3},
pages = {235--260},
pmid = {15142746},
title = {{Reaction kinetics in intracellular environments with macromolecular crowding: Simulations and rate laws}},
volume = {85},
year = {2004}
}
@article{Search,
author = {Search, Home and Journals, Collections and Contact, About and Iopscience, My and Address, I P},
doi = {10.1209/0295-5075/94/18002},
file = {:home/mi/janekg89/Downloads/epl{\_}94{\_}1{\_}18002.pdf:pdf},
title = {{Anomalous reaction kinetics and domain formation on crowded membranes}},
volume = {18002}
}
@article{Turner2004,
abstract = {In recent years, stochastic modelling has emerged as a physically more realistic alternative for modelling in vivo reactions. There are numerous stochastic approaches available in the literature; most of these assume that observed random fluctuations are a consequence of the small number of reacting molecules. We review some important developments of the stochastic approach and consider its suitability for modelling intracellular reactions. We then describe recent efforts to include the fluctuation effects caused by the structural organisation of the cytoplasm and the limited diffusion of molecules due to macromolecular crowding. ?? 2004 Elsevier Ltd. All rights reserved.},
author = {Turner, T. E. and Schnell, S. and Burrage, K.},
doi = {10.1016/j.compbiolchem.2004.05.001},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Turner, Schnell, Burrage - 2004 - Stochastic approaches for modelling in vivo reactions.pdf:pdf},
isbn = {1476-9271 (Print)$\backslash$r1476-9271 (Linking)},
issn = {14769271},
journal = {Computational Biology and Chemistry},
keywords = {??-leap method,Fractal-like kinetics,Intracellular reactions,Quasi-steady-state approximation,Stochastic simulation algorithm},
number = {3},
pages = {165--178},
pmid = {15261147},
title = {{Stochastic approaches for modelling in vivo reactions}},
volume = {28},
year = {2004}
}
@article{Mandelbrot1968,
author = {Mandelbrot, Benoit B. and {Van Ness}, John W.},
doi = {10.1137/1010093},
file = {:home/mi/janekg89/Dokumente/literatur/2027184.pdf:pdf},
issn = {0036-1445},
journal = {SIAM Review},
month = {oct},
number = {4},
pages = {422--437},
title = {{Fractional Brownian Motions, Fractional Noises and Applications}},
url = {http://epubs.siam.org/doi/abs/10.1137/1010093},
volume = {10},
year = {1968}
}