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Extensive Monte Carlo simulations are presented for the bond-fluctuation model on three-dimensional simple cubic lattices. High statistics data are obtained for polymer volume fractions Φ in the range $0.025 \leqslant \Phi \leqslant 0.500$ and chain lengths N in the range $20 \leqslant N \leqslant 200$, making use of a parallel computer containing 80 transputers. The simulation technique takes into account both excluded volume interactions and entanglement restrictions, while otherwise the chains are non-interacting and athermal. The simulation data are analysed in terms of the de Gennes scaling concepts, describing the crossover from swollen coils in the dilute limit to gaussian coils in semidilute and concentrated solution. The crossover scaling functions for the chain linear dimensions and for the decay of the structure factor are estimated and compared to corresponding theoretical and experimental results in the literature. Also the dynamics of the chains is studied in detail, and evidence for a gradual crossover from the Rouse model to a D ∼N-2 law for the diffusion constant is presented. This crossover is consistent with scaling only if a concentration-dependent segmental “friction coefficient" is introduced. Within this framework general agreement between these data, other simulations and experiment is found

Genome function in higher eukaryotes involves major changes in the spatial organization of the chromatin fiber. Nevertheless, our understanding of chromatin folding is remarkably limited. Polymer models have been used to describe chromatin folding. However, none of the proposed models gives a satisfactory explanation of experimental data. In particularly, they ignore that each chromosome occupies a confined space, i.e., the chromosome territory. Here, we present a polymer model that is able to describe key properties of chromatin over length scales ranging from 0.5 to 75 Mb. This random loop (RL) model assumes a self-avoiding random walk folding of the polymer backbone and defines a probability P for 2 monomers to interact, creating loops of a broad size range. Model predictions are compared with systematic measurements of chromatin folding of the q-arms of chromosomes 1 and 11. The RL model can explain our observed data and suggests that on the tens-of-megabases length scale P is small, i.e., 10 -30 loops per 100 Mb. This is sufficient to enforce folding inside the confined space of a chromosome territory. On the 0.5-to 3-Mb length scale chromatin compaction differs in different subchromosomal domains. This aspect of chromatin structure is incorporated in the RL model by introducing heterogeneity along the fiber contour length due to different local looping probabilities. The RL model creates a quantitative and predictive framework for the identification of nuclear components that are responsible for chromatin-chromatin interactions and determine the 3-dimensional organization of the chromatin fiber.genome organization ͉ polymer model ͉ chromatin folding T he chromatin fiber inside the interphase nucleus of higher eukaryotes is folded and compacted on several length scales. On the smallest scale the basic filament is formed by wrapping double-stranded DNA around a histone protein octamer, forming a nucleosomal unit every Ϸ200 bp. This beads-on-a-string type filament in turn condenses to a fiber of 30-nm diameter, which detailed organization is still under debate (1-3). At bigger length scales the spatial organization of chromatin in the interphase nucleus is even more unclear. Imaging techniques do not allow one to directly follow the folding path of the chromatin fiber in the interphase nucleus. Therefore, indirect approaches have been used to obtain information about chromatin folding. One way, pursued in this study, is fluorescence in situ hybridization (FISH) to measure the relationship between the physical distance between genomic sequence elements (in m) and their genomic distance (in megabases). There have been several attempts to explain the folding of chromatin in the interphase nucleus using polymer models. The strength of polymer models is their ability to make predictions on the structure of chromatin by pointing out the driving forces for observed folding motifs. These predictions can then be tested experimentally. However, a polymer model that is able to explain chromatin folding spanning differen...

The bond fluctuation model on the simple cubic lattice is studied by Monte Carlo simulations on a multitransputer array, for polymer volume fractions φ in the range 0.025≤φ≤0.500 and chain lengths N in the range 20≤N≤200. Extensive data are presented on the dynamics of monomer displacements, center-of-gravity displacements, and relaxation times. This study is complementary to previous work, in which the crossover scaling properties of the chain linear dimensions, structure factor, and self-diffusion constant were tested for the same athermal model. The simulation technique takes both excluded volume interactions and entanglement constraints into account, but ignores hydrodynamic forces. Our results describe the crossover from Rouse behavior of swollen chains (τ∼N1+2ν, ν being the exponent describing the radius R of the chains, R∼Nν ) to reptation, τ∼N3. Since the excluded volume screening length is found to be smaller than the tube diameter by a factor of about 3, the rescaled times Wτ/N1+2ν decrease first as a function of the scaled chain length Ñ∼Nφ1/(3ν−1), before they increase due to the onset of reptation. Additional evidence for reptative behavior is found by identifying the several successive crossovers in the time-dependent displacements predicted by de Gennes.

Mathematical modeling is required for understanding the complex behavior of large signal transduction networks. Previous attempts to model signal transduction pathways were often limited to small systems or based on qualitative data only. Here, we developed a mathematical modeling framework for understanding the complex signaling behavior of CD95(APO-1/Fas)-mediated apoptosis. Defects in the regulation of apoptosis result in serious diseases such as cancer, autoimmunity, and neurodegeneration. During the last decade many of the molecular mechanisms of apoptosis signaling have been examined and elucidated. A systemic understanding of apoptosis is, however, still missing. To address the complexity of apoptotic signaling we subdivided this system into subsystems of different information qualities. A new approach for sensitivity analysis within the mathematical model was key for the identification of critical system parameters and two essential system properties: modularity and robustness. Our model describes the regulation of apoptosis on a systems level and resolves the important question of a threshold mechanism for the regulation of apoptosis.

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