An extensive rewiring of cell metabolism supports enhanced proliferation in cancer cells. We propose a systems level approach to describe this phenomenon based on Flux Balance Analysis (FBA). The approach does not explicit a cell biomass formation re
action to be maximized, but takes into account an ensemble of alternative flux distributions that match the cancer metabolic rewiring (CMR) phenotype description. The underlying concept is that the analysis the common/distinguishing properties of the ensemble can provide indications on how CMR is achieved and sustained and thus on how it can be controlled.
The preliminary analyses on a multiscale model of intestinal crypt dynamics are here presented. The model combines a morphological model, based on the Cellular Potts Model (CPM), and a gene regulatory network model, based on Noisy Random Boolean Netw
orks (NRBNs). Simulations suggest that the stochastic differentiation process is itself sufficient to ensure the general homeostasis in the asymptotic states, as proven by several measures.
The hydrophobic-polar (HP) model has been widely studied in the field of protein structure prediction (PSP) both for theoretical purposes and as a benchmark for new optimization strategies. In this work we introduce a new heuristics based on Ant Colo
ny Optimization (ACO) and Markov Chain Monte Carlo (MCMC) that we called Hybrid Monte Carlo Ant Colony Optimization (HMCACO). We describe this method and compare results obtained on well known HP instances in the 3 dimensional cubic lattice to those obtained with standard ACO and Simulated Annealing (SA). All methods were implemented using an unconstrained neighborhood and a modified objective function to prevent the creation of overlapping walks. Results show that our methods perform better than the other heuristics in all benchmark instances.
Metapopulations are models of ecological systems, describing the interactions and the behavior of populations that live in fragmented habitats. In this paper, we present a model of metapopulations based on the multivolume simulation algorithm tau-DPP
, a stochastic class of membrane systems, that we utilize to investigate the influence that different habitat topologies can have on the local and global dynamics of metapopulations. In particular, we focus our analysis on the migration rate of individuals among adjacent patches, and on their capability of colonizing the empty patches in the habitat. We compare the simulation results obtained for each habitat topology, and conclude the paper with some proposals for other research issues concerning metapopulations.
The energy region spanning from $sim 10^{17}$ to $lesssim 10^{19}$ eV is critical for understanding both, the Galactic and the extragalactic cosmic ray fluxes. This is the region where the propagation regime of nuclei inside the Galactic magnetic env
ironment changes from diffusive to ballistic, as well as the region where, very likely, the most powerful Galactic accelerators reach their maximum output energies. In this work, a diffusion Galactic model is used to analyze the end of the Galactic cosmic ray spectrum and its mixing with the extragalactic cosmic ray flux. In particular, we study the conditions that must be met, from the spectral and composition points of view, by the Galactic and the extragalactic fluxes in order to reproduce simultaneously the total spectrum and elongation rate measured over the transition region by HiRes and Auger. Our analysis favors a mixed extragalactic spectrum in combination with a Galactic spectrum enhanced by additional high energy components, i.e., extending beyond the maximum energies expected from regular supernova remnants. The two additional components have mixed composition, with the lowest energy one heavier than the highest energy one. The potential impact on the astrophysical analysis of the assumed hadronic interaction model is also assessed in detail.
