12,777 research outputs found
Differential equations and cellular automata models of the growth of cell cultures and transformation foci
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A cellular automata model for the simulation of in vitro carcinogenesis tests
No full textIn vitro tests are very powerful methods to assess the carcinogenic effects of different substances and to study the initial phases of tumor development. A CA model of the formation of transformation foci in cell cultures which are exposed to a carcinogen is presented here, based on known facts about carcinogenesis and about reasonable assumptions, which gives rise to a cell growth dynamics similar to the one experimentally observed. The model can be used to test formal hypotheses about different interfering phenomena and about their relative strengt
THE DIFFUSION OF PERTURBATIONS IN A MODEL OF COUPLED RANDOM BOOLEAN NETWORKS
No full textDeciphering the influence of the interaction among the constituentsof a complex system on the overall behaviour is one of themain goals of complex systems science. The model we present in thiswork is a 2D square cellular automaton whose of each cell is occupiedby a complete random Boolean network. Random Boolean networks area well-known simplified model of genetic regulatory networks and thismodel of interacting RBNs may be therefore regarded as a simplifiedmodel of a tissue or a monoclonal colony. The mechanism of cell-to-cellinteraction is here simulated letting some nodes of a particular networkbeing influenced by the state of some nodes belonging to its neighbouringcells. One possible means to investigate the overall dynamics of acomplex system is studying its response to perturbations. Our analysesfollow this methodological approach. Even though the dynamics of thesystem is far from trivial we could show in a clear way how the interactionaffects the dynamics and the global degree of order
COMUNICAZIONE CELLULARE, LIVELLI E STRUTTURE ORDINATE
No full textLe cellule interagiscono per formare strutture di ordine superiore come colonie monoclonali o tessuti cellulari. Le Reti Booleane Casuali (RBN) possono essere considerate come modello di una cellula isolata ed è dunque di estrema importanza l’analisi della relazione tra la dinamica di una singola RBN e quella di un insieme di reti interagenti. Presentiamo un modello adatto allo scopo: un automa cellulare bidimensionale in cui ogni cella è occupata da una RBN. Il meccanismo di interazione tra le reti dell’automa è ispirato alla comunicazione intercellulare. L’analisi dello stato di ordine del modello può avvenire al livello dell’automa e a quello della singola rete costituente. Si osserva che l’influenza della forza di interazione sul grado di ordine delle RBN non è univoca, in alcuni casi l’ordine è accresciuto, mentre in altri è amplificato il disordine. Sono state individuate tre tipologie di comportamento, al crescere dell’intensità dell’interazione, che appaiono correlate alla dinamica della specifica RBN in assenza di interazione
Valanghe in reti booleane a topologia scale-free
No full textL'articolo tratta della simulazione di eventi di knock-out tramite reti booleane con topologia scale-free, e del confronto dei risultati con dati reali (eventi in Saccaromicies Cerevisiae
Information transfer among coupled Random Boolean Networks
No full textInformation processing and information flow occur at many levels in the course of an organism’s development and throughout its lifespan. Biological networks inside cells transmit information from their inputs (e.g. the concentrations of proteins or other signaling molecules) to their outputs (e.g. the expression levels of various genes). Moreover, cells do not exist in isolation, but they constantly interact with one another. We study the information flow in a model of interacting genetic networks, which are represented as Boolean graphs. It is observed that the information transfer among the networks is not linearly dependent on the amount of nodes that are able to influence the state of genes in surrounding cells
MABS validation through repeated execution and data mining analysis
No full textAgent Based Modelling is the most interesting and advanced approach for simulating a complex system: in a social context, the single parts and the whole are often very hard to describe in detail. Besides, there are agent based formalisms which allow to study the emergency of social behaviour with the creation and study of models, known as artificial societies. Thanks to the ever increasing computational power, it's been possible to use such models to create software, based on intelligent agents, which aggregate behaviour is complex and difficult to predict, and can be used in open and distributed systems. Data mining is born in the last decades in order to help users in finding useful knowledge from the otherwise overwhelming amount of data available nowadays from the web and the data collected every day by companies. Data Mining techniques can therefore be the keystone to reveal non-trivial knowledge expressed by the initial assumption used to build the micro-level of the model and the structure of the society of agents that emerged from the simulation
Comunicazione cellulare, livelli e strutture ordinate.
No full textLe cellule interagiscono per formare strutture di ordine superiorecome colonie monoclonali o tessuti cellulari. Le Reti Booleane Casuali (RBN)possono essere considerate come modello di una cellula isolata ed è dunque diestrema importanza l’analisi della relazione tra la dinamica di una singola RBNe quella di un insieme di reti interagenti. Presentiamo un modello adatto alloscopo: un automa cellulare bidimensionale in cui ogni cella è occupata da unaRBN. Il meccanismo di interazione tra le reti dell’automa è ispirato allacomunicazione intercellulare. L’analisi dello stato di ordine del modello puòavvenire al livello dell’automa e a quello della singola rete costituente. Siosserva che l’influenza della forza di interazione sul grado di ordine delle RBNnon è univoca, in alcuni casi l’ordine è accresciuto, mentre in altri è amplificatoil disordine. Sono state individuate tre tipologie di comportamento, al cresceredell’intensità dell’interazione, che appaiono correlate alla dinamica dellaspecifica RBN in assenza di interazione
Cell differentiation in noisy random boolean networks.
No full textThe dynamics of genetic regulatory networks are often affected bystochastic noise, due to the small number of molecules involved in some reactions.The role of these fluctuations is analyzed in a discrete model of gene regulatorynetworks, i.e. that of noisy random Boolean networks. By relating the asymptoticstates of the noisy system to the different cell types, we show how the main featuresof the important process of cell differentiation can be described by assuming thatthe noise level changes as differentiation proceeds. Differentiation is seen as a seriesof transitions from an asymptotic state in which the system can wander amongmany states under the action of noise to other asymptotic states in which the systemcan reach fewer and fewer states. This model easily describes the fact that multipotentcells can stochastically differentiate along various routes.We show here thatthe process can also be controlled (as it happens in the embryo growth) so that it ispossible to determine the final fully differentiated state of the cell. This is achievedby forcing some genes, which are called here "swithces", to take constant values,in a way which mimicks the influence of external signals, and by simoultaneouslyvarying the noise level in the cel
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