Showing papers by "Alfonso Rodríguez-Patón published in 2011"

A simple negative interaction in the positive transcriptional feedback of a single gene is sufficient to produce reliable oscillations.

Abstract: Negative and positive transcriptional feedback loops are present in natural and synthetic genetic oscillators. A single gene with negative transcriptional feedback needs a time delay and sufficiently strong nonlinearity in the transmission of the feedback signal in order to produce biochemical rhythms. A single gene with only positive transcriptional feedback does not produce oscillations. Here, we demonstrate that this single-gene network in conjunction with a simple negative interaction can also easily produce rhythms. We examine a model comprised of two well-differentiated parts. The first is a positive feedback created by a protein that binds to the promoter of its own gene and activates the transcription. The second is a negative interaction in which a repressor molecule prevents this protein from binding to its promoter. A stochastic study shows that the system is robust to noise. A deterministic study identifies that the dynamics of the oscillator are mainly driven by two types of biomolecules: the protein, and the complex formed by the repressor and this protein. The main conclusion of this paper is that a simple and usual negative interaction, such as degradation, sequestration or inhibition, acting on the positive transcriptional feedback of a single gene is a sufficient condition to produce reliable oscillations. One gene is enough and the positive transcriptional feedback signal does not need to activate a second repressor gene. This means that at the genetic level an explicit negative feedback loop is not necessary. The model needs neither cooperative binding reactions nor the formation of protein multimers. Therefore, our findings could help to clarify the design principles of cellular clocks and constitute a new efficient tool for engineering synthetic genetic oscillators.

Spiking Neural P Systems with Several Types of Spikes

Abstract: With a motivation related to gene expression, where enzymes act in series, somewhat similar to the train spikes traveling along the axons of neurons, we consider an extension of spiking neural P systems, where several types of “spikes" are allowed. The power of the obtained spiking neural P systems is investigated. Some further extensions are mentioned, such as considering a process of decay in time of the spikes

P systems with proteins on membranes: a survey

Abstract: The paper is a survey of the recent model of P systems with proteins on membranes introduced by Paun and Popa in 2006. This model can be viewed as an extension of the highly successful paper of (Paun and Paun 2002) describing P systems based on symport/antiport. The previous model represented an important change of direction from strings to objects in the area of P systems. The main drawback of the model from 2002 was the massive parallelism that is not seen in real life. The 2006 model was a step in controlling the parallelism the same way it is done in nature in symporters and antiporters: these processes take place through protein channels embedded at the level of the membrane which can only be used by a molecule at a time, thus yielding a sequentiality with respect to the number of such proteins embedded in the membrane.

Simulating a rock-scissors-paper bacterial game with a discrete cellular automaton

Abstract: This paper describes some of the results obtained after the design and implementation of a discrete cellular automata simulating the generation, degradation and diffusion of particles in a two dimensional grid where different colonies of bacteria coexist and interact. This lattice-based simulator use a random walk-based algorithm to diffuse particles in a 2D discrete lattice. As first results, we analyze and show the oscillatory dynamical behavior of 3 colonies of bacteria competing in a non-transitive relationship analogous to a Rock-Scissors-Paper game (Rock bacteria beats Scissors bacteria that beats Paper bacteria; and Paper beats Rock bacteria). The interaction and communication between bacteria is done with the quorum sensing process through the generation and diffusion of three small molecules called autoinducers. These are the first results obtained from the first version of a general simulator able to model some of the complex molecular information processing and rich communication processes in synthetic bacterial ecosystems.

Autonomous resolution based on DNA strand displacement

Abstract: We present a computing model based on the technique of DNA strand displacement which performs a chain of logical resolutions with logical formulae in conjunctive normal form. The model is enzymefree and autonomous. Each clause of a formula is encoded in a separate DNA molecule: propositions are encoded assigning a strand to each proposition p, and its complementary strand to the proposition ¬p; clauses are encoded comprising different propositions in the same strand. The model allows to run logic programs composed of Horn clauses by cascading resolution steps and, therefore, possibly function as an autonomous programmable nano-device. This technique can be also used to solve SAT. The resulting SAT algorithm has a linear time complexity in the number of resolution steps, whereas its spatial complexity is exponential in the number of variables of the formula.

A review of the nondeterministic waiting time algorithm

Abstract: We provide the description for the nondeterministic waiting time (NWT) algorithm, a biochemical modeling approach based on the membrane systems paradigm of computation. The technique provides a unique (different to Gillespie's algorithm or ODE modeling) perspective on the biochemical evolution of the cell. That is, depending on the reactions and molecular multiplicities of a given model, our simulator is capable of producing results comparable to the alternative techniques--continuous and deterministic or discrete and stochastic. Some results for sample models are given, illustrating the differences between the NWT algorithm, the Gillespie algorithm, and the solutions to systems of ordinary differential equations. We have previously used this simulation technique to address issues surrounding Fas-induced apoptosis in cancerous cells and so-called latent HIV-infected cells.

On the power of families of recognizer spiking neural p systems

Abstract: The paper summarizes recent knowledge about computational power of spiking neural P systems and presents a sequence of new more general results. The concepts of recognizer SN P systems and of uniform families of SN P systems provide a formal framework for this study. We establish the relation of computational power of spiking neural P systems with various limitations to standard complexity classes like P, NP, PSPACE and P/poly.