Gabi Escuela

Learn More
A protein is a linear chain of amino acids that folds into a unique functional structure, called its native state. In this state, proteins show repeated sub-structures like alpha helices and beta sheets. This suggests that native structures may be captured by the formalism known as Lindenmayer systems (L-systems). In this paper an evolutionary approach is(More)
The process of designing a P system in order to perform a task is a hard job. The researcher has often only an approximate idea of the design, but finding the exact description of the rules is a heavy handmade work. In this paper we introduce PSystemEvolver, an evolutionary algorithm based on generative encoding, that could help to design a P system to(More)
Cycles are abundant in most kinds of networks, especially in biological ones. Here, we investigate their role in the evolution of a chemical reaction system from one self-sustaining composition of molecular species to another and their influence on the stability of these compositions. While it is accepted that, from a topological standpoint, they enhance(More)
We investigate several evolutionary computation approaches as a mechanism to “program” networks of excitable chemical droplets. For this kind of systems, we assigned a specific task and concentrated on the characteristics of signals representing symbols. Given a Boolean function as target functionality, 2D networks composed of 10 × 10 droplets were(More)
An encoding scheme for protein folding on lattice models, inspired by parametric L-systems, was proposed. The encoding incorporates problem domain knowledge in the form of predesigned production rules that capture commonly known secondary structures: α-helices and β-sheets. The ability of this encoding to capture protein native con-formations was tested(More)
Reconstruction of signal transduction network models based on incomplete information about network structure and dynamical behaviour is a major challenge in current systems biology. In particular, interactions within signalling networks are frequently characterised by partially unknown protein phosphorylation and dephosphory-lation cascades at a(More)
Distributed Genetic Algorithm (DGA) is one of the most promising choices among the optimization methods. In this paper we describe DGAFrame, a flexible framework for evolutionary computation, written in Java. DGAFrame executes GAs across a range of machines communicating through RMI network technology, allowing the implementation of portable, flexible GAs(More)