Author: Community

Discrete models for protein structure prediction embed the protein amino acid sequence into a discrete spatial structure,
usually a lattice, where an optimal tertiary structure is predicted on the basis of simple assumptions relating to the hydrophobic–hydrophilic
character of amino acids in the sequence and to relevant interactions for free energy minimization. While the prediction problem
is known to be NP complete even in the simple setting of Dill’s model with a 2D-lattice, a variety of bio-inspired algorithms
for this problem have been proposed in the literature. Immunological algorithms are inspired by the kind of optimization that
immune systems perform when identifying and promoting the replication of the most effective antibodies against given antigens.
A quick, state-of-the-art survey of discrete models and immunological algorithms for protein structure prediction is presented
in this paper, and the main design and performance features of an immunological algorithm for this problem are illustrated
in a tutorial fashion.

The hand-made graphical representation of the configuration of a P system becomes a hard task when the number of membranes
and objects increases. In this paper we present a new software tool, called JPLANT, for computing and representing the evolution
of a P system model with membrane creation. We also present some experiments performed with JPLANT and point out new lines
for the research in computer graphics with membrane systems.