A tutorial for competent memetic algorithms: Model, taxonomy and design issues

The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (Moscato, 1989). These methods are inspired by models of natural systems that combine the evolutionary adaptation of a population with individual learning within the lifetimes of its members. Additionally, MAs are inspired by Richard Dawkin's concept of a meme, which represents a unit of cultural evolution that can exhibit local refinement (Dawkins, 1976). In the case of MA's, "memes" refer to the strategies (e.g., local refinement, perturbation, or constructive methods, etc.) that are employed to improve individuals. In this paper, we review some works on the application of MAs to well-known combinatorial optimization problems, and place them in a framework defined by a general syntactic model. This model provides us with a classification scheme based on a computable index D, which facilitates algorithmic comparisons and suggests areas for future research. Also, by having an abstract model for this class of metaheuristics, it is possible to explore their design space and better understand their behavior from a theoretical standpoint. We illustrate the theoretical and practical relevance of this model and taxonomy for MAs in the context of a discussion of important design issues that must be addressed to produce effective and efficient MAs

Measuring the similarity of protein structures by means of the universal similarity metric

Motivation: As an increasing number of protein structures become available, the need for algorithms that can quantify the similarity between protein structures increases as well. Thus, the comparison of proteins’ structures, and their clustering accordingly to a given similarity measure, is at the core of today’s biomedical research. In this paper, we show how an algorithmic information theory inspired Universal Similarity Metric (USM) can be used to calculate similarities between protein pairs.The method, besides being theoretically supported, is surprisingly simple to implement and computationally efficient. Results: Structural similarity between proteins in four different datasets was measured using the USM.The sample employed represented alpha, beta, alpha–beta, tim–barrel, globins and serpine protein types. The use of the proposed metric allows for a correct measurement of similarity and classification of the proteins in the four datasets. Availability: All the scripts and programs used for the preparation of this paper are available at http://www.cs.nott.ac.uk/ ~nxk/USM/protocol.html. In that web-page the reader will find a brief description on how to use the various scripts and programs.TIC2002-04242-C03-0

Mutagenesis as a Diversity Enhancer and Preserver in Evolution Strategies

Proceedings of: 9th International Symposium on Distributed Computing and Artificial Intelligence (DCAI 2012). Salamanca, March 28-30, 2012Mutagenesis is a process which forces the coverage of certain zones of the search space during the generations of an evolution strategy, by keeping track of the covered ranges for the different variables in the so called gene matrix. Originally introduced as an artifact to control the automated stopping criterion in a memetic algorithm, ESLAT, it also improved the exploration capabilities of the algorithm, even though this was considered a secondary matter and not properly analyzed or tested. This work focuses on this diversity enhancement, redefining mutagenesis to increase this characteristic, measuring this improvement over a set of twenty-seven unconstrained optimization functions to provide statistically significant results.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029-C02-02.Publicad

Phase diagram of self-assembled rigid rods on two-dimensional lattices: Theory and Monte Carlo simulations

Monte Carlo simulations and finite-size scaling analysis have been carried out to study the critical behavior in a two-dimensional system of particles with two bonding sites that, by decreasing temperature or increasing density, polymerize reversibly into chains with discrete orientational degrees of freedom and, at the same time, undergo a continuous isotropic-nematic (IN) transition. A complete phase diagram was obtained as a function of temperature and density. The numerical results were compared with mean field (MF) and real space renormalization group (RSRG) analytical predictions about the IN transformation. While the RSRG approach supports the continuous nature of the transition, the MF solution predicts a first-order transition line and a tricritical point, at variance with the simulation results.Comment: 12 pages, 10 figures, supplementary informatio

Simbiotics: a multi-scale integrative platform for 3D modeling of bacterial populations

Simbiotics is a spatially explicit multiscale modeling platform for the design, simulation and analysis of bacterial populations. Systems ranging from planktonic cells and colonies, to biofilm formation and development may be modeled. Representation of biological systems in Simbiotics is flexible, and user-defined processes may be in a variety of forms depending on desired model abstraction. Simbiotics provides a library of modules such as cell geometries, physical force dynamics, genetic circuits, metabolic pathways, chemical diffusion and cell interactions. Model defined processes are integrated and scheduled for parallel multithread and multi-CPU execution. A virtual lab provides the modeler with analysis modules and some simulated lab equipment, enabling automation of sample interaction and data collection. An extendable and modular framework allows for the platform to be updated as novel models of bacteria are developed, coupled with an intuitive user interface to allow for model definitions with minimal programming experience. Simbiotics can integrate existing standards such as SBML, and process microscopy images to initialize the 3D spatial configuration of bacteria consortia. Two case studies, used to illustrate the platform flexibility, focus on the physical properties of the biosystems modeled. These pilot case studies demonstrate Simbiotics versatility in modeling and analysis of natural systems and as a CAD tool for synthetic biology

On Meme Self-Adaptation in Spatially-Structured Multimemetic Algorithms

NMA 2014Multimemetic algorithms (MMAs) are memetic algorithms that explicitly exploit the evolution of memes, i.e., non-genetic expressions of problem-solving strategies. We consider a class of MMAs in which these memes are rewriting rules whose length can be fixed during the run of the algorithm or self-adapt during the search process. We analyze this self-adaptation in the context of spatially-structured MMAs, namely MMAs in which the population is endowed with a certain topology to which interactions (from the point of view of selection and variation operators) are constrained. For the problems considered, it is shown that panmictic (i.e., non-structured) MMAs are more sensitive to this self-adaptation, and that using variable-length memes seems to be a robust strategy throughout different population structures.This work is partially supported by MICINN project ANYSELF (TIN2011-28627-C04-01), by Junta de Andaluía project DNEMESIS (P10-TIC-6083) and by Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech

Automatic Selection of Verification Tools for Efficient Analysis of Biochemical Models

YesMotivation: Formal verification is a computational approach that checks system correctness (in relation to a desired functionality). It has been widely used in engineering applications to verify that systems work correctly. Model checking, an algorithmic approach to verification, looks at whether a system model satisfies its requirements specification. This approach has been applied to a large number of models in systems and synthetic biology as well as in systems medicine. Model checking is, however, computationally very expensive, and is not scalable to large models and systems. Consequently, statistical model checking (SMC), which relaxes some of the constraints of model checking, has been introduced to address this drawback. Several SMC tools have been developed; however, the performance of each tool significantly varies according to the system model in question and the type of requirements being verified. This makes it hard to know, a priori, which one to use for a given model and requirement, as choosing the most efficient tool for any biological application requires a significant degree of computational expertise, not usually available in biology labs. The objective of this paper is to introduce a method and provide a tool leading to the automatic selection of the most appropriate model checker for the system of interest. Results: We provide a system that can automatically predict the fastest model checking tool for a given biological model. Our results show that one can make predictions of high confidence, with over 90% accuracy. This implies significant performance gain in verification time and substantially reduces the “usability barrier” enabling biologists to have access to this powerful computational technology.EPSRC, Innovate U

TopoGSA: network topological gene set analysis

Summary: TopoGSA (Topology-based Gene Set Analysis) is a web-application dedicated to the computation and visualization of network topological properties for gene and protein sets in molecular interaction networks. Different topological characteristics, such as the centrality of nodes in the network or their tendency to form clusters, can be computed and compared with those of known cellular pathways and processes