Multi-genome Core Pathway Identification through Gene Clustering

Part 8: First Workshop on Algorithms for Data and Text Mining in Bioinformatics (WADTMB 2012)International audienceIn the wake of gene-oriented data analysis in large-scale bioinformatics studies, focus in research is currently shifting towards the analysis of the functional association of genes, namely the metabolic pathways in which genes participate. The goal of this paper is to attempt to identify the core genes in a specific pathway, based on a user-defined selection of genomes. To this end, a novel methodology has been developed that uses data from the KEGG database, and through the application of the MCL clustering algorithm, identifies clusters that correspond to different “layers” of genes, either on a phylogenetic or a functional level. The algorithm’s complexity, evaluated experimentally, is presented and the results on a characteristic case study are discussed

Synthetic Neutrality for Artificial Evolution

Recent works in both evolution theory and molecular biology have brought up the part played by selective neutrality in evolution dynamics. Contrary to the classical metaphor of fitness landscapes, the dynamics are not viewed as a climb towards optimal solutions but rather as explorations of networks of equivalent selective genotypes followed by jumps towards other networks. Although the benefit of neutrality is well known, it is hardly exploited in the genetic algorithm (GA) field. The only works about this subject deal with the influence of the inherent neutrality of a fitness landscape for evolution dynamics. In this paper, we propose a very different approach which consists to introduce "handmade" neutrality into the fitness landscape. Without any hypothesis about the inherent neutrality, we show that a GA is able to exploit new paths through the fitness landscape owing to the synthetic neutrality

Visualizing Related Metabolic Pathways in Two and a Half Dimensions

We propose a method for visualizing a set of related metabolic pathways using 2 2 D graph drawing. Interdependent, two-dimensional layouts of each pathway are stacked on top of each other so that biologists get a full picture of subtle and significant di#erences among the pathways. Layouts are determined by a global layout of the union of all pathway-representing graphs using a variant of the proven Sugiyama approach for layered graph drawing that allows edges to cross if they appear in di#erent graphs

DNA starts to learn poker

Abstract. DNA is used to implement a simplified version of poker. Strategies are evolved that mix bluffing with telling the truth. The essential features are (1) to wait your turn, (2) to default to the most conservative course, (3) to probabilistically override the default in some cases, and (4) to learn from payoffs. Two players each use an independent population of strategies that adapt and learn from their experiences in competition.