Probabilistic Clustering of Sequences: Inferring new bacterial regulons by comparative genomics

Genome wide comparisons between enteric bacteria yield large sets of conserved putative regulatory sites on a gene by gene basis that need to be clustered into regulons. Using the assumption that regulatory sites can be represented as samples from weight matrices we derive a unique probability distribution for assignments of sites into clusters. Our algorithm, 'PROCSE' (probabilistic clustering of sequences), uses Monte-Carlo sampling of this distribution to partition and align thousands of short DNA sequences into clusters. The algorithm internally determines the number of clusters from the data, and assigns significance to the resulting clusters. We place theoretical limits on the ability of any algorithm to correctly cluster sequences drawn from weight matrices (WMs) when these WMs are unknown. Our analysis suggests that the set of all putative sites for a single genome (e.g. E. coli) is largely inadequate for clustering. When sites from different genomes are combined and all the homologous sites from the various species are used as a block, clustering becomes feasible. We predict 50-100 new regulons as well as many new members of existing regulons, potentially doubling the number of known regulatory sites in E. coli.Comment: 27 pages including 9 figures and 3 table

An analysis of the XOR dynamic problem generator based on the dynamical system

This is the post-print version of the article - Copyright @ 2010 Springer-VerlagIn this paper, we use the exact model (or dynamical system approach) to describe the standard evolutionary algorithm (EA) as a discrete dynamical system for dynamic optimization problems (DOPs). Based on this dynamical system model, we analyse the properties of the XOR DOP Generator, which has been widely used by researchers to create DOPs from any binary encoded problem. DOPs generated by this generator are described as DOPs with permutation, where the fitness vector is changed according to a permutation matrix. Some properties of DOPs with permutation are analyzed, which allows explaining some behaviors observed in experimental results. The analysis of the properties of problems created by the XOR DOP Generator is important to understand the results obtained in experiments with this generator and to analyze the similarity of such problems to real world DOPs.This work was supported by Brazil FAPESP under Grant 04/04289-6 and by UK EPSRC under Grant EP/E060722/2

Evolutionary games and quasispecies

We discuss a population of sequences subject to mutations and frequency-dependent selection, where the fitness of a sequence depends on the composition of the entire population. This type of dynamics is crucial to understand the evolution of genomic regulation. Mathematically, it takes the form of a reaction-diffusion problem that is nonlinear in the population state. In our model system, the fitness is determined by a simple mathematical game, the hawk-dove game. The stationary population distribution is found to be a quasispecies with properties different from those which hold in fixed fitness landscapes.Comment: 7 pages, 2 figures. Typos corrected, references updated. An exact solution for the hawks-dove game is provide

On the Neutrality of Flowshop Scheduling Fitness Landscapes

Solving efficiently complex problems using metaheuristics, and in particular local searches, requires incorporating knowledge about the problem to solve. In this paper, the permutation flowshop problem is studied. It is well known that in such problems, several solutions may have the same fitness value. As this neutrality property is an important one, it should be taken into account during the design of optimization methods. Then in the context of the permutation flowshop, a deep landscape analysis focused on the neutrality property is driven and propositions on the way to use this neutrality to guide efficiently the search are given.Comment: Learning and Intelligent OptimizatioN Conference (LION 5), Rome : Italy (2011

Sublingual allergen immunotherapy with a liquid birch pollen product in patients with seasonal allergic rhinoconjunctivitis with or without asthma

Background: Sublingual allergen immunotherapy (SLIT) has been demonstrated to be both clinically efficacious and safe. However, in line with the current regulatory guidance from the European Medicines Agency, allergen immunotherapy (AIT) products must demonstrate their efficacy and safety in pivotal phase III trials for registration. Objective: We sought to investigate the efficacy and safety of sublingual high-dose liquid birch pollen extract (40,000 allergy units native [AUN]/mL) in adults with birch pollen allergy. Methods: A randomized, double-blind, placebo-controlled, parallel-group multicenter trial was conducted in 406 adult patients with moderate-to-severe birch pollen-induced allergic rhinoconjunctivitis with or without mild-to-moderate controlled asthma. Treatment was started 3 to 6 months before the birch pollen season and continued during the season in 40 clinical study centers in 5 European countries. For primary end point assessment, the recommended combined symptom and medication score of the European Academy of Allergy and Clinical Immunology was used. Secondary end points included quality-of-life assessments, immunologic parameters, and safety. Results: Primary efficacy results demonstrated a significant (P < .0001) and clinically relevant (32%) reduction in the combined symptom and medication score compared with placebo after 3 to 6 months of SLIT. Significantly better rhinoconjunctivitis quality-of-life scores (P < .0001) and the patient's own overall assessment of his or her health status, including the visual analog scale score (Euro Quality of Life Visual Analogue Scale; P = .0025), were also demonstrated. In total, a good safety profile of SLIT was observed. Conclusion: This study confirmed both the clinical efficacy and safety of a sublingual liquid birch pollen extract in adults with birch pollen allergy in a pivotal phase III trial (EudraCT: 2013-005550-30; ClinicalTrials. gov: NCT02231307)

Coupled Replicator Equations for the Dynamics of Learning in Multiagent Systems

Starting with a group of reinforcement-learning agents we derive coupled replicator equations that describe the dynamics of collective learning in multiagent systems. We show that, although agents model their environment in a self-interested way without sharing knowledge, a game dynamics emerges naturally through environment-mediated interactions. An application to rock-scissors-paper game interactions shows that the collective learning dynamics exhibits a diversity of competitive and cooperative behaviors. These include quasiperiodicity, stable limit cycles, intermittency, and deterministic chaos--behaviors that should be expected in heterogeneous multiagent systems described by the general replicator equations we derive.Comment: 4 pages, 3 figures, http://www.santafe.edu/projects/CompMech/papers/credlmas.html; updated references, corrected typos, changed conten

On Non-Elitist Evolutionary Algorithms Optimizing Fitness Functions with a Plateau

We consider the expected runtime of non-elitist evolutionary algorithms (EAs), when they are applied to a family of fitness functions with a plateau of second-best fitness in a Hamming ball of radius r around a unique global optimum. On one hand, using the level-based theorems, we obtain polynomial upper bounds on the expected runtime for some modes of non-elitist EA based on unbiased mutation and the bitwise mutation in particular. On the other hand, we show that the EA with fitness proportionate selection is inefficient if the bitwise mutation is used with the standard settings of mutation probability.Comment: 14 pages, accepted for proceedings of Mathematical Optimization Theory and Operations Research (MOTOR 2020). arXiv admin note: text overlap with arXiv:1908.0868

Aquilegia, Vol. 34 No. 1, Spring 2010, Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1131/thumbnail.jp