Evolutionary dynamics of the immunodominant repeats of the Plasmodium vivax malaria-vaccine candidate circumsporozoite protein (CSP)

The circumsporozoite protein (CSP) of Plasmodium vivax, a major target for malaria vaccine development, has immunodominant B-cell epitopes mapped to central nonapeptide repeat arrays. To determine whether rearrangements of repeat motifs during mitotic DNA replication of parasites create significant CSP diversity under conditions of low effective meiotic recombination rates, we examined csp alleles from sympatric P. vivax isolates systematically sampled from an area of low malaria endemicity in Brazil over a period of 14 months. Nine unique csp types, comprising six different nona peptide repeats, were observed in 45 isolates analyzed. Identical or nearly identical repeats predominated in most arrays, consistent with their recent expansion. We found strong linkage disequilibrium at sites across the chromosome 8 segment flanking the csp locus, consistent with rare meiotic recombination in this region. We conclude that CSP repeat diversity may not be severely constrained by rare meiotic recombination in areas of low malaria endemicity. New repeat variants may be readily created by nonhomologous recombination even when meiotic recombination is rare, with potential implications for CSP-based vaccine development. (C) 2010 Elsevier B.V. All rights reserved.

Sequence diversity and evolutionary dynamics of the dimorphic antigen merozoite surface protein-6 and other Msp genes of Plasmodium falciparum

Immune evasion by Plasmodium falciparum is favored by extensive allelic diversity of surface antigens. Some of them, most notably the vaccine-candidate merozoite surface protein (MSP)-1, exhibit a poorly understood pattern of allelic dimorphism, in which all observed alleles group into two highly diverged allelic families with few or no inter-family recombinants. Here we describe contrasting levels and patterns of sequence diversity in genes encoding three MSP-1-associated surface antigens of P. falciparum, ranging from an ancient allelic dimorphism in the Msp-6 gene to a near lack of allelic divergence in Msp-9 to a more classical multi-allele polymorphism in Msp-7 Other members of the Msp-7 gene family exhibit very little polymorphism in non-repetitive regions. A comparison of P. falciparum Msp-6 sequences to an orthologous sequence from P. reichenowi provided evidence for distinct evolutionary histories of the 5` and 3` segments of the dimorphic region in PfMsp-6, consistent with one dimorphic lineage having arisen from recombination between now-extinct ancestral alleles. In addition. we uncovered two surprising patterns of evolution in repetitive sequence. Firsts in Msp-6, large deletions are associated with (nearly) identical sequence motifs at their borders. Second, a comparison of PfMsp-9 with the P. reichenowi ortholog indicated retention of a significant inter-unit diversity within an 18-base pair repeat within the coding region of P. falciparum, but homogenization in P. reichenowi. (C) 2009 Elsevier B.V. All rights reserved.

Evolutionary history of trypanosomes from South American caiman (Caiman yacare) and African crocodiles inferred by phylogenetic analyses using SSU rDNA and gGAPDH genes

In this study, using a combined data set of SSU rDNA and gGAPDH gene sequences, we provide phylogenetic evidence that supports Clustering of crocodilian trypanosomes from the Brazilian Caiman yacare (Alligatoridae) and Trypanosoma grayi, a species that Circulates between African crocodiles (Crocodilydae) and tsetse flies. In a survey of trypanosomes in Caiman yacare from the Brazilian Pantanal, the prevalence of trypanosome infection was 35% as determined by microhaematocrit and haemoculture, and 9 cultures were obtained. The morphology of trypomastigotes from caiman blood and tissue imprints was compared with those described for other crocodilian trypanosomes. Differences in morphology and growth behaviour of caiman trypanosomes were corroborated by molecular polymorphism that revealed 2 genotypes. Eight isolates were ascribed to genotype Cay01 and 1 to genotype Cay02. Phylogenetic inferences based on concatenated SSU rDNA and gGAPDII sequences showed that caiman isolates are closely related to T. grayi, constituting a well-supported monophyletic assemblage (clade T. grayi). Divergence time estimates based on clade composition, and biogeographical and geological events were used to discuss the relationships between the evolutionary histories of crocodilian trypanosomes and their hosts.

Efficiency issues of evolutionary k-means

One of the top ten most influential data mining algorithms, k-means, is known for being simple and scalable. However, it is sensitive to initialization of prototypes and requires that the number of clusters be specified in advance. This paper shows that evolutionary techniques conceived to guide the application of k-means can be more computationally efficient than systematic (i.e., repetitive) approaches that try to get around the above-mentioned drawbacks by repeatedly running the algorithm from different configurations for the number of clusters and initial positions of prototypes. To do so, a modified version of a (k-means based) fast evolutionary algorithm for clustering is employed. Theoretical complexity analyses for the systematic and evolutionary algorithms under interest are provided. Computational experiments and statistical analyses of the results are presented for artificial and text mining data sets. (C) 2010 Elsevier B.V. All rights reserved.

Evolutionary fuzzy clustering of relational data

This paper is concerned with the computational efficiency of fuzzy clustering algorithms when the data set to be clustered is described by a proximity matrix only (relational data) and the number of clusters must be automatically estimated from such data. A fuzzy variant of an evolutionary algorithm for relational clustering is derived and compared against two systematic (pseudo-exhaustive) approaches that can also be used to automatically estimate the number of fuzzy clusters in relational data. An extensive collection of experiments involving 18 artificial and two real data sets is reported and analyzed. (C) 2011 Elsevier B.V. All rights reserved.

On the efficiency of evolutionary fuzzy clustering

This paper tackles the problem of showing that evolutionary algorithms for fuzzy clustering can be more efficient than systematic (i.e. repetitive) approaches when the number of clusters in a data set is unknown. To do so, a fuzzy version of an Evolutionary Algorithm for Clustering (EAC) is introduced. A fuzzy cluster validity criterion and a fuzzy local search algorithm are used instead of their hard counterparts employed by EAC. Theoretical complexity analyses for both the systematic and evolutionary algorithms under interest are provided. Examples with computational experiments and statistical analyses are also presented.

Evolutionary tuning of SVM parameter values in multiclass problems

Support vector machines (SVMs) were originally formulated for the solution of binary classification problems. In multiclass problems, a decomposition approach is often employed, in which the multiclass problem is divided into multiple binary subproblems, whose results are combined. Generally, the performance of SVM classifiers is affected by the selection of values for their parameters. This paper investigates the use of genetic algorithms (GAs) to tune the parameters of the binary SVMs in common multiclass decompositions. The developed GA may search for a set of parameter values common to all binary classifiers or for differentiated values for each binary classifier. (C) 2008 Elsevier B.V. All rights reserved.

A hybrid approach to learn with imbalanced classes using evolutionary algorithms

There is an increasing interest in the application of Evolutionary Algorithms (EAs) to induce classification rules. This hybrid approach can benefit areas where classical methods for rule induction have not been very successful. One example is the induction of classification rules in imbalanced domains. Imbalanced data occur when one or more classes heavily outnumber other classes. Frequently, classical machine learning (ML) classifiers are not able to learn in the presence of imbalanced data sets, inducing classification models that always predict the most numerous classes. In this work, we propose a novel hybrid approach to deal with this problem. We create several balanced data sets with all minority class cases and a random sample of majority class cases. These balanced data sets are fed to classical ML systems that produce rule sets. The rule sets are combined creating a pool of rules and an EA is used to build a classifier from this pool of rules. This hybrid approach has some advantages over undersampling, since it reduces the amount of discarded information, and some advantages over oversampling, since it avoids overfitting. The proposed approach was experimentally analysed and the experimental results show an improvement in the classification performance measured as the area under the receiver operating characteristics (ROC) curve.

Evolutionary model trees for handling continuous classes in machine learning

Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

Network genealogy of 195-bp satellite DNA supports the superimposed hybridization hypothesis of Trypanosoma cruzi evolutionary pattern

Trypanosoma cruzi is highly diverse genetically and has been partitioned into six discrete typing units (DTUs), recently re-named T. cruzi I-VI. Although T. cruzi reproduces predominantly by binary division, accumulating evidence indicates that particular DTUs are the result of hybridization events. Two major scenarios for the origin of the hybrid lineages have been proposed. It is accepted widely that the most heterozygous TcV and TcVI DTUs are the result of genetic exchange between TcII and TcIII strains. On the other hand, the participation of a TcI parental in the current genome structure of these hybrid strains is a matter of debate. Here, sequences of the T. cruzi-specific 195-bp satellite DNA of TcI, TcII, Tat, TcV, and TcVI strains have been used for inferring network genealogies. The resulting genealogy showed a high degree of reticulation, which is consistent with more than one event of hybridization between the Tc DTUs. The data also strongly suggest that Tat is a hybrid with two distinct sets of satellite sequences, and that genetic exchange between TcI and TcII parentals occurred within the pedigree of the TcV and TcVI DTUs. Although satellite DNAs belong to the fast-evolving portion of eukaryotic genomes, in >100 satellite units of nine T. cruzi strains we found regions that display 100% identity. No DTU-specific consensus motifs were identified, inferring species-wide conservation. (C) 2010 Elsevier B.V. All rights reserved.

Developing Box-Pushing Behaviours Using Evolutionary Robotics

The context of this report and the IRIDIA laboratory are described in the preface. Evolutionary Robotics and the box-pushing task are presented in the introduction.The building of a test system supporting Evolutionary Robotics experiments is then detailed. This system is made of a robot simulator and a Genetic Algorithm. It is used to explore the possibility of evolving box-pushing behaviours. The bootstrapping problem is explained, and a novel approach for dealing with it is proposed, with results presented.Finally, ideas for extending this approach are presented in the conclusion.

Critical anthropomorphism and animal ethics

Anthropomorphism has long been considered a cardinal error when describing animals. Ethicists have feared the consequences of misrepresenting animals in their reasoning. Recent research within human-animal studies, however, has sophisticated the notion of anthropomorphism. It is suggested that avoiding anthropomorphism merely creates other morphisms, such as mechanomorphism. Instead of avoiding anthropomorphism, it is argued that it is a communicative strategy that should be used critically. Instances of anthropomorphism in animal ethics are analyzed in this paper. Some analogies made between people and non-human animals in present theories of animal ethics are clear instances of psychological anthropomorphism. Other analogies are implicit cases of cultural anthropomorphism. It is argued that animal ethics needs to take the wider discourse of critical anthropomorphism into account in order to sophisticate the understanding and use of anthropomorphic projections. Anthropomorphism is an efficient tool of communication, and it may be made an adequate one as well.

Understanding virtue ethics

After presenting a broad overview of the history of virtue ethics, this work explores virtues in the context of contemporary moral theory to analyse how many intractable moral dilemmas might be overcome by responsible, virtuous agents.