Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.

Causality detection on US mutual fund movements using evolutionary subset time-series

In this paper we develop an evolutionary kernel-based time update algorithm to recursively estimate subset discrete lag models (including fullorder models) with a forgetting factor and a constant term, using the exactwindowed case. The algorithm applies to causality detection when the true relationship occurs with a continuous or a random delay. We then demonstrate the use of the proposed evolutionary algorithm to study the monthly mutual fund data, which come from the 'CRSP Survivor-bias free US Mutual Fund Database'. The results show that the NAV is an influential player on the international stage of global bond and stock markets.

Optimising profitability and environmental trade-offs in managing cropping systems using differential evolution

Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.

A consistent point-searching algorithm for solution interpolation in unstructured meshes consisting of 4-node bilinear quadrilateral elements

To translate and transfer solution data between two totally different meshes (i.e. mesh 1 and mesh 2), a consistent point-searching algorithm for solution interpolation in unstructured meshes consisting of 4-node bilinear quadrilateral elements is presented in this paper. The proposed algorithm has the following significant advantages: (1) The use of a point-searching strategy allows a point in one mesh to be accurately related to an element (containing this point) in another mesh. Thus, to translate/transfer the solution of any particular point from mesh 2 td mesh 1, only one element in mesh 2 needs to be inversely mapped. This certainly minimizes the number of elements, to which the inverse mapping is applied. In this regard, the present algorithm is very effective and efficient. (2) Analytical solutions to the local co ordinates of any point in a four-node quadrilateral element, which are derived in a rigorous mathematical manner in the context of this paper, make it possible to carry out an inverse mapping process very effectively and efficiently. (3) The use of consistent interpolation enables the interpolated solution to be compatible with an original solution and, therefore guarantees the interpolated solution of extremely high accuracy. After the mathematical formulations of the algorithm are presented, the algorithm is tested and validated through a challenging problem. The related results from the test problem have demonstrated the generality, accuracy, effectiveness, efficiency and robustness of the proposed consistent point-searching algorithm. Copyright (C) 1999 John Wiley & Sons, Ltd.

Searching oligo sets of human chromosome 12 using evolutionary strategies

DNA Microarray is a powerful tool to measure the level of a mixed population of nucleic acids at one time, which has great impact in many aspects of life sciences research. In order to distinguish nucleic acids with very similar composition by hybridization, it is necessary to design microarray probes with high specificities and sensitivities. Highly specific probes correspond to probes having unique DNA sequences; whereas highly sensitive probes correspond to those with melting temperature within a desired range and having no secondary structure. The selection of these probes from a set of functional DNA sequences (exons) constitutes a computationally expensive discrete non-linear search problem. We delegate the search task to a simple yet effective Evolution Strategy algorithm. The computational efficiency is also greatly improved by making use of an available bioinformatics tool.

Diverse members of the Ralstonia solanacearum species complex cause bacterial wilts of banana

The bacterial wilts of banana known as Moko disease, Bugtok disease and blood disease are caused by members of the R. solanacearum species complex. R. solanacearum is a heterogeneous species which has been divided into 4 genetic groups known as phylotypes. Within the R. solanacearum species complex, strains that cause Moko and Bugtok diseases belong to phylotype II. The blood disease bacterium, the cause of blood disease, belongs to phylotype IV. This study employs phylogenetic analysis of partial endoglucanase gene sequences to further assess the evolutionary relationships between strains of R. solanacearum causing Moko disease and Bugtok disease and the relationship of the blood disease bacterium to other R. solanacearum strains within phylotype IV of the R. solanacearum species complex. These analyses showed that R. solanacearum Moko disease-causing strains are polyphyletic, forming four related, but distinct, clusters of strains. One of these clusters is a previously unrecognised group of R. solanacearum Moko disease-causing strains. It was also found that R. solanacearum strains that cause Bugtok disease are indistinguishable from strains causing Moko disease in the Philippines. Phylogenetic analysis of partial endoglucanase gene sequences of the strains of the blood disease confirms a close relationship of these strains to R. solanacearum strains within phylotype IV of the R. solanacearum species complex.

The interaction between technologies and society: Lessons learnt from 160 evolutionary years of online news services

In mapping the evolutionary process of online news and the socio-cultural factors determining this development, this paper has a dual purpose. First, in reworking the definition of “online communication”, it argues that despite its seemingly sudden emergence in the 1990s, the history of online news started right in the early days of the telegraphs and spread throughout the development of the telephone and the fax machine before becoming computer-based in the 1980s and Web-based in the 1990s. Second, merging macro-perspectives on the dynamic of media evolution by DeFleur and Ball-Rokeach (1989) and Winston (1998), the paper consolidates a critical point for thinking about new media development: that something technically feasible does not always mean that it will be socially accepted and/or demanded. From a producer-centric perspective, the birth and development of pre-Web online news forms have been more or less generated by the traditional media’s sometimes excessive hype about the power of new technologies. However, placing such an emphasis on technological potentials at the expense of their social conditions not only can be misleading but also can be detrimental to the development of new media, including the potential of today’s online news.

Evolution of Wolbachia pipientis transmission dynamics in insects

Wolbachia pipientis is an intracellular bacterial parasite of arthropods that enhances its transmission by manipulating host reproduction, most commonly by inducing cytoplasmic incompatibility. The discovery of isolates with modified cytoplasmic incompatibility phenotypes and others with novel virulence properties is an indication of the potential breadth of evolutionary strategies employed by Wolbachia.

Cloning and characterization of a gene encoding the major surface protein of the bacterial endosymbiont Wolbachia pipientis

The maternally inherited intracellular symbiont Wolbachia pipientis is well known for inducing a variety of reproductive abnormalities in the diverse arthropod hosts it infects. It has been implicated in causing cytoplasmic incompatibility, parthenogenesis, and the feminization of genetic males in different hosts. The molecular mechanisms by which this fastidious intracellular bacterium causes these reproductive and developmental abnormalities have not yet been determined. In this paper, we report on (i) the purification of one of the most abundantly expressed Wolbachia proteins from infected Drosophila eggs and (ii) the subsequent cloning and characterization of the gene (wsp) that encodes it. The functionality of the wsp promoter region was also successfully tested in Escherichia coli. Comparison of sequences of this gene from different strains of Wolbachia revealed a high level of variability. This sequence variation correlated with the ability of certain Wolbachia strains to induce or rescue the cytoplasmic incompatibility phenotype in infected insects. As such, this gene will be a very useful tool for Wolbachia strain typing and phylogenetic analysis, as well as understanding the molecular basis of the interaction of Wolbachia with its host.

Wolbachia pipientis: bacterial density and unidirectional cytoplasmic incompatibility between infected populations of Aedes albopictus

Unidirectional cytoplasmic incompatibility is seen when certain Wolbachia-infected insect populations are crossed. Two hypotheses might explain this phenomenon: superinfections with mutually incompatible strains of Wolbachia producing incompatibility when crossed to individuals infected with only a single bacterial strain or, alternatively, a bacterial dosage model, with differences in Wolbachia densities responsible for the incompatibility. A quantitative PCR assay was set up as a general method to compare Wolbachia densities between populations. Using this assay in unidirectionally incompatible stocks of the mosquito Aedes albopictus, we have determined that densities are significantly higher in Houston than in the Mauritius and Koh Samui stocks. This is consistent with a dosage model for the observed crossing patterns, but does not rule out the possibility that superinfection is the primary cause of the incompatibility.

16S rRNA phylogenetic analysis of the bacterial endosymbionts associated with cytoplasmic incompatibility in insects

Bacterial endosymbionts of insects have long been implicated in the phenomenon of cytoplasmic incompatibility, in which certain crosses between symbiont-infected individuals lead to embryonic death or sex ratio distortion. The taxonomic position of these bacteria has, however, not been known with any certainty. Similarly, the relatedness of the bacteria infecting various insect hosts has been unclear. The inability to grow these bacteria on defined cell-free medium has been the major factor underlying these uncertainties. We circumvented this problem by selective PCR amplification and subsequent sequencing of the symbiont 16S rRNA genes directly from infected insect tissue. Maximum parsimony analysis of these sequences indicates that the symbionts belong in the α-subdivision of the Proteobacteria, where they are most closely related to the Rickettsia and their relatives. They are all closely related to each other and are assigned to the type species Wolbachia pipientis. Lack of congruence between the phylogeny of the symbionts and their insect hosts suggests that horizontal transfer of symbionts between insect species may occur. Comparison of the sequences for W. pipientis and for Wolbachia persica, an endosymbiont of ticks, shows that the genus Wolbachia is polyphyletic. A PCR assay based on 16S primers was designed for the detection of W. pipientis in insect tissue, and initial screening of insects indicates that cytoplasmic incompatibility may be a more general phenomenon in insects than is currently recognized.