Generalisation and Model Selection in Supervised Learning with Evolutionary Computation

Rowland, J. J. (2003) Generalisation and Model Selection in Supervised Learning with Evolutionary Computation. European Workshop on Evolutionary Computation in Bioinformatics: EvoBio 2003. Lecture Notes in Computer Science (Springer), Vol 2611, pp 119-130

Barnacle cement: a polymerization model based on evolutionary concepts.

Enzymes and biochemical mechanisms essential to survival are under extreme selective pressure and are highly conserved through evolutionary time. We applied this evolutionary concept to barnacle cement polymerization, a process critical to barnacle fitness that involves aggregation and cross-linking of proteins. The biochemical mechanisms of cement polymerization remain largely unknown. We hypothesized that this process is biochemically similar to blood clotting, a critical physiological response that is also based on aggregation and cross-linking of proteins. Like key elements of vertebrate and invertebrate blood clotting, barnacle cement polymerization was shown to involve proteolytic activation of enzymes and structural precursors, transglutaminase cross-linking and assembly of fibrous proteins. Proteolytic activation of structural proteins maximizes the potential for bonding interactions with other proteins and with the surface. Transglutaminase cross-linking reinforces cement integrity. Remarkably, epitopes and sequences homologous to bovine trypsin and human transglutaminase were identified in barnacle cement with tandem mass spectrometry and/or western blotting. Akin to blood clotting, the peptides generated during proteolytic activation functioned as signal molecules, linking a molecular level event (protein aggregation) to a behavioral response (barnacle larval settlement). Our results draw attention to a highly conserved protein polymerization mechanism and shed light on a long-standing biochemical puzzle. We suggest that barnacle cement polymerization is a specialized form of wound healing. The polymerization mechanism common between barnacle cement and blood may be a theme for many marine animal glues.

Eco-evolutionary feedbacks in community and ecosystem ecology: interactions between the ecological theatre and the evolutionary play.

Interactions between natural selection and environmental change are well recognized and sit at the core of ecology and evolutionary biology. Reciprocal interactions between ecology and evolution, eco-evolutionary feedbacks, are less well studied, even though they may be critical for understanding the evolution of biological diversity, the structure of communities and the function of ecosystems. Eco-evolutionary feedbacks require that populations alter their environment (niche construction) and that those changes in the environment feed back to influence the subsequent evolution of the population. There is strong evidence that organisms influence their environment through predation, nutrient excretion and habitat modification, and that populations evolve in response to changes in their environment at time-scales congruent with ecological change (contemporary evolution). Here, we outline how the niche construction and contemporary evolution interact to alter the direction of evolution and the structure and function of communities and ecosystems. We then present five empirical systems that highlight important characteristics of eco-evolutionary feedbacks: rotifer-algae chemostats; alewife-zooplankton interactions in lakes; guppy life-history evolution and nutrient cycling in streams; avian seed predators and plants; and tree leaf chemistry and soil processes. The alewife-zooplankton system provides the most complete evidence for eco-evolutionary feedbacks, but other systems highlight the potential for eco-evolutionary feedbacks in a wide variety of natural systems.

The evolutionary history of ferns inferred from 25 low-copy nuclear genes.

UNLABELLED: • PREMISE OF THE STUDY: Understanding fern (monilophyte) phylogeny and its evolutionary timescale is critical for broad investigations of the evolution of land plants, and for providing the point of comparison necessary for studying the evolution of the fern sister group, seed plants. Molecular phylogenetic investigations have revolutionized our understanding of fern phylogeny, however, to date, these studies have relied almost exclusively on plastid data.• METHODS: Here we take a curated phylogenomics approach to infer the first broad fern phylogeny from multiple nuclear loci, by combining broad taxon sampling (73 ferns and 12 outgroup species) with focused character sampling (25 loci comprising 35877 bp), along with rigorous alignment, orthology inference and model selection.• KEY RESULTS: Our phylogeny corroborates some earlier inferences and provides novel insights; in particular, we find strong support for Equisetales as sister to the rest of ferns, Marattiales as sister to leptosporangiate ferns, and Dennstaedtiaceae as sister to the eupolypods. Our divergence-time analyses reveal that divergences among the extant fern orders all occurred prior to ∼200 MYA. Finally, our species-tree inferences are congruent with analyses of concatenated data, but generally with lower support. Those cases where species-tree support values are higher than expected involve relationships that have been supported by smaller plastid datasets, suggesting that deep coalescence may be reducing support from the concatenated nuclear data.• CONCLUSIONS: Our study demonstrates the utility of a curated phylogenomics approach to inferring fern phylogeny, and highlights the need to consider underlying data characteristics, along with data quantity, in phylogenetic studies.

B-type supergiants in the SMC: Chemical compositions and comparison of static and unified models

High-resolution UCLES/AAT spectra are presented for nine B-type supergiants in the SMC, chosen on the basis that they may show varying amounts of nuclear-synthetically processed material mixed to their surface. These spectra have been analysed using a new grid of approximately 12 000 non-LTE line blanketed tlusty model atmospheres to estimate atmospheric parameters and chemical composition. The abundance estimates for O, Mg and Si are in excellent agreement with those deduced from other studies, whilst the low estimate for C may reflect the use of the C II doublet at 4267 Å. The N estimates are approximately an order of magnitude greater than those found in unevolved B-type stars or H II regions but are consistent with the other estimates in AB-type supergiants. These results have been combined with results from a unified model atmosphere analysis of UVES/VLT spectra of B-type supergiants (Trundle et al. 2004, A&A, 417, 217) to discuss the evolutionary status of these objects. For two stars that are in common with those discussed by Trundle et al., we have undertaken a careful comparison in order to try to understand the relative importance of the different uncertainties present in such analyses, including observational errors and the use of static or unified models. We find that even for these relatively luminous supergiants, tlusty models yield atmospheric parameters and chemical compositions similar to those deduced from the unified code fastwind.

Evolutionary agglomeration theory: increasing returns, diminishing returns, and the industry life cycle

According to Marshall’s agglomeration theory, Krugman’s New Economic Geography models, and Porter’s cluster policies, firms should receive increasing returns from a trinity of agglomeration economies: a local pool of skilled labour, local supplier linkages, and local knowledge spillovers. Recent evolutionary theories suggest that whether agglomeration economies generate increasing returns or diminishing returns depends on time, and especially the evolution of the industry life cycle. At the start of the twenty-first century, we re-examine Marshall’s trinity of agglomeration economies in the city-region where he discovered them. The econometric results from our multivariate regression models are the polar opposite of Marshall’s. During the later stages of the industry life cycle, Marshall’s agglomeration economies decrease the economic performance of firms and create widespread diminishing returns for the economic development of the city-region, which has evolved to become one of the poorest city-regions in Europe.

Limitations of Gene Duplication Models: Evolution of Modules in Protein Interaction Networks

It has been generally acknowledged that the module structure of protein interaction networks plays a crucial role with respect to the functional understanding of these networks. In this paper, we study evolutionary aspects of the module structure of protein interaction networks, which forms a mesoscopic level of description with respect to the architectural principles of networks. The purpose of this paper is to investigate limitations of well known gene duplication models by showing that these models are lacking crucial structural features present in protein interaction networks on a mesoscopic scale. This observation reveals our incomplete understanding of the structural evolution of protein networks on the module level. © 2012 Emmert-Streib.

Evolutionary Requirements for Next-Generation Dataflow-Based FPGA System Design

The use of dataflow digital signal processing system modelling
and synthesis techniques has been a fruitful research theme for many years and has yielded many powerful rapid system synthesis and optimisation capabilities. However, recent years have seen the spectrum of languages and techniques splinter in an application specific manner, resulting in an ad-hoc design process which is increasingly dependent on the particular application under development. This poses a major problem for automated toolflows attempting to provide rapid system synthesis for a wide ranges of applications. By analysing a number of dataflow FPGA implementation case studies, this paper shows that despit ethis common traits may be found in current techniques, which fall largely into three classes. Further, it exposes limitations pertaining to their ability to adapt algorith models to implementations for different operating environments and target platforms.

Pool Evolution: A Parallel Pattern for Evolutionary and Symbolic Computing

We introduce a new parallel pattern derived from a specific application domain and show how it turns out to have application beyond its domain of origin. The pool evolution pattern models the parallel evolution of a population subject to mutations and evolving in such a way that a given fitness function is optimized. The pattern has been demonstrated to be suitable for capturing and modeling the parallel patterns underpinning various evolutionary algorithms, as well as other parallel patterns typical of symbolic computation. In this paper we introduce the pattern, we discuss its implementation on modern multi/many core architectures and finally present experimental results obtained with FastFlow and Erlang implementations to assess its feasibility and scalability.

Molecular pedigree reconstruction and estimation of evolutionary parameters in a wild Atlantic salmon river system with incomplete sampling: a power analysis

Background: Pedigree reconstruction using genetic analysis provides a useful means to estimate fundamental population biology parameters relating to population demography, trait heritability and individual fitness when combined with other sources of data. However, there remain limitations to pedigree reconstruction in wild populations, particularly in systems where parent-offspring relationships cannot be directly observed, there is incomplete sampling of individuals, or molecular parentage inference relies on low quality DNA from archived material. While much can still be inferred from incomplete or sparse pedigrees, it is crucial to evaluate the quality and power of available genetic information a priori to testing specific biological hypotheses. Here, we used microsatellite markers to reconstruct a multi-generation pedigree of wild Atlantic salmon (Salmo salar L.) using archived scale samples collected with a total trapping system within a river over a 10 year period. Using a simulation-based approach, we determined the optimal microsatellite marker number for accurate parentage assignment, and evaluated the power of the resulting partial pedigree to investigate important evolutionary and quantitative genetic characteristics of salmon in the system.

Results: We show that at least 20 microsatellites (ave. 12 alleles/locus) are required to maximise parentage assignment and to improve the power to estimate reproductive success and heritability in this study system. We also show that 1.5 fold differences can be detected between groups simulated to have differing reproductive success, and that it is possible to detect moderate heritability values for continuous traits (h(2) similar to 0.40) with more than 80% power when using 28 moderately to highly polymorphic markers.

Conclusion: The methodologies and work flow described provide a robust approach for evaluating archived samples for pedigree-based research, even where only a proportion of the total population is sampled. The results demonstrate the feasibility of pedigree-based studies to address challenging ecological and evolutionary questions in free-living populations, where genealogies can be traced only using molecular tools, and that significant increases in pedigree assignment power can be achieved by using higher numbers of markers.

Evolutionary diversification in Central Brazil: where Amazonia and Cerrado meet

Apesar da fauna de mamíferos Neotropicais ser uma das mais ricas do mundo, o nosso conhecimento sobre os limites de espécies, distribuições geográficas e relações filogenéticas está ainda agora no seu início. As áreas de transição entre os dois maiores biomas da América do Sul, o Cerrado e a Amazónia, são ainda menos conhecidas. Até ao momento, escassos estudos focaram os pequenos mamíferos destas áreas. Destes estudos, apenas dois apresentam dados taxonómicos e de distribuição geográfica de uma lista de espécies reduzida e, nenhum é focado nos processos evolutivos que conduziram à diversidade destas áreas. O presente trabalho tem como objectivo aumentar o conhecimento básico sobre a diversidade do médio Rio Araguaia, na região central do Brasil, através da amostragem e análise de espécies de pequenos mamíferos, integrando um intenso trabalho de campo, de laboratório e de museu. Desta forma, um total de 22 espécies é registado para o médio Araguaia. De entre estas espécies, descreve-se uma espécie nova de Rhipidomys, regista-se uma espécie não descrita de Thrichomys e uma potencial nova forma de Oligoryzomys, e também se apresenta uma diagnose emendada do obscuro Oecomys cleberi. Para cada espécie, são também descritas as suas características morfológicas e resumem-se os seus aspectos de distribuição geográfica e história natural. Para os quatro géneros acima referidos, são apresentadas as análises filogenéticas que permitem a identificação das espécies. Adicionalmente, os princípios da filogeografia são aplicados para estudar os padrões da distribuição geográfica da diversidade genética de três roedores sigmodontíneos e seis marsupiais didelphídeos. Os resultados obtidos demonstram que o Rio Araguaia forma uma barreira geográfica para espécies especialistas em florestas não-alagáveis; por outro lado, espécies generalistas apresentam partilha de haplótipos em ambas as margens do rio. Argumentamos também que os refúgios florestais e os gradientes poderão ter tido um papel importante para moldar a estrutura genética de populações de pequenos mamíferos no Brasil central. Em suma, os resultados apresentados corroboram a proposição de que a diversidade Neotropical não poderá ser explicada através de um único modelo de especiação e que estes não são mutuamente exclusivos. O entendimento integral dos processos ecológicos e históricos que deram origem à fauna Neotropical, assim como a continuidade de estudos sistemáticos, depende da realização de novas amostragens e consequente enriquecimento dos museus com colecções apropriadas.

The evolutionary history of the CD209 (DC-SIGN) family in humans and non-human primates

The CD209 gene family that encodes C-type lectins in primates includes CD209 (DC-SIGN), CD209L (L-SIGN) and CD209L2. Understanding the evolution of these genes can help understand the duplication events generating this family, the process leading to the repeated neck region and identify protein domains under selective pressure. We compiled sequences from 14 primates representing 40 million years of evolution and from three non-primate mammal species. Phylogenetic analyses used Bayesian inference, and nucleotide substitutional patterns were assessed by codon-based maximum likelihood. Analyses suggest that CD209 genes emerged from a first duplication event in the common ancestor of anthropoids, yielding CD209L2 and an ancestral CD209 gene, which, in turn, duplicated in the common Old World primate ancestor, giving rise to CD209L and CD209. K(A)/K(S) values averaged over the entire tree were 0.43 (CD209), 0.52 (CD209L) and 0.35 (CD209L2), consistent with overall signatures of purifying selection. We also assessed the Toll-like receptor (TLR) gene family, which shares with CD209 genes a common profile of evolutionary constraint. The general feature of purifying selection of CD209 genes, despite an apparent redundancy (gene absence and gene loss), may reflect the need to faithfully recognize a multiplicity of pathogen motifs, commensals and a number of self-antigens

Evolutionary branching in deme-structured populations.

Adaptive dynamics shows that a continuous trait under frequency dependent selection may first converge to a singular point followed by spontaneous transition from a unimodal trait distribution into a bimodal one, which is called "evolutionary branching". Here, we study evolutionary branching in a deme-structured population by constructing a quantitative genetic model for the trait variance dynamics, which allows us to obtain an analytic condition for evolutionary branching. This is first shown to agree with previous conditions for branching expressed in terms of relatedness between interacting individuals within demes and obtained from mutant-resident systems. We then show this branching condition can be markedly simplified when the evolving trait affect fecundity and/or survival, as opposed to affecting population structure, which would occur in the case of the evolution of dispersal. As an application of our model, we evaluate the threshold migration rate below which evolutionary branching cannot occur in a pairwise interaction game. This agrees very well with the individual-based simulation results.

RNA-based gene duplication: mechanistic and evolutionary insights.

Gene copies that stem from the mRNAs of parental source genes have long been viewed as evolutionary dead-ends with little biological relevance. Here we review a range of recent studies that have unveiled a significant number of functional retroposed gene copies in both mammalian and some non-mammalian genomes. These studies have not only revealed previously unknown mechanisms for the emergence of new genes and their functions but have also provided fascinating general insights into molecular and evolutionary processes that have shaped genomes. For example, analyses of chromosomal gene movement patterns via RNA-based gene duplication have shed fresh light on the evolutionary origin and biology of our sex chromosomes.

Evolving graphs: dynamical models, inverse problems and propagation

Applications such as neuroscience, telecommunication, online social networking, transport and retail trading give rise to connectivity patterns that change over time. In this work, we address the resulting need for network models and computational algorithms that deal with dynamic links. We introduce a new class of evolving range-dependent random graphs that gives a tractable framework for modelling and simulation. We develop a spectral algorithm for calibrating a set of edge ranges from a sequence of network snapshots and give a proof of principle illustration on some neuroscience data. We also show how the model can be used computationally and analytically to investigate the scenario where an evolutionary process, such as an epidemic, takes place on an evolving network. This allows us to study the cumulative effect of two distinct types of dynamics.