69 research outputs found

    TEDA: A Targeted Estimation of Distribution Algorithm

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    This thesis discusses the development and performance of a novel evolutionary algorithm, the Targeted Estimation of Distribution Algorithm (TEDA). TEDA takes the concept of targeting, an idea that has previously been shown to be effective as part of a Genetic Algorithm (GA) called Fitness Directed Crossover (FDC), and introduces it into a novel hybrid algorithm that transitions from a GA to an Estimation of Distribution Algorithm (EDA). Targeting is a process for solving optimisation problems where there is a concept of control points, genes that can be said to be active, and where the total number of control points found within a solution is as important as where they are located. When generating a new solution an algorithm that uses targeting must first of all choose the number of control points to set in the new solution before choosing which to set. The hybrid approach is designed to take advantage of the ability of EDAs to exploit patterns within the population to effectively locate the global optimum while avoiding the tendency of EDAs to prematurely converge. This is achieved by initially using a GA to effectively explore the search space before transitioning into an EDA as the population converges on the region of the global optimum. As targeting places an extra restriction on the solutions produced by specifying their size, combining it with the hybrid approach allows TEDA to produce solutions that are of an optimal size and of a higher quality than would be found using a GA alone without risking a loss of diversity. TEDA is tested on three different problem domains. These are optimal control of cancer chemotherapy, network routing and Feature Subset Selection (FSS). Of these problems, TEDA showed consistent advantage over standard EAs in the routing problem and demonstrated that it is able to find good solutions faster than untargeted EAs and non evolutionary approaches at the FSS problem. It did not demonstrate any advantage over other approaches when applied to chemotherapy. The FSS domain demonstrated that in large and noisy problems TEDA’s targeting derived ability to reduce the size of the search space significantly increased the speed with which good solutions could be found. The routing domain demonstrated that, where the ideal number of control points is deceptive, both targeting and the exploitative capabilities of an EDA are needed, making TEDA a more effective approach than both untargeted approaches and FDC. Additionally, in none of the problems was TEDA seen to perform significantly worse than any alternative approaches

    Influenza Virus Ribonucleoprotein Complexes Gain Preferential Access to Cellular Export Machinery through Chromatin Targeting

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    In contrast to most RNA viruses, influenza viruses replicate their genome in the nucleus of infected cells. As a result, newly-synthesized vRNA genomes, in the form of viral ribonucleoprotein complexes (vRNPs), must be exported to the cytoplasm for productive infection. To characterize the composition of vRNP export complexes and their interplay with the nucleus of infected cells, we affinity-purified tagged vRNPs from biochemically fractionated infected nuclei. After treatment of infected cells with leptomycin B, a potent inhibitor of Crm1-mediated export, we isolated vRNP export complexes which, unexpectedly, were tethered to the host-cell chromatin with very high affinity. At late time points of infection, the cellular export receptor Crm1 also accumulated at the same regions of the chromatin as vRNPs, which led to a decrease in the export of other nuclear Crm1 substrates from the nucleus. Interestingly, chromatin targeting of vRNP export complexes brought them into association with Rcc1, the Ran guanine exchange factor responsible for generating RanGTP and driving Crm1-dependent nuclear export. Thus, influenza viruses gain preferential access to newly-generated host cell export machinery by targeting vRNP export complexes at the sites of Ran regeneration

    The heterogeneity of wooded-agricultural landscape mosaics influences woodland bird community assemblages

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    Context Landscape heterogeneity (the composition and configuration of different landcover types) plays a key role in shaping woodland bird assemblages in wooded-agricultural mosaics. Understanding how species respond to landscape factors could contribute to preventing further decline of woodland bird populations. Objective To investigate how woodland birds with different species traits respond to landscape heterogeneity, and to identify whether specific landcover types are important for maintaining diverse populations in wooded-agricultural environments. Methods Birds were sampled from woodlands in 58 2 x 2 km tetrads across southern Britain. Landscape heterogeneity was quantified for each tetrad. Bird assemblage response was determined using redundancy analysis combined with variation partitioning and response trait analyses. Results For woodland bird assemblages, the independent explanatory importance of landscape composition and landscape configuration variables were closely interrelated. When considered simultaneously during variation partitioning, the community response was better represented by compositional variables. Different species responded to different landscape features and this could be explained by traits relating to woodland association, foraging strata and nest location. Ubiquitous, generalist species, many of which were hole-nesters or ground foragers, correlated positively with urban landcover while specialists of broadleaved woodland avoided landscapes containing urban areas. Species typical of coniferous woodland correlated with large conifer plantations. Conclusions At the 2 x 2 km scale, there was evidence that the availability of resources provided by proximate landcover types was highly important for shaping woodland bird assemblages. Further research to disentangle the effects of composition and configuration at different spatial scales is advocated

    Identification of a PA-Binding Peptide with Inhibitory Activity against Influenza A and B Virus Replication

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    There is an urgent need for new drugs against influenza type A and B viruses due to incomplete protection by vaccines and the emergence of resistance to current antivirals. The influenza virus polymerase complex, consisting of the PB1, PB2 and PA subunits, represents a promising target for the development of new drugs. We have previously demonstrated the feasibility of targeting the protein-protein interaction domain between the PB1 and PA subunits of the polymerase complex of influenza A virus using a small peptide derived from the PA-binding domain of PB1. However, this influenza A virus-derived peptide did not affect influenza B virus polymerase activity. Here we report that the PA-binding domain of the polymerase subunit PB1 of influenza A and B viruses is highly conserved and that mutual amino acid exchange shows that they cannot be functionally exchanged with each other. Based on phylogenetic analysis and a novel biochemical ELISA-based screening approach, we were able to identify an influenza A-derived peptide with a single influenza B-specific amino acid substitution which efficiently binds to PA of both virus types. This dual-binding peptide blocked the viral polymerase activity and growth of both virus types. Our findings provide proof of principle that protein-protein interaction inhibitors can be generated against influenza A and B viruses. Furthermore, this dual-binding peptide, combined with our novel screening method, is a promising platform to identify new antiviral lead compounds

    The first myriapod genome sequence reveals conservative arthropod gene content and genome organisation in the centipede Strigamia maritima.

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    Myriapods (e.g., centipedes and millipedes) display a simple homonomous body plan relative to other arthropods. All members of the class are terrestrial, but they attained terrestriality independently of insects. Myriapoda is the only arthropod class not represented by a sequenced genome. We present an analysis of the genome of the centipede Strigamia maritima. It retains a compact genome that has undergone less gene loss and shuffling than previously sequenced arthropods, and many orthologues of genes conserved from the bilaterian ancestor that have been lost in insects. Our analysis locates many genes in conserved macro-synteny contexts, and many small-scale examples of gene clustering. We describe several examples where S. maritima shows different solutions from insects to similar problems. The insect olfactory receptor gene family is absent from S. maritima, and olfaction in air is likely effected by expansion of other receptor gene families. For some genes S. maritima has evolved paralogues to generate coding sequence diversity, where insects use alternate splicing. This is most striking for the Dscam gene, which in Drosophila generates more than 100,000 alternate splice forms, but in S. maritima is encoded by over 100 paralogues. We see an intriguing linkage between the absence of any known photosensory proteins in a blind organism and the additional absence of canonical circadian clock genes. The phylogenetic position of myriapods allows us to identify where in arthropod phylogeny several particular molecular mechanisms and traits emerged. For example, we conclude that juvenile hormone signalling evolved with the emergence of the exoskeleton in the arthropods and that RR-1 containing cuticle proteins evolved in the lineage leading to Mandibulata. We also identify when various gene expansions and losses occurred. The genome of S. maritima offers us a unique glimpse into the ancestral arthropod genome, while also displaying many adaptations to its specific life history.This work was supported by the following grants: NHGRIU54HG003273 to R.A.G; EU Marie Curie ITN #215781 “Evonet” to M.A.; a Wellcome Trust Value in People (VIP) award to C.B. and Wellcome Trust graduate studentship WT089615MA to J.E.G; Marine rhythms of Life” of the University of Vienna, an FWF (http://www.fwf.ac.at/) START award (#AY0041321) and HFSP (http://www.hfsp.org/) research grant (#RGY0082/2010) to KT-­‐R; MFPL Vienna International PostDoctoral Program for Molecular Life Sciences (funded by Austrian Ministry of Science and Research and City of Vienna, Cultural Department -­‐Science and Research to T.K; Direct Grant (4053034) of the Chinese University of Hong Kong to J.H.L.H.; NHGRI HG004164 to G.M.; Danish Research Agency (FNU), Carlsberg Foundation, and Lundbeck Foundation to C.J.P.G.; U.S. National Institutes of Health R01AI55624 to J.H.W.; Royal Society University Research fellowship to F.M.J.; P.D.E. was supported by the BBSRC via the Babraham Institute;This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pbio.100200

    Genome-wide analyses as part of the international FTLD-TDP whole-genome sequencing consortium reveals novel disease risk factors and increases support for immune dysfunction in FTLD

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    Frontotemporal lobar degeneration with neuronal inclusions of the TAR DNA-binding protein 43 (FTLD-TDP) represents the most common pathological subtype of FTLD. We established the international FTLD-TDP whole genome sequencing consortium to thoroughly characterize the known genetic causes of FTLD-TDP and identify novel genetic risk factors. Through the study of 1,131 unrelated Caucasian patients, we estimated that C9orf72 repeat expansions and GRN loss-of-function mutations account for 25.5% and 13.9% of FTLD-TDP patients, respectively. Mutations in TBK1 (1.5%) and other known FTLD genes (1.4%) were rare, and the disease in 57.7% of FTLD-TDP patients was unexplained by the known FTLD genes. To unravel the contribution of common genetic factors to the FTLD-TDP etiology in these patients, we conducted a two-stage association study comprising the analysis of whole-genome sequencing data from 517 FTLD-TDP patients and 838 controls, followed by targeted genotyping of the most associated genomic loci in 119 additional FTLD-TDP patients and 1653 controls. We identified three genome-wide significant FTLD-TDP risk loci: one new locus at chromosome 7q36 within the DPP6 gene led by rs118113626 (pvalue=4.82e-08, OR=2.12), and two known loci: UNC13A, led by rs1297319 (pvalue=1.27e-08, OR=1.50) and HLA-DQA2 led by rs17219281 (pvalue=3.22e-08, OR=1.98). While HLA represents a locus previously implicated in clinical FTLD and related neurodegenerative disorders, the association signal in our study is independent from previously reported associations. Through inspection of our whole genome sequence data for genes with an excess of rare loss-of-function variants in FTLD-TDP patients (n≥3) as compared to controls (n=0), we further discovered a possible role for genes functioning within the TBK1-related immune pathway (e.g. DHX58, TRIM21, IRF7) in the genetic etiology of FTLD-TDP. Together, our study based on the largest cohort of unrelated FTLD-TDP patients assembled to date provides a comprehensive view of the genetic landscape of FTLD-TDP, nominates novel FTLD-TDP risk loci, and strongly implicates the immune pathway in FTLD-TDP pathogenesis

    The United States COVID-19 Forecast Hub dataset

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    Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

    In defence of generalized Darwinism

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    The original publication is available at: www.springerlink.com Copyright SpringerDarwin himself suggested the idea of generalizing the core Darwinian principles to cover the evolution of social entities. Also in the nineteenth century, influential social scientists proposed their extension to political society and economic institutions. Nevertheless, misunderstanding and misrepresentation have hindered the realization of the powerful potential in this longstanding idea. Some critics confuse generalization with analogy. Others mistakenly presume that generalizing Darwinism necessarily involves biological reductionism. This essay outlines the types of phenomena to which a generalized Darwinism applies, and upholds that there is no reason to exclude social or economic entities. © 2008 Springer-Verlag.Peer reviewe
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