Cophylogeny reconstruction via an approximate bayesian computation

Despite an increasingly vast literature on cophylogenetic reconstructions for studying host-parasite associations, understanding the common evolutionary history of such systems remains a problem that is far from being solved. Most algorithms for host-parasite reconciliation use an event-based model, where the events include in general (a subset of) cospeciation, duplication, loss, and host switch. All known parsimonious event-based methods then assign a cost to each type of event in order to find a reconstruction of minimum cost. The main problem with this approach is that the cost of the events strongly influences the reconciliation obtained. Some earlier approaches attempt to avoid this problem by finding a Pareto set of solutions and hence by considering event costs under some minimization constraints. To deal with this problem, we developed an algorithm, called Coala, for estimating the frequency of the events based on an approximate Bayesian computation approach. The benefits of this method are 2-fold: (i) it provides more confidence in the set of costs to be used in a reconciliation, and (ii) it allows estimation of the frequency of the events in cases where the data set consists of trees with a large number of taxa. We evaluate our method on simulated and on biological data sets. We show that in both cases, for the same pair of host and parasite trees, different sets of frequencies for the events lead to equally probable solutions. Moreover, often these solutions differ greatly in terms of the number of inferred events. It appears crucial to take this into account before attempting any further biological interpretation of such reconciliations. More generally, we also show that the set of frequencies can vary widely depending on the input host and parasite trees. Indiscriminately applying a standard vector of costs may thus not be a good strategy

Cassis: detection of genomic rearrangement breakpoints

Summary: Genomes undergo large structural changes that alter their organization. The chromosomal regions affected by these rearrangements are called breakpoints, while those which have not been rearranged are called synteny blocks. Lemaitre et al. presented a new method to precisely delimit rearrangement breakpoints in a genome by comparison with the genome of a related species. Receiving as input a list of one2one orthologous genes found in the genomes of two species, the method builds a set of reliable and non-overlapping synteny blocks and refines the regions that are not contained into them. Through the alignment of each breakpoint sequence against its specific orthologous sequences in the other species, we can look for weak similarities inside the breakpoint, thus extending the synteny blocks and narrowing the breakpoints. The identification of the narrowed breakpoints relies on a segmentation algorithm and is statistically assessed. Here, we present the package Cassis that implements this method of precise detection of genomic rearrangement breakpoints

ASSET : a dataset for tuning and evaluation of sentence simplification models with multiple rewriting transformations

In order to simplify a sentence, human editors perform multiple rewriting transformations: they split it into several shorter sentences, paraphrase words (i.e. replacing complex words or phrases by simpler synonyms), reorder components, and/or delete information deemed unnecessary. Despite these varied range of possible text alterations, current models for automatic sentence simplification are evaluated using datasets that are focused on a single transformation, such as lexical paraphrasing or splitting. This makes it impossible to understand the ability of simplification models in more realistic settings. To alleviate this limitation, this paper introduces ASSET, a new dataset for assessing sentence simplification in English. ASSET is a crowdsourced multi-reference corpus where each simplification was produced by executing several rewriting transformations. Through quantitative and qualitative experiments, we show that simplifications in ASSET are better at capturing characteristics of simplicity when compared to other standard evaluation datasets for the task. Furthermore, we motivate the need for developing better methods for automatic evaluation using ASSET, since we show that current popular metrics may not be suitable when multiple simplification transformations are performed

From global to local creative dynamics: the location patterns of art galleries

The aim of this chapter is to analyze art galleries’ locational patterns. We successively investigate regional, city and district scales. Firstly, we show that art galleries are concentrated  within historical centers of the art market in Western Europe and North America. Nevertheless, we highlight the emergence of gallery polarities in new art market areas in Asia or Latin America. Secondly, within these regions, galleries are concentrated in a few cities such as New York, London, Paris, Berlin, Zurich, Hong Kong and Shanghai. Thirdly, in each of these cities, most galleries are located in a few districts, either in affluent inner-city neighborhoods or in semi-peripheral areas subject to urban transformations. We assume that these location patterns can be explained through various agglomeration forces such as wealth, urban and cultural assets, and connectivity. But the formation of art gallery districts also results from the collective endeavour of art world actors’ to differentiate from the already established art districts, and from the strategies of private or public urban developers to enhance land value

NTRFinder: a software tool to find nested tandem repeats

We introduce the software tool NTRFinder to search for a complex repetitive structure in DNA we call a nested tandem repeat (NTR). An NTR is a recurrence of two or more distinct tandem motifs interspersed with each other. We propose that NTRs can be used as phylogenetic and population markers. We have tested our algorithm on both real and simulated data, and present some real NTRs of interest. NTRFinder can be downloaded from http://www.maths.otago.ac.nz/~aamatroud/

Genius loci reloaded, The creative renaissance of Nantes and Saint Etienne

Since the middle of the 1990s, the creative city concept has gradually interfered with debates related to the governance and development of urban areas in France. This interference has occurred through a discourse which seeks to praise the territorial virtues of culture. This concept emerged in Anglo-Saxon countries and has since seduced numerous local decision-makers in France. Culture is thus central to city strategies, and is seen as a resource which is mobilised and used in political, economic or touristic projects. This new trend has benefit from the increasing power of cities in terms of public policy implementation, but also from the « post industrialisation » of urban economies, in which culture is part of territorial showcasing. Undoubtedly, Paris has always been considered to be one of the most creative cities in the world, in cultural as in touristic terms. The city, number one tourist spot in Europe, and equipped with one of the best museums of the world is considered to be a creative city par excellence. However, other cities in France, such as Lyon, Lille, Nantes, St Etienne, Nice or Marseille are worthwhile to explore when it comes to illustrate the French attitudes towards the creative city paradigm. Two of these cities, St Etienne and Nantes are taken as examples in this paper because of their earlier strategies to promote their creative soul as an urban development tool