Relative hermitian morita theory. Part II : Hermitian Morita contexts

We introduce the notion of a relative hermitian Morita context between torsion triples and show how these induce equivalences between suitable quotient categories of left and right modules. Due to the lack of involutive bimodules, the induced Morita equivalences are not necessarily hermitian, however

Relative derived functors

AbstractThe Gabriel-Popescu Theorem states essentially that every Grothendieck category is (up to equivalence) of the form (R,σ)-mod, i.e., the quotient category of some left module category R-mod, by some Serre subcategory Tσ associated to an idempotent kernel functor σ. It follows that every Grothendieck category is a Giraud suncategory of a left module category.In this paper, we study the relationship between derived functors in a Grothendieck category C and a Giraud subcategory D. With C=R-mod, the foregoing thus yields methods to study derived functors in arbitrary Grothendieck categories from knowledge about derived functors in R-mod

Flexible network reconstruction from relational databases with Cytoscape and CytoSQL

<p>Abstract</p> <p>Background</p> <p>Molecular interaction networks can be efficiently studied using network visualization software such as Cytoscape. The relevant nodes, edges and their attributes can be imported in Cytoscape in various file formats, or directly from external databases through specialized third party plugins. However, molecular data are often stored in relational databases with their own specific structure, for which dedicated plugins do not exist. Therefore, a more generic solution is presented.</p> <p>Results</p> <p>A new Cytoscape plugin 'CytoSQL' is developed to connect Cytoscape to any relational database. It allows to launch SQL ('Structured Query Language') queries from within Cytoscape, with the option to inject node or edge features of an existing network as SQL arguments, and to convert the retrieved data to Cytoscape network components. Supported by a set of case studies we demonstrate the flexibility and the power of the CytoSQL plugin in converting specific data subsets into meaningful network representations.</p> <p>Conclusions</p> <p>CytoSQL offers a unified approach to let Cytoscape interact with relational databases. Thanks to the power of the SQL syntax, this tool can rapidly generate and enrich networks according to very complex criteria. The plugin is available at <url>http://www.ptools.ua.ac.be/CytoSQL</url>.</p

Mapping of Submerged Aquatic Vegetation in Rivers From Very High Resolution Image Data, Using Object Based Image Analysis Combined with Expert Knowledge

The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy

An integrated workflow for robust alignment and simplified quantitative analysis of NMR spectrometry data

<p>Abstract</p> <p>Background</p> <p>Nuclear magnetic resonance spectroscopy (NMR) is a powerful technique to reveal and compare quantitative metabolic profiles of biological tissues. However, chemical and physical sample variations make the analysis of the data challenging, and typically require the application of a number of preprocessing steps prior to data interpretation. For example, noise reduction, normalization, baseline correction, peak picking, spectrum alignment and statistical analysis are indispensable components in any NMR analysis pipeline.</p> <p>Results</p> <p>We introduce a novel suite of informatics tools for the quantitative analysis of NMR metabolomic profile data. The core of the processing cascade is a novel peak alignment algorithm, called hierarchical Cluster-based Peak Alignment (CluPA). The algorithm aligns a target spectrum to the reference spectrum in a top-down fashion by building a hierarchical cluster tree from peak lists of reference and target spectra and then dividing the spectra into smaller segments based on the most distant clusters of the tree. To reduce the computational time to estimate the spectral misalignment, the method makes use of Fast Fourier Transformation (FFT) cross-correlation. Since the method returns a high-quality alignment, we can propose a simple methodology to study the variability of the NMR spectra. For each aligned NMR data point the ratio of the between-group and within-group sum of squares (BW-ratio) is calculated to quantify the difference in variability between and within predefined groups of NMR spectra. This differential analysis is related to the calculation of the F-statistic or a one-way ANOVA, but without distributional assumptions. Statistical inference based on the BW-ratio is achieved by bootstrapping the null distribution from the experimental data.</p> <p>Conclusions</p> <p>The workflow performance was evaluated using a previously published dataset. Correlation maps, spectral and grey scale plots show clear improvements in comparison to other methods, and the down-to-earth quantitative analysis works well for the CluPA-aligned spectra. The whole workflow is embedded into a modular and statistically sound framework that is implemented as an R package called "speaq" ("spectrum alignment and quantitation"), which is freely available from <url>http://code.google.com/p/speaq/</url>.</p

Plants in aquatic ecosystems: current trends and future directions

Aquatic plants fulfil a wide range of ecological roles, and make a substantial contribution to the structure, function and service provision of aquatic ecosystems. Given their well-documented importance in aquatic ecosystems, research into aquatic plants continues to blossom. The 14th International Symposium on Aquatic Plants, held in Edinburgh in September 2015, brought together 120 delegates from 28 countries and six continents. This special issue of Hydrobiologia includes a select number of papers on aspects of aquatic plants, covering a wide range of species, systems and issues. In this paper we present an overview of current trends and future directions in aquatic plant research in the early 21st century. Our understanding of aquatic plant biology, the range of scientific issues being addressed and the range of techniques available to researchers have all arguably never been greater; however, substantial challenges exist to the conservation and management of both aquatic plants and the ecosystems in which they are found. The range of countries and continents represented by conference delegates and authors of papers in the special issue illustrate the global relevance of aquatic plant research in the early 21st century but also the many challenges that this burgeoning scientific discipline must address