Computational Models for Prediction of Yeast Strain Potential for Winemaking from Phenotypic Profiles

Saccharomyces cerevisiae strains from diverse natural habitats harbour a vast amount of phenotypic diversity, driven by interactions between yeast and the respective environment. In grape juice fermentations, strains are exposed to a wide array of biotic and abiotic stressors, which may lead to strain selection and generate naturally arising strain diversity. Certain phenotypes are of particular interest for the winemaking industry and could be identified by screening of large number of different strains. The objective of the present work was to use data mining approaches to identify those phenotypic tests that are most useful to predict a strain's potential for winemaking. We have constituted a S. cerevisiae collection comprising 172 strains of worldwide geographical origins or technological applications. Their phenotype was screened by considering 30 physiological traits that are important from an oenological point of view. Growth in the presence of potassium bisulphite, growth at 40 degrees C, and resistance to ethanol were mostly contributing to strain variability, as shown by the principal component analysis. In the hierarchical clustering of phenotypic profiles the strains isolated from the same wines and vineyards were scattered throughout all clusters, whereas commercial winemaking strains tended to co-cluster. Mann-Whitney test revealed significant associations between phenotypic results and strain's technological application or origin. Naive Bayesian classifier identified 3 of the 30 phenotypic tests of growth in iprodion (0.05 mg/mL), cycloheximide (0.1 mu g/mL) and potassium bisulphite (150 mg/mL) that provided most information for the assignment of a strain to the group of commercial strains. The probability of a strain to be assigned to this group was 27% using the entire phenotypic profile and increased to 95%, when only results from the three tests were considered. Results show the usefulness of computational approaches to simplify strain selection procedures.Ines Mendes and Ricardo Franco-Duarte are recipients of a fellowship from the Portuguese Science Foundation, FCT (SFRH/BD/74798/2010, SFRH/BD/48591/2008, respectively) and Joao Drumonde-Neves is recipient of a fellowship from the Azores government (M3.1.2/F/006/2008 (DRCT)). Financial support was obtained from FEDER funds through the program COMPETE and by national funds through FCT by the projects FCOMP-01-0124-008775 (PTDC/AGR-ALI/103392/2008) and PTDC/AGR-ALI/121062/2010. Lan Umek and Blaz Zupan acknowledge financial support from Slovene Research Agency (P2-0209). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

Unsupervised assessment of microarray data quality using a Gaussian mixture model

<p>Abstract</p> <p>Background</p> <p>Quality assessment of microarray data is an important and often challenging aspect of gene expression analysis. This task frequently involves the examination of a variety of summary statistics and diagnostic plots. The interpretation of these diagnostics is often subjective, and generally requires careful expert scrutiny.</p> <p>Results</p> <p>We show how an unsupervised classification technique based on the Expectation-Maximization (EM) algorithm and the naïve Bayes model can be used to automate microarray quality assessment. The method is flexible and can be easily adapted to accommodate alternate quality statistics and platforms. We evaluate our approach using Affymetrix 3' gene expression and exon arrays and compare the performance of this method to a similar supervised approach.</p> <p>Conclusion</p> <p>This research illustrates the efficacy of an unsupervised classification approach for the purpose of automated microarray data quality assessment. Since our approach requires only unannotated training data, it is easy to customize and to keep up-to-date as technology evolves. In contrast to other "black box" classification systems, this method also allows for intuitive explanations.</p

Overcoming concerns in collaborative transactions

Platforms that facilitate the sharing economy promise to help create a circular economy on a peer2peer level. When a consumer is acting as a “prosumer” offering goods or services to a peer, the other party may not profit from consumer protection. This negative consequence of a possible positive development is an incentive for the legislator to start regulating platform activities. This article translates the concerns to a positive platform policy instead

Management through spiritual self-help discourse in post-socialist Slovenia

From the 1990s, during and after the post-communist transitions in Eastern Europe, different self-help texts advancing spiritual or personal well-being continue to be a highly popular discourse in Slovenia. In this article we examine the appropriation of self-help discourse in one of Slovenia's most influential management magazines, Manager. On the basis of a critical discourse analysis of Manager's articles, we argue that the magazine predominantly uses spiritual self-help vocabulary and accordingly transforms definitions of basic business vocabulary. It offers a spiritual self-growth discourse as a solution to any current management or social problems and in doing so supports the (neo)liberal capitalism. This discourse attempts to advise managers as to how to adapt to the new competitive business environment. It furthermore promotes the belief that solely spiritual self-growth will help managers and their business partners to resist political and economic barriers and assure the business success in times of global corporate `survival'

Agaritine content of 53 Agaricus species collected from nature

International audienceAbstract Fifty-three different species of the genus Agaricus were collected in the Czech Republic during the period 1998-2001 and identified by an experienced mycologist. The samples were analysed for agaritine (N2-(Γ-L-glutamyl)-4-hydroxymethylphenyl¬hydrazine) content, a precursor to a suspected rodent carcinogen. There was a huge variation in agaritine content between species, less variation between samples of a species. Whereas the cultivated mushroom Agaricus bisporus commonly contain 200-500 mg agaritine/kg fresh weight, no less than 24 of the 53 species contained agaritine levels above 1000 mg/kg fresh weight. The highest level was found in A. elvensis containing up to 10,000 mg/kg fresh weight. Seventeen species contained intermediate levels (125-1000 mg/kg), and twelve species below 125 mg/kg. Some of the species producing low levels of agaritine might be candidates for future strain-development of Agaricus mushrooms for cultivation. No correlation could be observed between the agaritine content and size of the mushroom, week of the year when collected, year of collection, or site of collection. Besides occurring in the genus Agaricus, some species of the genera Leucoagaricus and Macrolepiota were also shown to contain agaritine