Knowledge-based gene expression classification via matrix factorization

Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield expression modes (ICA) or metagenes (NMF). These extracted features are considered indicative of underlying regulatory processes. They can as well be applied to the classification of gene expression datasets by grouping samples into different categories for diagnostic purposes or group genes into functional categories for further investigation of related metabolic pathways and regulatory networks. Results: In this study we focus on unsupervised matrix factorization techniques and apply ICA and sparse NMF to microarray datasets. The latter monitor the gene expression levels of human peripheral blood cells during differentiation from monocytes to macrophages. We show that these tools are able to identify relevant signatures in the deduced component matrices and extract informative sets of marker genes from these gene expression profiles. The methods rely on the joint discriminative power of a set of marker genes rather than on single marker genes. With these sets of marker genes, corroborated by leave-one-out or random forest cross-validation, the datasets could easily be classified into related diagnostic categories. The latter correspond to either monocytes versus macrophages or healthy vs Niemann Pick C disease patients.Siemens AG, MunichDFG (Graduate College 638)DAAD (PPP Luso - Alem˜a and PPP Hispano - Alemanas

The sound of waves in the Mutriku wave energy plant

Peer Reviewe

High post-anthesis temperature effects on bread wheat (Triticum aestivum L.) grain transcriptome during early grain-filling

Background: High post-anthesis (p.a) temperatures significantly reduce mature grain weight in wheat and other cereals. However, the mechanisms through which this reduction occurs are not entirely known. It has been suggested that the pericarp may control grain expansion and weight potential, but this interaction has not been investigated under high p.a. temperatures. Disreregulation, caused by high p.a. temperatures, of pericarp-localised genes involved in cell wall expansion may limit the expansion of the endosperm and contribute to a reduction in mature grain size. Here the effect of high p.a. temperature on the transcriptome of the outer-pericarp and endosperm of the wheat grain during early grain-filling was investigated via RNA-Seq and is discussed in the context of grain moisture dynamics during early grain development and of mature grain weight Results: High p.a. temperatures applied from 6-days after anthesis (daa) and until 18daa reduced the ability of the grain to accumulate water, with total grain moisture and percentage moisture content of the grain being significantly reduced from 14daa onwards. High p.a. temperatures applied from 6daa and for a minimum of 4-daysalso significantly reduced mature grain weight. Comparison of our RNA-Seq data from whole grains, with existing data sets from isolated outer-pericarp and endosperm tissues enabled the identification of subsets of genes whose expression was significantly affected by high p.a. temperature and predominantly expressed in either tissue. Hierarchical clustering and gene ontology analysis resulted in the identification of a number of genes implicated in the regulation of cell wall expansion, predominantly expressed in the outer-pericarp and significantly down-regulated under high p.a. temperatures; these included endoglucanase, xyloglucan endotransglycosylases and a β-expansin. An over-representation of genes involved in the ‘cuticle development’ functional pathway expressed in the outer-pericarp and affected by high p.a. temperatures was also observed. Conclusions: High p.a. temperatures induced down regulation of genes involved in the control of pericarp cell wall expansion and occurred concomitantly to a reduction in the potential for grain moisture accumulation, which is the driving force for endosperm cell volume enlargement and an important determinant of final grain sink capacity. This suggests that high p.a. temperatures impairs the coordination of the development of the different grain tissues, resulting in reduced expansion of the maternal layers and therefore, reduce mature grain weight

Detection of drug-drug interactions by modeling interaction profile fingerprints

Drug-drug interactions (DDIs) constitute an important problem in postmarketing pharmacovigilance and in the development of new drugs. The effectiveness or toxicity of a medication could be affected by the co-administration of other drugs that share pharmacokinetic or pharmacodynamic pathways. For this reason, a great effort is being made to develop new methodologies to detect and assess DDIs. In this article, we present a novel method based on drug interaction profile fingerprints (IPFs) with successful application to DDI detection. IPFs were generated based on the DrugBank database, which provided 9,454 well-established DDIs as a primary source of interaction data. The model uses IPFs to measure the similarity of pairs of drugs and generates new putative DDIs from the non-intersecting interactions of a pair. We described as part of our analysis the pharmacological and biological effects associated with the putative interactions; for example, the interaction between haloperidol and dicyclomine can cause increased risk of psychosis and tardive dyskinesia. First, we evaluated the method through hold-out validation and then by using four independent test sets that did not overlap with DrugBank. Precision for the test sets ranged from 0.4–0.5 with more than two fold enrichment factor enhancement. In conclusion, we demonstrated the usefulness of the method in pharmacovigilance as a DDI predictor, and created a dataset of potential DDIs, highlighting the etiology or pharmacological effect of the DDI, and providing an exploratory tool to facilitate decision support in DDI detection and patient safety.This work was supported by grants R01 LM010016 (CF), R01 LM010016-0S1 (CF), R01 LM010016-0S2 (CF), R01 LM008635 (CF), “Plan Galego de Investigación, Innovación e Crece-mento 2011–2015 (I2C)”, European Social Fund (ESF) and Angeles Alvariño program from Xunta de Galicia (Spain)S

GeneSrF and varSelRF: a web-based tool and R package for gene selection and classification using random forest

<p>Abstract</p> <p>Background</p> <p>Microarray data are often used for patient classification and gene selection. An appropriate tool for end users and biomedical researchers should combine user friendliness with statistical rigor, including carefully avoiding selection biases and allowing analysis of multiple solutions, together with access to additional functional information of selected genes. Methodologically, such a tool would be of greater use if it incorporates state-of-the-art computational approaches and makes source code available.</p> <p>Results</p> <p>We have developed GeneSrF, a web-based tool, and varSelRF, an R package, that implement, in the context of patient classification, a validated method for selecting very small sets of genes while preserving classification accuracy. Computation is parallelized, allowing to take advantage of multicore CPUs and clusters of workstations. Output includes bootstrapped estimates of prediction error rate, and assessments of the stability of the solutions. Clickable tables link to additional information for each gene (GO terms, PubMed citations, KEGG pathways), and output can be sent to PaLS for examination of PubMed references, GO terms, KEGG and and Reactome pathways characteristic of sets of genes selected for class prediction. The full source code is available, allowing to extend the software. The web-based application is available from <url>http://genesrf2.bioinfo.cnio.es</url>. All source code is available from Bioinformatics.org or The Launchpad. The R package is also available from CRAN.</p> <p>Conclusion</p> <p>varSelRF and GeneSrF implement a validated method for gene selection including bootstrap estimates of classification error rate. They are valuable tools for applied biomedical researchers, specially for exploratory work with microarray data. Because of the underlying technology used (combination of parallelization with web-based application) they are also of methodological interest to bioinformaticians and biostatisticians.</p

2.3 Postsurgical atrial tachycardias: Report of four cases not due to macro-reentry

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Plantmetabolomics.org: mass spectrometry-based Arabidopsis metabolomics—database and tools update

The PlantMetabolomics (PM) database (http://www.plantmetabolomics.org) contains comprehensive targeted and untargeted mass spectrum metabolomics data for Arabidopsis mutants across a variety of metabolomics platforms. The database allows users to generate hypotheses about the changes in metabolism for mutants with genes of unknown function. Version 2.0 of PlantMetabolomics.org currently contains data for 140 mutant lines along with the morphological data. A web-based data analysis wizard allows researchers to select preprocessing and data-mining procedures to discover differences between mutants. This community resource enables researchers to formulate models of the metabolic network of Arabidopsis and enhances the research community's ability to formulate testable hypotheses concerning gene functions. PM features new web-based tools for data-mining analysis, visualization tools and enhanced cross links to other databases. The database is publicly available. PM aims to provide a hypothesis building platform for the researchers interested in any of the mutant lines or metabolites

CONOCIMIENTO DE ENFERMERÍA EN EL CUIDADO DE PACIENTES DIABÉTICOS ANTES Y DESPUÉS DE UNA INTERVENCIÓN EDUCATIVA.

Introduction: The constantly education of anybody profession, in special the nursery advance with the professionals diferents stamentsneeds a permanent plan of formation. If we set a real commitment with transformation on labor and social practice, as the quality of the attention; this plan cannot be conceived without integrating the institutions of effective performance. Objetive: To compare the degree of Knowledges of the nursing personal of the education Model in Diabetes Mellitus for the health before and after of a educative intervatiun. Material and methods: It is realized comparative research before and after to 25 nurses, them to attend to the educative intervatiun, it was the model capacitation in Diabetes Mellitus of the health education using didactics strategists. That permitted to personal having more participation, of the one hour 30 minutes, each one. The instrument elaborated of an examination structured with question of options multiples and false and true, with a value 70% o the items, and a clinical case of diabetic patient with a value of 30%. Result: The middle of age of the student population was to 38 years, with a DE plus 5.3 about to the degree of Knowledges to the infirmary personal of the education model for the health education before of the educative intervatiun. The 80% was low. After of theintervatiun to winnowen 72% high. With proof of the hypothesis of WILCOXON = with value PO. 05. Conclusions: The effect of the educative intervatiun was significant statistically, for the sake of the degree of knowledges to education model in Diabetes Mellitus for the health was bigger after to the intervatiun.Introducción: La Educación permanente de cualquier profesión, en especial el avance en enfermería con sus distintos estamentos de profesionales, requiere de un plan permanente de formación. Si se plantea un compromiso real con la transformación en la práctica laboral y social, así como con la calidad de la atención, dicho plano no puede concebirse sin integrar a las instituciones de desempeño efectivo. Objetivo: Comparar el grado de conocimientos del personal de enfermería del modelo educación para la salud en Diabetes Mellitus antes y después de una intervención educativa. Material y métodos: Se realizó estudio comparativo antes y después, a 25 enfermeras, las cuales asistieron a la intervención educativa de capacitación del modelo de Educación para la Salud en Diabetes Mellitus, utilizando estrategias didácticas que permitieron al personal tener mayor participación. En total se desarrollaron 15 sesiones de hora y media cada una. El instrumento se elaboró a través de un examen estructurado con preguntas de opción múltiple y falso y verdadero con un valor del 70% de los ítems y un caso clínico de paciente diabético con un valor de 30% de lo ítems. Resultados: El promedio de edad de la población estudiada fue de 38 años, con una DE +5.3. Referente al grado de conocimiento del personal de enfermería del Modelo de Educación para la Salud antes de la intervención educativa, el 80% salió BAJO. Después de la intervención arrojó el 72% ALTO. Con prueba WLCOXON = con valor P < 0.05. Conclusiones: El efecto de la intervención educativa fue estadísticamente significativa; por lo que el grado de conocimientos del modelo de Educación para la Salud en Diabetes Mellitus fue mayor después de la intervención