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

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

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

SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data

<p>Abstract</p> <p>Background</p> <p>Censored data are increasingly common in many microarray studies that attempt to relate gene expression to patient survival. Several new methods have been proposed in the last two years. Most of these methods, however, are not available to biomedical researchers, leading to many re-implementations from scratch of ad-hoc, and suboptimal, approaches with survival data.</p> <p>Results</p> <p>We have developed SignS (Signatures for Survival data), an open-source, freely-available, web-based tool and R package for gene selection, building molecular signatures, and prediction with survival data. SignS implements four methods which, according to existing reviews, perform well and, by being of a very different nature, offer complementary approaches. We use parallel computing via MPI, leading to large decreases in user waiting time. Cross-validation is used to asses predictive performance and stability of solutions, the latter an issue of increasing concern given that there are often several solutions with similar predictive performance. Biological interpretation of results is enhanced because genes and signatures in models can be sent to other freely-available on-line tools for examination of PubMed references, GO terms, and KEGG and Reactome pathways of selected genes.</p> <p>Conclusion</p> <p>SignS is the first web-based tool for survival analysis of expression data, and one of the very few with biomedical researchers as target users. SignS is also one of the few bioinformatics web-based applications to extensively use parallelization, including fault tolerance and crash recovery. Because of its combination of methods implemented, usage of parallel computing, code availability, and links to additional data bases, SignS is a unique tool, and will be of immediate relevance to biomedical researchers, biostatisticians and bioinformaticians.</p

Demographic connectivity of sardine in the Bay of Biscay and Iberian coast region

Demographic connectivity in sardine populatio

Dietary Fat Patterns and Outcomes in Acute Pancreatitis in Spain

Background/Objective: Evidence from basic and clinical studies suggests that unsaturated fatty acids (UFAs) might be relevant mediators of the development of complications in acute pancreatitis (AP). Objective: The aim of this study was to analyze outcomes in patients with AP from regions in Spain with different patterns of dietary fat intake. Materials and Methods: A retrospective analysis was performed with data from 1,655 patients with AP from a Spanish prospective cohort study and regional nutritional data from a Spanish cross-sectional study. Nutritional data considered in the study concern the total lipid consumption, detailing total saturated fatty acids, UFAs and monounsaturated fatty acids (MUFAs) consumption derived from regional data and not from the patient prospective cohort. Two multivariable analysis models were used: (1) a model with the Charlson comorbidity index, sex, alcoholic etiology, and recurrent AP; (2) a model that included these variables plus obesity. Results: In multivariable analysis, patients from regions with high UFA intake had a significantly increased frequency of local complications, persistent organ failure (POF), mortality, and moderate-to-severe disease in the model without obesity and a higher frequency of POF in the model with obesity. Patients from regions with high MUFA intake had significantly more local complications and moderate-to-severe disease; this significance remained for moderate-to-severe disease when obesity was added to the model. Conclusions: Differences in dietary fat patterns could be associated with different outcomes in AP, and dietary fat patterns may be a pre-morbid factor that determines the severity of AP. UFAs, and particulary MUFAs, may influence the pathogenesis of the severity of AP

Fast 2D/3D object representation with growing neural gas

This work presents the design of a real-time system to model visual objects with the use of self-organising networks. The architecture of the system addresses multiple computer vision tasks such as image segmentation, optimal parameter estimation and object representation. We first develop a framework for building non-rigid shapes using the growth mechanism of the self-organising maps, and then we define an optimal number of nodes without overfitting or underfitting the network based on the knowledge obtained from information-theoretic considerations. We present experimental results for hands and faces, and we quantitatively evaluate the matching capabilities of the proposed method with the topographic product. The proposed method is easily extensible to 3D objects, as it offers similar features for efficient mesh reconstruction

Guidelines for the definition of operational management units

The objective of fisheries management is the sustainable exploitation of the fish resources over the extent of their spatial distribution. Along with the Common Fisheries Policy (CFP) objectives, the socio-economic viability of the fisheries exploiting the resource is also to be achieved. To reach these aims, managers need to define the management units they are going to work with. For the purpose of GEPETO project, we define a management unit (MU) as the set of fishing fleets exploiting a common pool of fish resources with strong spatial overlapping and sharing of habitats, which make them being typically fished together. In other words, a MU is the set of fishing fleets exploiting a common fish community over their spatial distribution. MUs have to be defined by the fish community, by the spatial range of distribution of the fish community, and by the set of fishing fleets sharing the exploitation of the fish communityL'objectif de gestion de la pêche est l'exploitation durable des ressources halieutiques sur l'étendue de leur répartition spatiale. Avec la nouvelle Politique Commune de la pêche (PCP) l' objectif de la viabilité socio-économique des pêcheries exploitant la ressource doit également être réalisé. Pour l'atteindre, les gestionnaires doivent définir des unités de gestion. Les partenaires du projet GEPETO, définissent une unité de gestion (MU) comme l'ensemble des flottes de pêche exploitant un pool commun de ressources halieutiques disponibles dans des habitats communs, ce qui les rend très imbriquées. En d'autres termes, un MU est l'ensemble des flottes de pêche exploitant une communauté de poissons ordinaires sur leur répartition spatiale. La MU peu être définie par la communauté de poissons, par la gamme spatiale de la distribution de la communauté de poissons, et par l'ensemble des flottes de pêche qui partagent l'exploitation de la communauté de poissons

Impacto de una investigación epidemiológica seguida de una intervención comunitaria para garantizar el acceso a la atención de las enfermedades crónicas de poblaciones socialmente vulnerables

Las enfermedades crónicas como la diabetes o la hipertensión se han vuelto endémicas en la mayoría de los países del mundo incluyendo a la Argentina. Debido a que ambas patologías mencionadas son oligosintomáticas, los pacientes suelen pasar muchos años sin percatarse de las mismas y frecuentemente el sistema de salud las identifica por una complicación asociada o por una descompensación que sufren los pacientes afectados. La consulta profesional vinculada a dichas enfermedades crónicas es realizada en forma muy tardía, configurándose cómo práctica extendida en gran parte de la población bonaerense. Los alcances del fenómeno han sido captados por estudios epidemiológicos oficiales realizados por la Sub-Secretaria de Planificación del Ministerio de Salud de la Provincia de Bs As, que muestran que solo el 13,5% de la población consulta oportunamente a los servicios de Salud. Asimismo, gran parte de los individuos que son diagnosticados, y a los que se les prescribe un tratamiento farmacológico, no tienen la adherencia al tratamiento esperada, con las consecuencias ominosas que ello tiene para su salud. Con el fin de establecer cuál es el impacto de un estudio epidemiológico de detección precoz de estas patologías y de una intervención que incluya un monitoreo continuo y garantice el cumplimiento adecuado del tratamiento en los pacientes con patologías crónicas, se inició el presente estudio que forma parte del proyecto de investigación M194 del programa incentivos docentes de la SPU

A response to Yu et al. "A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array", BMC Bioinformatics 2007, 8: 145

<p>Abstract</p> <p>Background</p> <p>Yu et al. (BMC Bioinformatics 2007,8: 145+) have recently compared the performance of several methods for the detection of genomic amplification and deletion breakpoints using data from high-density single nucleotide polymorphism arrays. One of the methods compared is our non-homogenous Hidden Markov Model approach. Our approach uses Markov Chain Monte Carlo for inference, but Yu et al. ran the sampler for a severely insufficient number of iterations for a Markov Chain Monte Carlo-based method. Moreover, they did not use the appropriate reference level for the non-altered state.</p> <p>Methods</p> <p>We rerun the analysis in Yu et al. using appropriate settings for both the Markov Chain Monte Carlo iterations and the reference level. Additionally, to show how easy it is to obtain answers to additional specific questions, we have added a new analysis targeted specifically to the detection of breakpoints.</p> <p>Results</p> <p>The reanalysis shows that the performance of our method is comparable to that of the other methods analyzed. In addition, we can provide probabilities of a given spot being a breakpoint, something unique among the methods examined.</p> <p>Conclusion</p> <p>Markov Chain Monte Carlo methods require using a sufficient number of iterations before they can be assumed to yield samples from the distribution of interest. Running our method with too small a number of iterations cannot be representative of its performance. Moreover, our analysis shows how our original approach can be easily adapted to answer specific additional questions (e.g., identify edges).</p