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Additional file 14. A table with description of strains and plasmids generated and used in this study and graphical representation of over-expressed operons/genes

Integration of the changes in the metabolites associated with selected metabolic pathways in the upper non-inoculated leaves from the PVY^N-inoculated and PVY^NTN-inoculated plants, relative to the mock-inoculated plants.

<p>The metabolites identified from the primary and secondary metabolism and from redox reactions are shown. Each coloured square represents the log2 ratios of the concentration (red, high; green, low) at 3 and 6 dpi in the upper non-inoculated leaves of the PVY^N-inoculated (N:m) and PVY^NTM-inoculated (NTN:m) plants, relative to the mock-inoculated plants (as indicated). MapMan BINs linked to primary metabolism: 2.1.1 major CHO metabolism, sucrose synthesis; 2.2.1 major CHO metabolism, sucrose degradation; 2.2.2 major CHO metabolism, starch degradation. MapMan BINs linked to the GABA shunt: 13.1.1.1 amino-acid metabolism, GABA synthesis; 8.1. TCA; 22. polyamine metabolism; 12.2.1002 N-metabolism, ammonia. MapMan BINs linked to secondary metabolism: 16.2.1 secondary metabolism, phenylpropanoids biosynthesis; 13.1. amino-acid synthesis.</p

Overview of the response of individual leaf sample and changes of metabolites in inoculated leaves.

<p>Mock-inoculated (S, 1 to 6), PVY^N-inoculated (N, 1 to 6), and PVY^NTN-inoculated (NTN, 1 to 6) leaves, collected at 1, 3 and 6 dpi, are shown. Distance matrix (A) shows more similar responses between samples collected at 1 dpi and at 6 dpi, while less uniform response is observed in samples collected at 3 dpi. Hierarchical clustering (B) was done on a set of identified metabolites to which metabolite ontology (metabolic pathway) was assigned. Clusters of metabolites linked to amino-acid synthesis and those linked to secondary metabolism and cell wall clustered together.</p

Integration of the changes in the metabolites and transcripts associated with selected metabolic pathways in the PVY^N-inoculated and PVY^NTN-inoculated leaves, relative to the mock-inoculated leaves.

<p>The metabolites identified and the genes analysed from the primary and secondary metabolism and from redox reactions are shown. Each coloured square represents the log2 ratios of the expression or abundance (red, high; green, low) at 1, 3 and 6 dpi in the PVY^N-inoculated (N:m) and PVY^NTN-inoculated (NTN:m) leaves, relative to the mock-inoculated leaves (as indicated). MapMan BINs linked to primary metabolism: 2.1.1 major CHO metabolism, sucrose synthesis; 2.2.1 major CHO metabolism, sucrose degradation; 2.2.2 major CHO metabolism, starch degradation. MapMan BINs linked to the GABA shunt: 13.1.1.1 amino-acid metabolism, GABA synthesis; 8.1. TCA; 22. polyamine metabolism; 12.2.1002 N-metabolism, ammonia. MapMan BINs linked to secondary metabolism: 16.2.1 secondary metabolism, phenylpropanoids biosynthesis; 13.1. amino-acid synthesis.</p

Desarrollo de una batería de uso espacial a partir de células comerciales

Este Trabajo Fin de Máster es la culminación de un proyecto docente dedicado a las baterías de uso espacial a partir de células comerciales (COTS), iniciado por el autor en el Caso de Estudio II y en el Caso de Estudio III del Máster Universitario en Sistemas espaciales, impartido en el instituto IDR/UPM. Este TFM se centra en el análisis de los circuitos de equilibrado en baterías de uso espacial. El uso de este tipo de circuitos es imprescindible en el empleo de baterías de ion Litio, y su necesidad ha quedado bien patente tras los trabajos de monitorización y equilibrado de la batería del UPMSat-2. El trabajo desarrollado en este documento se empleará en el diseño y construcción de la futura batería para la misión UNION/Lian. La batería (o baterías) de un micro-satélite comprende una parte significativa de su masa seca total (sin propulsante), y son elementos críticos de misión, los cuales suministran potencia eléctrica a todos los subsistemas del segmento de vuelo durante los periodos de eclipse. No obstante, el suministro energético de la batería no es la única demanda de la que esta es objeto: todas las misiones típicamente exponen a la batería a vibraciones extremas y choques durante el lanzamiento y la separación, así como altos gradientes de temperatura, radiación, y condiciones de vacío en órbita. En este Trabajo Fin de Máster se recopila también el Plan de Ensayos que guiará a los mismos con el fin de calificar la futura batería de la misión UNION/Lian

Additional file 5: of quantGenius: implementation of a decision support system for qPCR-based gene quantification

quantGenius performance validation: calculations in Excel. (XLS 50 kb

Signalling Network Construction for Modelling Plant Defence Response

<div><p>Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the <i>Arabidopsis thaliana</i> model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of <i>(component1, reaction, component2)</i> triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at <a href="http://ropot.ijs.si/bio3graph/and" target="_blank">http://ropot.ijs.si/bio3graph/and</a> can be utilised for modelling other biological systems, given that an adequate vocabulary is provided.</p></div

Summary of all reaction types of the manually constructed SA, JA and ET sub-models, including the crosstalk connections, represented at level 1 of the PDS taxonomy of Figure 1B.

<p>Summary of all reaction types of the manually constructed SA, JA and ET sub-models, including the crosstalk connections, represented at level 1 of the PDS taxonomy of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051822#pone-0051822-g001" target="_blank">Figure 1B</a>.</p

Recall and precision analysis for 50 full-length papers.

<p>Recall and precision analysis for 50 full-length papers.</p

New direct PDS relations extracted from the biological literature.

<p>The new direct links result from the Bio3graph processing of 9,586 articles. Bio3graph extracted 14 new direct relations between the components which were not identified in the manually built PDS model topology. Note that two of these triplets are trivial (<i>SAG_metabolite, activates, SA_metabolite)</i> and <i>(NIMIN1_protein, inhibits, NPR1_protein</i>).</p