Descripción del proyecto
Nuevas herramientas bioinformáticas y de biología de sistemas para la descripción funcional de bacterias
Las bacterias representan el mayor grupo de organismos del planeta. Sin embargo, su investigación no ha suscitado demasiado interés hasta el momento, lo que ha generado obstáculos en el procesamiento de datos bioinformáticos y de biología de sistemas, ya que muchas herramientas modernas están diseñadas principalmente para organismos modelo eucariotas y no se pueden adaptar fácilmente a las bacterias no modelo. Financiado por las Acciones Marie Skłodowska-Curie, el proyecto HOPE-4-BEST tiene como objetivo diseñar nuevas herramientas bioinformáticas y de biología de sistemas para realizar análisis de bacterias exhaustivos, así como aplicaciones para la ingeniería industrial de cepas bacterianas. El propósito es ensamblar una anotación funcional integral para los organismos no modelo mediante el diseño de un proceso novedoso que analice las muestras del transcriptoma completo en diversas condiciones, combinándola con las anotaciones creadas mediante una búsqueda exhaustiva en las bases de datos.
Objetivo
The project “The Annotation and Functional Description of Non-Model Bacterial Organisms for Bio-based Engineering and Industry (HOPE-4-BEST)” aims to bring new bioinformatics and systems biology tools for a comprehensive description of little studied microorganisms and inference of biological knowledge further utilizable in synthetic biology for engineering of industrially utilizable bacterial strains. Bacteria form the largest group of organisms in the world. Since the DNA and RNA sequencing became widely available, they begun to be often studied on molecular level for their exceptional biological properties, e.g. ability to produce fuels or plastics from waste. Unfortunately, previous lack of interest in their research is the source of many obstacles in bioinformatics and systems biology data processing as current tools, designed primarily for eukaryotic model organisms, cannot be easily used for processing data gathered from non-model bacterial organisms. Inference of biological knowledge presumes identification of regulated genes and annotation of their molecular function so involved biological processes could be captured. The project addresses two important questions, how to assemble a comprehensive functional annotation for non-model organisms and how it affects inferred biological knowledge. This will be achieved by designing novel pipeline utilizing transcriptome wide analysis based on comparison of samples under various conditions while considering data bias, e.g. multimapping reads or overlapping genes, and its combination with annotation build by extensive database searching. Eventually, the successful solution of the project will not only substantially contribute to our understanding how various parameters of bioinformatics data processing and annotation affect resulting biological knowledge, but will provide ready-to-use solution for wide scientific community.
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MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinador
80539 MUNCHEN
Alemania