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Bioimage Informatics in the context of Drosophila research.
Jug, Florian; Pietzsch, Tobias; Preibisch, Stephan; Tomancak, Pavel.
Afiliación
  • Jug F; Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.
  • Pietzsch T; Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.
  • Preibisch S; Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; Department of Anatomy and Structural Biology, Gruss Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, NY 10461, USA.
  • Tomancak P; Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany. Electronic address: tomancak@mpi-cbg.de.
Methods ; 68(1): 60-73, 2014 Jun 15.
Article en En | MEDLINE | ID: mdl-24732429
ABSTRACT
Modern biological research relies heavily on microscopic imaging. The advanced genetic toolkit of Drosophila makes it possible to label molecular and cellular components with unprecedented level of specificity necessitating the application of the most sophisticated imaging technologies. Imaging in Drosophila spans all scales from single molecules to the entire populations of adult organisms, from electron microscopy to live imaging of developmental processes. As the imaging approaches become more complex and ambitious, there is an increasing need for quantitative, computer-mediated image processing and analysis to make sense of the imagery. Bioimage Informatics is an emerging research field that covers all aspects of biological image analysis from data handling, through processing, to quantitative measurements, analysis and data presentation. Some of the most advanced, large scale projects, combining cutting edge imaging with complex bioimage informatics pipelines, are realized in the Drosophila research community. In this review, we discuss the current research in biological image analysis specifically relevant to the type of systems level image datasets that are uniquely available for the Drosophila model system. We focus on how state-of-the-art computer vision algorithms are impacting the ability of Drosophila researchers to analyze biological systems in space and time. We pay particular attention to how these algorithmic advances from computer science are made usable to practicing biologists through open source platforms and how biologists can themselves participate in their further development.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Biología Computacional / Drosophila melanogaster / Imagen Molecular Límite: Animals Idioma: En Revista: Methods Asunto de la revista: BIOQUIMICA Año: 2014 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Biología Computacional / Drosophila melanogaster / Imagen Molecular Límite: Animals Idioma: En Revista: Methods Asunto de la revista: BIOQUIMICA Año: 2014 Tipo del documento: Article País de afiliación: Alemania