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Rbbt: A Framework for Fast Bioinformatics Development with Ruby

  • Miguel Vázquez
  • Rubén Nogales
  • Pedro Carmona
  • Alberto Pascual
  • Juan Pavón
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 74)

Abstract

In a fast evolving field like molecular biology, which produces great amounts of data at an ever increasing pace, it becomes fundamental the development of analysis applications that can keep up with that pace. The Rbbt development framework intends to support the development of complex functionality with strong data processing dependencies, as reusable components, and serving them through a simple and consistent API. This way, the framework promotes reuse and accessibility, and complements other solutions like classic APIs and function libraries or web services. The Rbbt framework currently provides a wide range of functionality from text mining to microarray meta-analysis.

Keywords

Conditional Random Field Processing Pipeline Entity Recognition Gene Mention Word Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Miguel Vázquez
    • 1
  • Rubén Nogales
    • 2
  • Pedro Carmona
    • 2
  • Alberto Pascual
    • 3
  • Juan Pavón
    • 1
  1. 1.Dep. Ingeniería del Software e Inteligencia ArtificialUniversidad Complutense Madrid 
  2. 2.Dep. Arquitectura de Computadores y AutomáticaUniversidad Complutense Madrid 
  3. 3.Biocomputing UnitNational Center for Biotechnology-CSIC 

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