Gene Ontology Based Automated Annotation: Why It Isn’t Working

  • Matthijs van der Kroon
  • Ana M. Levin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6999)


Genomics has seen a great deal of development since the milestone of the sequencing of the human genome by Craig Venter and Francis Collins in 2000. However, it is broadly accepted now that real challenges are lying ahead in actually understanding the meaning of these raw data. Traditionally this process of assigning meaning to biological crude data is being performed by domain specialists and has been known as annotation. As data chaos becomes larger due to rapid advances in sequencing technologies, the interest for automated annotation has equally increased. Current approaches are often based on the Gene Ontology (GO), but often fail to meet the requirements. Determining why and how they fail will prove crucial in finding methods that perform better, and ultimately might very well deliver the promising feat of turning the Human Genome data chaos into actual knowledge.


Gene Ontology Information System Automate Annotation Model Drive Architecture Token Function 
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 2011

Authors and Affiliations

  • Matthijs van der Kroon
    • 1
  • Ana M. Levin
    • 1
  1. 1.Centro de Investigación en Métodos de Producción de Software -PROSUniversidad Politécnica de ValenciaValenciaSpain

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