Applying Agents to Bioinformatics in GeneWeaver

  • K. Bryson
  • M. Luck
  • M. Joy
  • D. T. Jones
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1860)


Recent years have seen dramatic and sustained growth in the amount of genomic data being generated, including in late 1999 the first complete sequence of a human chromosome. The challenge now faced by biological scientists is to make sense of this vast amount of accumulated and accumulating data. Fortunately, numerous databases are provided as resources containing relevant data, and there are similarly many available programs that analyse this data and attempt to understand it. However, the key problem in analyzing this genomic data is how to integrate the software and primary databases in a flexible and robust way. The wide range of available programs conform to very different input, output and processing requirements, typically with little consideration given to issues of integration, and in many cases with only token efforts made in the direction of usability. In this paper, we introduce the problem domain and describe GeneWeaver, a multi-agent system for genome analysis. We explain the suitability of the information agent paradigm to the problem domain, focus on the problem of incorporating different existing analysis tools, and describe progress to date.


Bovine SPONGIFORM Encephalopathy Communication Module Protein Structure Prediction Nucleic Acid Research Clustal Agent 
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 2000

Authors and Affiliations

  • K. Bryson
    • 1
  • M. Luck
    • 1
  • M. Joy
    • 1
  • D. T. Jones
    • 2
  1. 1.Department of Computer ScienceUniversity of Warwick CoventryUK
  2. 2.Department of Biological SciencesBrunel UniversityUxbridgeUK

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