title: Genephony: a knowledge management tool for genome-wide research.
abstract: BACKGROUND
  One of the consequences of the rapid and widespread adoption of high-throughput experimental technologies is an exponential increase of the amount of data produced by genome-wide experiments. Researchers increasingly need to handle very large volumes of heterogeneous data, including both the data generated by their own experiments and the data retrieved from publicly available repositories of genomic knowledge. Integration, exploration, manipulation and interpretation of data and information therefore need to become as automated as possible, since their scale and breadth are, in general, beyond the limits of what individual researchers and the basic data management tools in normal use can handle. This paper describes Genephony, a tool we are developing to address these challenges.
  
  
  RESULTS
  We describe how Genephony can be used to manage large datesets of genomic information, integrating them with existing knowledge repositories. We illustrate its functionalities with an example of a complex annotation task, in which a set of SNPs coming from a genotyping experiment is annotated with genes known to be associated to a phenotype of interest. We show how, thanks to the modular architecture of Genephony and its user-friendly interface, this task can be performed in a few simple steps.
  
  
  CONCLUSIONS
  Genephony is an online tool for the manipulation of large datasets of genomic information. It can be used as a browser for genomic data, as a high-throughput annotation tool, and as a knowledge discovery tool. It is designed to be easy to use, flexible and extensible. Its knowledge management engine provides fine-grained control over individual data elements, as well as efficient operations on large datasets.
authors.affiliation: Centre for Tissue Engineering, University of Pavia, Pavia, Italy. angelo.nuzzo@unipv.it
authors.forename: Angelo
authors.initials: A
authors.lastname: Nuzzo
authors.forename: Alberto
authors.initials: A
authors.lastname: Riva
mesh_terms: D019295:Computational Biology / Q000379:methods*; D003628:Database Management Systems; D016678:Genome; D023281:Genomics; D016247:Information Storage and Retrieval / Q000379:methods*; D012984:Software; D014584:User-Computer Interface