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Lowering barriers to publishing biological data on the web


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Short 10 minute talk encouraging bioinformatics programmers to organize and reuse code targeted at making data easily available on the web. Current open source technologies are combined into a higher level framework. An example implementation using Google App Engine and existing bioinformatics libraries is presented.

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Lowering barriers to publishing biological data on the web

  1. 1. Lowering barriers to publishing biological data on the web Brad Chapman Department of Molecular Biology Massachusetts General Hospital Boston, MA USA 27 June 2009
  2. 2. Motivation
  3. 3. Motivation Web accessible Interoperable in standard formats Displays for browsing Analyses Scale
  4. 4. Current state: Reusable libraries Parse file formats Run programs Build analysis pipelines Communities Python examples Biopython pygr bx-python PyCogent
  5. 5. Current state: Database schemas Represent biological data Expand analyses beyond flat files Interoperate with standards BioSQL Chado
  6. 6. Current state: Web applications
  7. 7. Faster and Bigger
  8. 8. Proposal Provide Reusable presentation components Quickly deployable frameworks Integrate Bioinformatics libraries Database schemas Web development frameworks
  9. 9. Proposal
  10. 10.
  11. 11. Challenges: Design Reusable Components: avoid large framework Multi-language: javascript front end Accessible Automated data retrieval (REST) Standard formats (GFF, RDF) Available Creative Commons Open Data Commons
  12. 12. Challenges: Community questions How do we. . . provide plug-in components? leverage existing code? make reuse easier? communicate about these issues?