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Architectural Constraints on Current Bioinformatics Integration Systems

Architectural Constraints on Current Bioinformatics Integration Systems. Norman Paton Department of Computer Science University of Manchester Manchester, UK <norm>@cs.man.ac.uk. Structure of Presentation. Current integration proposals. What they support. What they don’t support, and why.

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Architectural Constraints on Current Bioinformatics Integration Systems

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  1. Architectural Constraints on Current Bioinformatics Integration Systems Norman Paton Department of Computer Science University of Manchester Manchester, UK <norm>@cs.man.ac.uk

  2. Structure of Presentation • Current integration proposals. • What they support. • What they don’t support, and why. • Requirements for integration. • What could be useful, and why. • Grid opportunities. • Relevant Grid technologies. • Absent Grid technologies.

  3. Current Integration Proposals

  4. Classification

  5. SRS Sequence Retrieval System http://srs.ebi.ac.uk/

  6. SRS In Use List of Databases Search Interfaces Selected Databases

  7. SRS Results Links to Result Records

  8. Classification of SRS

  9. BioNavigator • BioNavigator combines data sources and the tools that act over them. • As tools act on specific kinds of data, the interface makes available only tools that are applicable to the data in hand. Online trial from: https://www.bionavigator.com/

  10. Initiating Navigation Select database Enter accession number

  11. Viewing Selected Data Navigate to related programs Relevant display options

  12. Chaining Analyses in Macros Chained collections of navigations can be saved as macros and restored for later use.

  13. Classification of BioNavigator

  14. Current Public Integration Systems • Location: data is replicated – under control. • Integration model: often minimal. • Architecture: The architecture is often two-tier. • Analysis support: Query and analysis access is carefully contained. Only very careful instantiation of the classification yields sufficiently predictable performance.

  15. GIMS

  16. GIMS – recent experience

  17. Example Analysis • Data: • Yeast genome sequence. • Protein-protein interaction data. • 350 transcriptome experiments. • Overall database ~350Mb. • Analysis: • Correlate transcription of interacting proteins.

  18. Features of Experience • Challenging to conduct single runs of analyses – must break into bits. • These are modest data sets compared with what is coming. • Environment has been designed with analysis in mind. • These analyses will never make it into the public release!

  19. Requirements for Integration

  20. Requirements for Integration • Location: replication is transparent. • Integration model: standards. • Architecture: Flexible, multiple tier. • Analysis support: Arbitrary analyses over diverse data sets. True integration in bioinformatics should not just be data oriented, but involve integration of analyses.

  21. Clients handle user interaction and presentation. Application servers perform computation and analysis. Data servers manage and query databases. Client Application Server Data Server Three Tier Architecture

  22. Three Tier Architecture • Scaleability: • Replace/Upgrade components as needed. • Replace/Upgrade layers independently. • Flexibility: • Application server layer protects clients from changes in database layer. Classical three tier architectures are configured statically, and are adapted slowly as needs evolve.

  23. Grid Opportunities

  24. Necessary: Directory services. Discovery services. Co-allocation. Data replication. Workload management. Accounting and payment. Missing: Databases. Data models. Heterogeneity resolution. Personalisation. Web services. Standards. Necessary and Missing

  25. Dynamic Multi-Tier Resources need to be identified, selected and scheduled dynamically. Client Application Server Application Server Application Server Data Server Data Server

  26. Grid Classification The current Grid is not the answer, but the answer subsumes the current facilities of the Grid.

  27. Summary • Current integration facilities in biology: • Are cunningly restrictive. • Make the most of limited distributed computational architectures. • The Grid is bringing to the table: • Resource description facilities. • Resource scheduling and workflow management facilities. • The Grid does not directly address current needs in biology, but its descendents may.

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