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Federation of Neuroscience Information: A Tale of Two Sciences

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  • 1. Federating Neuroscience Information: A Tale of Two Sciences Amarnath Gupta Bertram Lud äscher Maryann Martone
  • 2. Neuroscience A Scenario
  • 3. An Unresolved Challenge How do nerve cells change as we learn and remember? A multi-resolution study of the rat hippocampus at Boston University
  • 4. Dendritic spine morphology and its variations Reconstructions from the Synapse Lab, Boston University density = #spines/length
  • 5. Observations
    • Spine density, size, shape and PSD vary with maturity
    • Spine neck geometry controls peak Calcium amount
    • Calcium flow parameters depend on the different subclasses of spines
    • Distribution of spines changes
    • with learning
    • Each spine type performs a different task in information transmission
    Hypothesis Next Questions
    • Does anyone else have corroborative evidence for these observations?
    • Are these observations true in other comparable parts of the brain ?
    • Is this consistent with the distribution of Calcium-binding proteins ?
  • 6. “But we don’t have that data!”
  • 7. Exploring and Integrating Information
    • Who else has data on spiny dendrite morphology and Ca-binding protein distribution for hippocampus? What about other brain regions?
    • How do their findings compare with ours?
    Ask the KIND Mediator
  • 8. ANATOM Domain Map with Data Points
  • 9. ANATOM Domain Map Closure
  • 10. Raw Data “Hanging Off” the ANATOM Map
  • 11. MIX Mediation Framework MIX MEDIATOR INTEGRATED VIEW USER Data Sources Wrapper Wrapper Wrapper XML Q/A XML Q/A XML Integrated View Definition XML Q/A DB Files WWW Lab1 Lab2 Lab3
  • 12. Computer Science Issues and Challenges
  • 13. Computer Science Challenges SEMANTIC Integration ???
    • SYNTACTIC/STRUCTURAL Integration
    • Integrated Views (Src-XML => Intgr-XML)
    • Schema Integration (DTD =>DTD)
    • Wrapping, Data Extraction (Text => XML)
    MIX Mediation of Information using XML SYSTEM Integration SRB/MCAT TCP/IP HTTP CORBA storage, access protocols & services Distributed Query Processing
    • Simple One-World Mediation Scenarios
    • => System- and Structure-Level Integration is ok
    • Complex Multiple-World Scenarios
    • => Semantic Integration is needed!
  • 14. Model-Based Mediation Raw Data Raw Data Raw Data A = (B*|C),D B = ... XML DTDs Integrated- DTD := XML-QL (Src1- DTD ,...) IF  THEN  IF  THEN  IF  THEN  Logical Domain Constraints Integrated- CM := CM-QL (Src1- CM ,...) . . .... .... .... .... (XML) Objects C onceptual M odels XML Elements XML Models C2 C3 C1 R Classes, Relations, is-a , has-a, ... Domain Map
  • 15. Model-Based Mediation with Domain Maps I-CM(Z1,...) := get X1,... from Src1; get X2,... from Src2; LINK (Xi, Yj); Zj = CM-QL(X1,...,Y1,...) LINK(X,Y): X.zip = Y.zip X.addr in Y.zip X.zip overlaps Y.county ...
    • Domain Map:
    • abstraction of layered road-maps (Digital Earth, Brain Atlases, ...)
    • net of semantic link points (LPs)
    • LP relations: is-a, overlaps, ...
    • have layers
    • => common semantic coordinate system (“ontology”) for correlating (“hanging off”) data at LPs
    => from syntactic equality to semantic joins
  • 16. Example Query Evaluation Plan (simplified)
    • @SENSELAB : X1 := select output from parallel fiber ;
    • @MEDIATOR : X2 := “ hang off ” X1 from Domain Map ;
    • @MEDIATOR : X3 := subregion-closure (X2);
    • @NCMIR : X4 := select PROT-data(X3, Ryanodine Receptors );
    • @MEDIATOR : X5 := compute aggregate (X4);
    "How does the parallel fiber output ( Yale / SENSELAB ) relate to the distribution of Ryanodine Receptors ( UCSD / NCMIR )?" KIND Mediator
  • 17. Interactive KIND Query
  • 18. Resulting Sub-Domain Map “Browser”
  • 19. Actual Protein Localization Result Data
  • 20. Client-Side Result Visualization (using AxioMap Viewer: Ilya Zaslavsky)