• Like


Flash Player 9 (or above) is needed to view presentations.
We have detected that you do not have it on your computer. To install it, go here.

Federation of Neuroscience Information: A Tale of Two Sciences



  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads


Total Views
On SlideShare
From Embeds
Number of Embeds



Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

    No notes for slide


  • 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 ???
    • 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)