Federation of Neuroscience Information: A Tale of Two Sciences

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Federation of Neuroscience Information: A Tale of Two Sciences

  1. 1. Federating NeuroscienceFederating Neuroscience Information:Information: A Tale of Two SciencesA Tale of Two Sciences Amarnath Gupta Bertram Ludä scher Maryann Martone
  2. 2. NeuroscienceNeuroscience A ScenarioA Scenario
  3. 3. An Unresolved ChallengeAn Unresolved Challenge How do nerve cells change as we learn and remember?How do nerve cells change as we learn and remember? A multi-resolution study of the rat hippocampus at Boston University
  4. 4. Dendritic spine morphology and its variationsDendritic spine morphology and its variations Reconstructions from the Synapse Lab, Boston University density = #spines/length
  5. 5. • Distribution of spines changes with learning • Each spine type performs a different task in information transmission HypothesisHypothesis ObservationsObservations • 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 Next QuestionsNext 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. 6. ““But we don’t have that data!”But we don’t have that data!”
  7. 7. Exploring and IntegratingExploring and Integrating InformationInformation • 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. 8. ANATOMANATOM Domain MapDomain Map with Data Pointswith Data Points
  9. 9. ANATOMANATOM Domain Map ClosureDomain Map Closure
  10. 10. Raw DataRaw Data “Hanging Off” the ANATOM Map“Hanging Off” the ANATOM Map
  11. 11. MIXMIX Mediation FrameworkMediation Framework MIX MEDIATOR INTEGRATED VIEW USERUSER Data Sources DB Files WWW Lab1 Lab2 Lab3 Wrapper Wrapper Wrapper XML Q/A XML Q/A XML Integrated View Definition XML Q/A
  12. 12. Computer ScienceComputer Science Issues and ChallengesIssues and Challenges
  13. 13. Computer Science ChallengesComputer 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 QueryProcessing • Simple One-World Mediation Scenarios => System- and Structure-Level Integration is ok • Complex Multiple-World Scenarios => Semantic Integration is needed!
  14. 14. Model-Based MediationModel-Based Mediation Raw DataRaw DataRaw Data A = (B*|C),D B = ... XML DTDs Integrated-DTD := XML-QL(Src1- DTD,...) IF ϕ THEN ψIF ϕ THEN ψIF ϕ THEN ψ Logical Domain Constraints Integrated-CM := CM-QL(Src1- CM,...) . . .... .... ........ (XML) Objects Conceptual Models XML Elements XML Models C2 C3 C1 R Classes, Relations, is-a, has-a, ... Domai n Map
  15. 15. Model-Based Mediation withModel-Based Mediation with Domain MapsDomain 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: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. 16. Example Query EvaluationExample Query Evaluation PlanPlan (simplified)(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. 17. Interactive KIND QueryInteractive KIND Query
  18. 18. Resulting Sub-Domain MapResulting Sub-Domain Map “Browser”“Browser”
  19. 19. Actual Protein Localization ResultActual Protein Localization Result DataData
  20. 20. Client-Side Result VisualizationClient-Side Result Visualization (using AxioMap Viewer: Ilya Zaslavsky)(using AxioMap Viewer: Ilya Zaslavsky)

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