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  • 1. BeeSpace: An Interactive Environment for Analyzing Nature and Nurture in Societal Roles
    • Bruce Schatz
    • Institute for Genomic Biology
    • University of Illinois at Urbana-Champaign
    • www.beespace.uiuc.edu
    • Third Annual Project Workshop
    • IGB, Urbana IL May 21, 2007
  • 2.  
  • 3. BeeSpace Workshop Schedule
    • Introductory Lectures (Bevier Auditorium), 9-12
      • Informatics, Biology, Education
      • Faculty Investigators across Campus
    • Working Sessions (IGB Training Rooms), 1-5
      • System Demo, Biology Usage, User Support
      • Staff Members within IGB
    • Strategic Planning (IGB Conference Rooms),9-12
      • Project Members and Visitors
  • 4. BeeSpace is…
    • A Big Interdisciplinary Project
      • The First and the Biggest at IGB
      • NSF FIBR $5M 2004-2009
    • General Biotechnology (Dry Lab)
      • Interactive Environment for Functional Analysis (Bioinformatics)
    • Important Science (Wet Lab)
      • Model Dissection of Nature-Nurture (Genomics of Behavioral Plasticity)
  • 5. BeeSpace FIBR Project
    • BeeSpace project is NSF FIBR flagship
    • Frontiers Integrative Biological Research,
    • $5M for 5 years at University of Illinois
    • Analyzing Nature and Nurture in Societal Roles using honey bee as model
    • (Functional Analysis of Social Behavior)
    • Genomic technologies in wet lab and dry lab
    • Bee [Biology] gene expressions
    • Space [Informatics] concept navigations
  • 6. Project Investigators
    • Biology
    • Gene Robinson, Integrative Biology (genomics)
    • Susan Fahrbach, Biology at Wake Forest (anatomy)
    • Sandra Rodriguez-Zas, Animal Sciences (data analysis)
    • Informatics
    • Bruce Schatz, Medical Information Science (systems) ChengXiang Zhai, Computer Science (text analysis)
    • Chip Bruce, Library & Information Science (users )
    • Collaborators
    • FlyBase, BeeBase, Bee Genome Community
  • 7.  
  • 8. BeeSpace Goals
    • Analyze the relative contributions of
    • Nature and Nurture in
    • Societal Roles in Honey Bees
    • Experimentally measure gene expression in the brain for important societal roles during normal behavior varying heredity (nature) and environment (nurture)
    • Interactively annotate functions for differential expression using concept-based navigation of biological literature and gene –centered summarization analysis
  • 9. for Social B ee havior
  • 10. Complex Systems I
    • Understanding Social Behavior
    • Honey Bees have only 1 million neurons
    • Yet…
    • A Worker Bee exhibits Social Behavior!
    • She forages when she is not hungry
    • but the Hive is
    • She fights when she is not threatened
    • but the Hive is
  • 11. for Functional Analysis
  • 12. Complex Systems II
    • Understanding Functional Analysis
    • Integrating many sources to explain behavior
    • Across organisms and functions
    • Most of functional explanations are in text
    • Text Mining and Gene Summarizing
    • Intersecting Multiple Viewpoints to
    • Discover Emergent Properties
  • 13. BeeSpace Informatics
  • 14. Post-Genome Informatics
    • Comparative Genomics to Classical Models
    • Sequence-based gene annotation
      • To standard classifications such as Gene Ontology
    • Literature-based gene annotation
      • To computed classifications via extracted concepts
    • Descriptions in Literature MUST be used in future
    • interactive environments for functional analysis!
  • 15. Informatics: From Bases to Spaces
    • data Bases support genome data
    • e.g. FlyBase has sequences and maps
    • Insect genes typically re-use Drosophila names.
    • BeeBase (Christine Elsik, Texas A&M)
    • Uses computed orthologs to annotate genes
    • information Spaces support biological literature
    • BeeSpace uses automatically generated
    • conceptual relationships to navigate functions
  • 16. System Architecture Concepts Concepts Documents Documents Community Community Databases Expressions Bees Flies SEQ SEQ Expressions BeeSpace
  • 17. Concept Navigation in BeeSpace Neuroscience Literature Molecular Biology Literature Bee Literature Flybase, WormBase Bee Genome Brain Region Localization Brain Gene Expression Profiles Behavioral Biologist Molecular Biologist Neuro- scientist
  • 18. BeeSpace General Biotechnology
    • Bioinformatics of Genes and Behavior
    • Using scalable semantics technology
    • Using General Expressions and Literatures
    • Annotation Pipelines from Sequence and Text
    • Creating and Merging multiple SPACES
    • Where REGIONS are semantically created
    • And useful regions become shared spaces
  • 19. BeeSpace Community Collections
    • Organism
      • Honey Bee / Fruit Fly
      • Song Bird / Soy Bean
    • Behavior
      • Social / Territorial
      • Foraging / Nesting
    • Development
      • Behavioral Maturation
      • Insect Development
      • Insect Communication
    •  Structure
      • Fly Genetics / Fly Biochemistry
      • Fly Physiology / Insect Neurophysiology
  • 20. Analysis Environment: Model
    • Explicitly capture SCIENCE in SYSTEM!
    • Wet Lab:
    • Locate Candidate Genes
    • Classify Differential Genes
    • Dry Lab:
    • Locate Candidate Texts
    • Classify Differential Texts
  • 21. Analysis Environment: Features
    • SPACE is a Paradigm not a Metaphor!
    • Point of View for YOUR Problem
    • Externally:
    • -Dynamically describe custom Region of Space
    • -Merge Regions to form Hypothesis Space
    • -Differentially express genes against Space
  • 22. Analysis Environment: System
    • Concepts and Genes are Universal Entities!
    • Uniformly Represented
    • Uniformly Manipulated
    • Internally:
    • -Extract and Index Concepts within Collections
    • -Navigate Concepts within Documents
    • -Follow Genes from Documents into Databases
  • 23. CONCEPT SWITCHING
    • “ Concept” versus “Term”
      • set of “semantically” equivalent terms
    • Concept switching
      • region to region (set to set) match
    term Semantic region Concept Space Concept Space
  • 24. BeeSpace Information Sources
    • General for All Spaces:
    • Scientific Literature
    • -Medline, Biosis, Agricola, Agris, CAB Abstracts
    • -partitioned by organisms and by functions
    • Model Organisms
    • -Gene Descriptions (FlyBase, WormBase, MGI, OMIM, TAIR, SCD)
    • Special Sources for BeeSpace:
    • -Natural History Books (Cornell Library, Harvard Press)
  • 25. XSpace Information Sources
    • Organize Genome Databases (XBase)
    • Compute Gene Descriptions from Model Organisms
    • Partition Scientific Literature for Organism X
    • Compute XSpace using Semantic Indexing
    • Boost the Functional Analysis from Special Sources
    • Collecting Useful Data about Natural Histories
    • e.g. PigSpace Leverage in USDA Databases
  • 26. Towards the Interspace
    • The Analysis Environment technology is GENERAL ! BirdSpace? BeeSpace?
    • PigSpace? CowSpace?
    • SoySpace? CornSpace?
    • InsectSpace? PlantSpace?
    • BioSpace? MedSpace?
  • 27. BeeSpace Biology
  • 28. Biology: The Model Organism
    • Western Honey Bee, Apis mellifera
    • A model for social behavior
    Coordinated Publication 50 papers Oct 2006 Nature, Science, PNAS Genome Research Insect Molecular Biology
  • 29. Emergent Properties
    • Complex Behavior from Simple Model
    • Normal Behavior – honey bees live in the wild
    • Controllable Heredity – Queens and Hormones
    • Controllable Environment – hives can be modified
    • Small size manageable with genomic technology
    • Differential genes for normal behavior
  • 30. Nature and Nurture both act on the genome Heredity Environment
  • 31. Power of Social Evolution
    • Agriculture (bee forager)
    • Warfare (bee defender)
    • Language (bee dancer)
    • Humans do These, So do Social Insects
    • We are performing Nature-Nurture dissection to locate candidate genes spanning these normal behaviors of honey bees
  • 32.
      • (Whitfield et al, 2002)
  • 33. Experimental Status
    • Genome Complete and Microarray Fabricated
    • Bees collected for Societal Role experiments
    • Initial Dissections complete on EST array
    • On-going first Genome Array dissection
    • Sequence Annotation Pipeline being used
    • Literature Annotation Pipeline being tested
    • Designing Meta-analysis Environment
  • 34. BeeSpace Education
  • 35. Education: Scientific Inquiry
    • Graduate
      • New Research via Functional Analysis
      • 5 early adopter labs, then 15 international labs
    • Undergraduate
      • New Bioinformatics Course using BeeSpace
    • High School
      • Integrate into Field Biology course at Uni High
  • 36.  
  • 37.