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BeeSpace: An Interactive Environment for Analyzing Nature and Nurture in Societal Roles

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 FIBR Program Review June 1, 2006 BeeSpace Meetings Spring 2007 -- Jan 17, 2007.

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BeeSpace: An Interactive Environment for Analyzing Nature and Nurture in Societal Roles

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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 FIBR Program Review June 1, 2006 BeeSpace Meetings Spring 2007 -- Jan 17, 2007

  2. 2nd Annual Workshop May 21-22, 2007

  3. BeeSpace Goals Analyze the relative contributions of Nature and Nurture in Societal Roles in Honey Bees Experimentally measure brain gene expression for important societal roles during normal behavior varying heredity (nature) and environment (nurture) Interactively annotate gene functions for important gene clusters using concept navigation across biological literature representing community knowledge

  4. Power of Social Evolution • Language • Agriculture • Warfare Humans do These, So do Social Insects For Bees, we will carefully study Foraging and Defense

  5. Nature/Nurture Dissection I Defense Roles: Guard and Soldier Nature: Types of Bees (European, African) Nurture: Levels of Threats (Alarm pheromones)

  6. Nature/Nurture Dissection II Hereditary Differences affecting: onset age of Foraging Subspecies: European (German, Italian) and Africanized Honey Bees High/Low Pollen Hoarding Lines

  7. Nature/Nurture Dissection III Social Manipulations affecting: onset age of Foraging Precocious vs Normal Forager Normal vs Overage Nurse Reverted Nurse Socially Isolated

  8. Nature/Nurture Dissection IV Physiological Manipulations affecting: onset age of Foraging cGMP manganese NPF vitellogenin JH (Juvenile Hormone) octopamine TOFA (Fatty Acid inhibitor) Brood Pheromone, Queen Pheromone

  9. Goals of Functional Analysis • Identify Genes regulated by heredity and environment • Discover Candidate Genes (Gene Clusters, Gene Pathways) for Behavioral Regulation

  10. System Architecture BeeSpace Concepts Concepts SEQ Expressions Expressions Databases Bees Flies Documents Documents SEQ Community Community

  11. Behavioral Molecular Biologist Biologist Molecular Biology Literature Brain Gene Bee Bee Expression Literature Genome Profiles Flybase, Brain Region WormBase Localization Neuroscience Literature Neuro- scientist Concept Navigation in BeeSpace

  12. BeeSpace Information Sources • Biomedical Literature • Medline (medicine) • Biosis (biology) • Agricola, CAB Abstracts, Agris (agriculture) • Model Organisms (heredity) -Gene Descriptions (FlyBase, WormBase) • Natural Histories (environment) -BeeKeeping Books (Cornell Library, Harvard Press)

  13. BeeSpace Analysis Environment • Build Concept Space of Biomedical Literature for Functional Analysis of Bee Genes -Partition Literature into Community Collections -Extract and Index Concepts within Collections -Navigate Concepts within Documents -Follow Links from Documents into Databases Locate Candidate Genes in Related Literatures then follow links into Genome Databases

  14. Biological Concept Spaces Compute concept spaces for All of Biology BioSpace across entire biomedical literature 50M abstracts across 50K repositories Use Gene Ontology to partition literature into biological communities for functional analysis GO same scale as MeSH but adequate coverage? GO light on social behavior (biological process)

  15. 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

  16. Semantic region term Concept Space Concept Space CONCEPT SWITCHING • “Concept” versus “Term” • set of “semantically” equivalent terms • Concept switching • region to region (set to set) match

  17. Interactive Functional Analysis BeeSpace will enable users to navigate a uniform space of diverse databases and literature sources for hypothesis development and testing, with a software system that goes beyond a searchable database, using statistical literature analyses to discover functional relationships between genes and behavior. Genes to Behaviors Behaviors to Genes Concepts to Concepts Clusters to Clusters Navigation across Sources

  18. BeeSpace Analysis • Space Navigation -OLD Regions -NEW Regions -Sources towards Semantic Switching • Functional Analysis -MAPS Text -GENES Data -Sources towards Pathway Matching

  19. Space Navigation OLD Regions in Concept Space • Custom insect behavior • Ontology Gene, Behavior • Classification MeSH, Biosis • User Themes, Collections

  20. Space Navigation NEW Regions in Concept Space • Search text query • Search Switch set of terms • Region Switch set of documents • Spread follow to related

  21. Functional Analysis MAPS categories of text • Documents Relevance Ranked • Intrinsic Natural Bottom-Up • Extrinsic Artificial Top-Down

  22. Functional Analysis GENES concepts to data • Single Summarization e.g. FlyBase Genes • Related Set Meta-Analysis e.g. Behavior Maturation with EST array • Multiple Sets Intersection e.g. Nature plus Nurture with Genome array

  23. 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

  24. Towards the Interspace The Analysis Environment technology is GENERAL! BirdSpace? BeeSpace? PigSpace? CowSpace? BehaviorSpace? BrainSpace? BioSpace … Interspace

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