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BeeSpace: An Interactive Environment for Analyzing Nature and Nurture in Societal Roles Bruce Schatz Institute for Genomic Biology University of Illinois.

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Presentation on theme: "BeeSpace: An Interactive Environment for Analyzing Nature and Nurture in Societal Roles Bruce Schatz Institute for Genomic Biology University of Illinois."— Presentation transcript:

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

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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 ForagingDefense 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 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 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 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

11 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

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15 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)

16 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

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

18 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

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

20 Space Navigation OLD Regions in Concept Space Custominsect behavior OntologyGene, Behavior ClassificationMeSH, Biosis UserThemes, Collections

21 Space Navigation NEW Regions in Concept Space Searchtext query Search Switchset of terms Region Switchset of documents Spreadfollow to related

22 Functional Analysis MAPS categories of text DocumentsRelevance Ranked IntrinsicNatural Bottom-Up ExtrinsicArtificial Top-Down

23 Functional Analysis GENES concepts to data SingleSummarization e.g. FlyBase Genes Related SetMeta-Analysis e.g. Behavior Maturation with EST array Multiple SetsIntersection e.g. Nature plus Nurture with Genome array

24 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

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


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