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

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

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

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 Beehavior

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 BeeSpace Concepts Concepts SEQ Expressions Expressions Databases Bees Flies Documents Documents SEQ Community Community

17. 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

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. 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

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. Heredity Environment Nature and Nurture both act on the genome

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