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

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Title: 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

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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

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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 AM)
  • 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
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
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
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

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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

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