Download THE INTERSPACE PROTOTYPE An Analysis Environment for

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts
no text concepts found
Transcript
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
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
Power of Social Evolution



Language
Agriculture
Warfare
Humans do These, So do Social Insects
For Bees, we will carefully study
Foraging and Defense
Nature/Nurture Dissection I
Defense
Roles: Guard and Soldier
Nature:
Types of Bees (European, African)
Nurture: Levels of Threats (Alarm pheromones)
Nature/Nurture Dissection II
Hereditary Differences affecting:
onset age of Foraging
Subspecies: European (German, Italian)
and Africanized Honey Bees
High/Low Pollen Hoarding Lines
Nature/Nurture Dissection III
Social Manipulations affecting:
onset age of Foraging
Precocious vs Normal Forager
Normal vs Overage Nurse
Reverted Nurse
Socially Isolated
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
Goals of Functional Analysis

Identify Genes regulated by
heredity and environment

Discover Candidate Genes
(Gene Clusters, Gene Pathways) for
Behavioral Regulation
System Architecture
Concept Navigation in BeeSpace
Behavioral
Biologist
Bee
Literature
Molecular
Biology
Literature
Brain Gene
Expression
Profiles
Brain Region
Localization
Neuroscience
Literature
Neuroscientist
Molecular
Biologist
Bee
Genome
Flybase,
WormBase
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)
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
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)
BeeSpace Community Collections

Organism



Behavior



Social / Territorial
Foraging / Nesting
Development




Honey Bee / Fruit Fly
Song Bird / Soy Bean
Behavioral Maturation
Insect Development
Insect Communication
Structure


Fly Genetics / Fly Biochemistry
Fly Physiology / Insect Neurophysiology
CONCEPT SWITCHING

“Concept” versus “Term”


set of “semantically” equivalent terms
Concept switching

region to region (set to set) match
Semantic region
term
Concept Space
Concept Space
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
BeeSpace Analysis

Space Navigation
-OLD Regions
-NEW Regions
-Sources towards Semantic Switching

Functional Analysis
-MAPS Text
-GENES Data
-Sources towards Pathway Matching
Space Navigation
OLD Regions in Concept Space




Custom
insect behavior
Ontology
Gene, Behavior
Classification MeSH, Biosis
User
Themes, Collections
Space Navigation
NEW Regions in Concept Space




Search
Search Switch
Region Switch
Spread
text query
set of terms
set of documents
follow to related
Functional Analysis
MAPS



categories of text
Documents
Intrinsic
Extrinsic
Relevance Ranked
Natural Bottom-Up
Artificial Top-Down
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
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
Towards the Interspace
The Analysis Environment technology is
GENERAL!
BirdSpace? BeeSpace?
PigSpace? CowSpace?
BehaviorSpace? BrainSpace?
BioSpace
… Interspace