BeeSpace: An Interactive Environment

for Functional Analysis of Social Behavior

BeeSpace: An Interactive Environment

for Functional Analysis of Social Behavior

Bruce SchatzInstitute for Genomic Biology

University of Illinois at Urbana-Champaignwww.beespace.uiuc.edu

First Annual BeeSpace Workshop University of Illinois June 6, 2005

BeeSpace FIBR ProjectBeeSpace FIBR Project

BeeSpace project is NSF FIBR flagshipFrontiers 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 BeeBee [Biology] gene expressions SpaceSpace [Informatics] concept navigations

for Social Beehavior for Social Beehavior

Complex Systems IComplex 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

for Functional Analysisfor Functional Analysis

Complex Systems IIComplex Systems II

Understanding Functional Analysis

Molecular Mechanisms of Social Behavior Can only be Discovered via the Interactive Navigations of Distributed Systems

The InterspaceInterspace is the next generation of of the Net (beyond the Web) Where Concept Navigation across

Distributed Communities is routine

System ArchitectureSystem Architecture

Post-Genome InformaticsPost-Genome InformaticsClassical Organisms have extensive Genetic Descriptions!There will be NO more classical organisms beyondMice and Men other than Worms and Flies, Yeasts and Weeds.

So must use comparative genomics to classical organisms,Via sequence homologies and literature analysis.

Automatic annotation of genes to standard classifications,Such as Gene Ontology via sequence homology. Automatic analysis of functions to scientific literature,Such as concept spaces via text mining.

Descriptions in Literature MUST be used for future interactive environments for functional analysis!

Informational ScienceInformational ScienceComputational Science is the Third Branch of Science

(beyond Experimental and Theoretical)

Genes are Computed, Proteins are Computed, Sequence “equivalences” are Computed.

Informational Science is coming to be accepted as The Fourth Branch of Science

Based on Information Science technologies forFunctional Mining of Information Sources

Comparative Analysis within theComparative Analysis within theDry Lab of Biological KnowledgeDry Lab of Biological Knowledge

Biology: The Model OrganismBiology: The Model Organism

The Western Honey Bee, Apis melliferahas become a primary model for social behavior

Complex social behavior in controllable urban environment Normal Behavior – honey bees live in the wild Controllable Environment – hives can be modified

Small size manageable with current genomic technology Capture bees on-the-fly during normal behavior Record gene expressions for whole-brain or brain-region

(Note logistical limitations with bees and expressions)

Informatics: From Bases to SpacesInformatics: From Bases to Spaces

data Bases support genome datae.g. FlyBase has sequences and mapsGenes annotated by GeneOntology and

linked to biological literature

BeeBase (Christine Elsik, Texas A&M)Uses computed homologies to annotate genes

information Spaces support biological literaturee.g. BeeSpace uses automatically generated conceptual relationships to navigate functions

Project InvestigatorsProject Investigators

BeeSpace project is NSF FIBR flagshipFrontiers Integrative Biological Research, $5M for 5 years at University of Illinois

BiologyGene Robinson, Entomology (behavioral expression)Susan Fahrbach, Wake Forest (anatomical localization)Sandra Rodriguez-Zas, Animal Sciences (data analysis)

InformaticsBruce Schatz, Library & Information Science (systems) ChengXiang Zhai, Computer Science (text analysis)Chip Bruce, Library & Information Science (users)

Education and OutreachEducation and Outreach

Explaining Social Behavior at all Levels

Graduate Students and Postdocs as System Users5 early adopter labs then 15 international labs

Undergraduates to plan Bioinformatics Course through Susan Fahrbach at Wake Forest

Run Workshop for Middle School Minorities through UIUC SummerMath (George Reese)

University High School Biology Courses (David Stone) Home Hi Middle School for Girls Science (Jim Buell)

BeeSpace GOALSBeeSpace GOALS

Analyze the relative contributions of Analyze the relative contributions of Nature and Nurture in Nature and Nurture in

Societal Roles in Honey BeesSocietal Roles in Honey Bees

Experimentally measure differential 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

Concept Navigation in BeeSpaceConcept Navigation in BeeSpace

NeuroscienceLiterature

MolecularBiology

Literature

BeeLiterature

Flybase,WormBase

BeeGenome

Brain RegionLocalization

Brain GeneExpression

Profiles

BehavioralBiologist

MolecularBiologist

Neuro-scientist

BeeSpace Software EnvironmentBeeSpace Software Environment Will build a 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

BeeSpace Software ImplementationBeeSpace Software Implementation Natural Language Processing Identify noun phrasesRecognize biological entities

Statistical Information Retrieval Compute statistical contextsSupport conceptual navigation

Network Information SystemConcept switch across community collectionsSemantic Links into biological databases

BeeSpace Information SourcesBeeSpace 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)

Worm Community System (1991)Worm Community System (1991) WCS Information SourcesLiterature Biosis, Medline, newsletters, meetings

Data Genes, Maps, Sequences, strains, cells

WCS Interactive EnvironmentBrowsing search, navigationFiltering selection, analysisSharing linking, publishing

WCS: 250 users at 50 labs across Internet (1991)NSF National Collaboratories Flagship

WCSMolecular

WCS Cellular

Medical Concept Spaces (1998)Medical Concept Spaces (1998)

Medical Literature (Medline, 10M abstracts) Partition with Medical Subject Headings (MeSH)

Community is all abstracts classified by core term 40M abstracts containing 280M concepts computation is 2 days on NCSA Origin 2000

Simulating World of Medical Communities 10K repositories with > 1K abstracts (1K with > 10K)

Navigation in MedSpaceNavigation in MedSpace

For a patient with Rheumatoid Arthritis Find a drug that reduces the pain (analgesic) but does not cause stomach (gastrointestinal) bleeding

Choose DomainChoose Domain

Concept SearchConcept Search

Concept NavigationConcept Navigation

Retrieve DocumentRetrieve Document

CONCEPT SWITCHINGCONCEPT SWITCHING

“Concept” versus “Term” set of “semantically” equivalent terms

Concept switching region to region (set to set) match

term

Semantic region

Concept SpaceConcept Space

Biomedical SessionBiomedical Session

Categories and ConceptsCategories and Concepts

Concept SwitchingConcept Switching

Document RetrievalDocument Retrieval

Biological Concept Spaces (2006)Biological Concept Spaces (2006)

Compute concept spaces for All of BiologyBioSpace 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)

Interactive Functional AnalysisInteractive 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 BehaviorsBehaviors to GenesConcepts to ConceptsClusters to ClustersNavigation across Sources

BeeSpace Information SourcesBeeSpace 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,

SCD, TAIR)

Special Sources for BeeSpace:-Natural History Books (Cornell Library, Harvard Press)

XSpace Information SourcesXSpace Information SourcesOrganize Genome Databases (XBase)Compute Gene Descriptions from Model OrganismsPartition Scientific Literature for Organism XCompute XSpace using Semantic Indexing

Boost the Functional Analysis from Special SourcesCollecting Useful Data about Natural Historiese.g. CowSpace Leverage in AIPL Databases

Towards the InterspaceTowards the Interspace

The Analysis Environment technology is GENERAL!

BirdSpace? BeeSpace?PigSpace? CowSpace? BehaviorSpace? BrainSpace?

BioSpace… Interspace