Analysis Environments Analysis Environments For Scientific Communities For Scientific Communities From Bases to Spaces From Bases to Spaces Bruce R. Schatz Institute for Genomic Biology University of Illinois at Urbana- Champaign [email protected],www.beespace.uiu c.edu Baker Center for Bioinformatics Iowa State University October 6, 2006
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Analysis Environments For Scientific Communities From Bases to Spaces
Analysis Environments For Scientific Communities From Bases to Spaces. Bruce R. Schatz Institute for Genomic Biology University of Illinois at Urbana-Champaign [email protected],www.beespace.uiuc.edu. Baker Center for Bioinformatics Iowa State University October 6, 2006. - PowerPoint PPT Presentation
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Analysis EnvironmentsAnalysis Environments For Scientific CommunitiesFor Scientific Communities
from Objects to Concepts from Syntax to Semantics Infrastructure is Interaction with Abstraction
Internet is packet transmission across computersInterspace is concept navigation across repositories
Towards the Interspace
THE THIRD WAVE OF NET EVOLUTION
PACKETS
OBJECTS
CONCEPTS
Technology
Engineering
Electrical
FORMAL
INFORMAL
(manual)
(automatic)
IEEE
communities
groups
individuals
LEVELS OF INDEXES
Post-Genome Informatics IComparative Analysis within the
Dry Lab of Biological Knowledge
Classical Organisms have Genetic Descriptions.There will be NO more classical organisms beyondMice and Men, Worms and Flies, Yeasts and Weeds.
Must use comparative genomics on classical organismsVia sequence homologies and literature analysis.
Post-Genome Informatics IIFunctional Analysis within the
Dry Lab of Biological Knowledge
Automatic annotation of genes to standard classifications, e.g. Gene Ontology via homology on computed protein sequences.
Automatic analysis of functions to scientific literature, e.g. concept spaces via text extractions. Thus must use functions in literature descriptions.
Informatics: From Bases to Spacesdata Bases support genome datae.g. FlyBase has sequences and mapsGenes annotated by GeneOntology and
linked to biological literature
information Spaces support biological literaturee.g. BeeSpace uses automatically generated conceptual relationships to navigate functions
BeeSpace FIBR ProjectBeeSpace 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
System Architecture
Concept Navigation in BeeSpace
NeuroscienceLiterature
MolecularBiology
Literature
BeeLiterature
Flybase,WormBase
BeeGenome
Brain RegionLocalization
Brain GeneExpression
Profiles
BehavioralBiologist
MolecularBiologist
Neuro-scientist
V1 BeeSpace Community Collections
Organism Honey Bee / Fruit Fly Song Bird / Soy Bean
Behavior Social / Territorial Foraging / Nesting
Development Behavioral Maturation Insect Development Insect Communication
set of “semantically” equivalent terms Concept switching
region to region (set to set) match
term
Semantic region
Concept SpaceConcept Space
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
Well Characterized Gene
Poorly Characterized Gene
Gene Summarization, BeeSpace V2
Collaboration across Users
Category Browse (Collection)
Category Browse (Search)
PlantSpace Examples
Interactive Functional AnalysisBeeSpace will enable users to navigate a uniform space of
diverse databases and literature sources for hypothesis development and testing, with a software system beyond a searchable database, using literature analyses to discover functional relationships between genes and behavior.
Genes to BehaviorsBehaviors to GenesConcepts to ConceptsClusters to ClustersNavigation across Sources
BeeSpace Information SourcesGeneral for All Spaces: Scientific Literature-Medline, Biosis, CAB Abstracts Genome Databases-GenBank, ProteinDataBank, ArrayExpress
Special for BeeSpace: Model Organisms (heredity)-Gene Descriptions (FlyBase, WormBase) Natural Histories (environment)-BeeKeeping Books (Cornell, Harvard)
XSpace 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 SoySpace Organize Genome Databases (SoyBase) Partition Scientific Literature for SoyBean Gene Descriptions from Models (TAIR) Natural Histories from Population Databases
Key to Functional Analysis is Special Sources Collecting Appropriate Text about Genes Extracting Adequate Data about Histories Leverage is National Archives of germplasm
and Historical Records for soybean crops
Towards the InterspaceThe Analysis Environment technology is