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BeeSpace Informatics: Interactive System for Functional Analysis. Bruce Schatz Institute for Genomic Biology University of Illinois at Urbana-Champaign www.beespace.uiuc.edu Fifth Annual Project Workshop IGB, Urbana IL May 22, 2009. Behavioral. Molecular. Biologist. Biologist.

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BeeSpace Informatics: Interactive System for Functional Analysis


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beespace informatics interactive system for functional analysis
BeeSpace Informatics:Interactive System for Functional Analysis

Bruce Schatz

Institute for Genomic Biology

University of Illinois at Urbana-Champaign

www.beespace.uiuc.edu

Fifth Annual Project Workshop

IGB, Urbana IL May 22, 2009

concept navigation in beespace

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
informatics from bases to spaces
Informatics: From Bases to Spaces

data Bases support genome data

e.g. FlyBase has sequences and maps

Genes annotated by GeneOntology and

linked to biological literature

information Spaces support biological literature

e.g. BeeSpace uses automatically generated

conceptual relationships to navigate functions

system architecture
System Architecture

BeeSpace

Concepts

Concepts

SEQ

Expressions

Expressions

Databases

Bees

Flies

Documents

Documents

SEQ

Community

Community

system versions
System Versions
  • V1 Filter Concept Graph
    • Search, Expand, Merge, Switch, Visualize
  • V2 Cluster Conceptual Groupings
    • Small Worlds (Natural), Language Model (Steerable), Concepts/Documents
  • V3 Summarize Gene Descriptions
    • Gene Extraction, Sentence Classification
  • V4 Analyze Functional Concepts
    • Concept Identification, Category Grouping
  • V5 Answer Entity Relationships
    • Entities, Relations, Templates
informatics researchers faculty
Informatics Researchers (Faculty)

Investigators:

  • Bruce Schatz, systems (Medical Information Science)
  • ChengXiang Zhai, algorithms (Computer Science)

Collaborators (students):

  • Saurabh Sinha, Computer Science
  • Jiawei Han, Computer Science
  • Sheng Zhong, Bioengineering
  • Nathan Price, Chemical & Biomolecular Engineering

Collaborators (advices):

  • John MacMullen, Library & Information Science
  • Dan Roth, Computer Science
  • Roxana Girju, Linguistics
  • Karrie Karahalios, Computer Science
informatics researchers staff
Informatics Researchers (Staff)
  • V1-V3
  • Todd Littell, research programmer
  • Jim Buell, research coordinator
  • Nyla Ismail, biology postdoc
  • Moushumi Sen Sarma, biology postdoc
  • V4-V5
  • David Arcoleo, research programmer
  • Barry Sanders, research programmer
  • Moushumi Sen Sarma, biology postdoc
  • Radhika Khetani, biology postdoc
informatics researchers students
Informatics Researchers (Students)

V1 Filter (parse)

Jing Jiang, Azadeh Shakery, Yuanhua Lv

V2 Cluster (group)

Brant Chee, Qiaozhu Mei, Peixiang Zhao

V3 Summarize (classify)

Xu Ling, Jing Jiang, Qiaozhu Mei, Xin He

V4 Analyze (annotate)

Xin He, Brant Chee, Moushumi Sarma, Xu Ling

V5 Answer (extract)

Xu Ling, Xin He, Yanen Li, Yue Lu

analysis environment features
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

analysis environment system
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

automatic categorization v2
Automatic Categorization v2

Sorting of Spaces based on Metadata

Sorting of Spaces based on Ontology

MeSH for Medline Abstracts

Gene Ontology computed for documents

Sorting of Spaces based on Clustering

Natural Maps from Small Worlds

Steerable Maps from Language Models

Semantic Indexing of Dynamic Spaces

Fast System enables Interactive Sorting!

semantics deeper and faster
Semantics Deeper and Faster

Semantic Indexing across all of Medline

Previous Attempts used Word Co-Occurrence

Now Phrase Parser works general-purpose

Now Mutual Information full differential

Parallel Optimization of MI Graph

Real-time Computation Shared Memory Cluster

Interactive on our 16PC 256GB RAM workerbee

Dynamic Spaces then Dynamic Semantic Indexing

Interactive Clustering Natural Map

Heuristic Approximation Small Worlds Graphs

dynamic clustering
Dynamic Clustering

Community Structure enables Dynamic Clustering with Large Vectors

automatic curation v3
Automatic Curation v3

Automatic Summarization of Genes

Retrieve relevant sentences about gene

Classify sentences into important aspects

protein domain, homolog/ortholog

expression pattern, phenotype function

regulatory element, genetic interaction

Generalizing to Biology Entities

Genes, anatomical, behavior, chemical

Question answering from biology factoids

Computed Curation from Literature

gene summary beespace
Gene Summary (BeeSpace)

Structured summary consists of relevant sentences covering 6 aspects of a gene

Gene Products (GP)

Expression Location (EL)

Sequence Information (SI)

Wild-type Function & Phenotypic Information (WFPI)

Mutant Phenotype (MP)

Genetical Interaction (GI)

gene summarizer new aspects
Gene Summarizer New Aspects

New categories (proposed by FlyBase curators)

GP + SI => PS (protein domain or structure)

SI => HO (homologs or orthologs)

EL => EP (spatial/temporal expression patterns)

SI => RE (regulatory element information)

WFPI + MP => PF (wild-type or mutant phenotype and function)

GI => IT (genetic or physical interaction)

New (beyond FlyBase) => PG (population genetics)

Utilize cross-domain information for improving the GS on other organisms.

beespace system v3
BeeSpace System v3

SPACES and REGIONS

Dynamic and Relative

Space is collection of documents

Region is collection of terms

  • Extract creates new Region from old Space
  • Map creates new Space from old Region
  • New from Old Spaces and Regions via merges
  • Summarize classifies Gene within Space
  • Annotate finds differential functional expression
beespace semantic operations
BeeSpace Semantic Operations
  • Merge (S1,S2) into S3
  • Summarize (S) into Gene classify

Extract

S

R

Map

S

R

new interface v4
New Interface v4

Single Window, Multiple Panes

Space Panel, Service Tabs

SPACES custom, system

FILTER searching, sorting

CLUSTER map natural and steerable

SUMMARIZE categorize using space

ANALYZE annotate using space

functional analysis v4
Functional Analysis v4

The software system goes beyond a searchable database, using statistical literature analyses to discover functional relationships between genes and behavior.

This research will enable all scientists who study bee genes to live on the frontier of integrative biology, where biotechnology enables routine expression analysis and bioinformatics enables functional analysis

unconstrained by pre-existing categories.

Genelist Analyzer v4

-Differential Expression of Gene Names against Space

-Background is custom made Literature Space

-Produces Concept List from Gene List

-Analyze using Concept Navigation and Gene Summarization

question answering v5
Question Answering v5

Entities and Relations

Question Answering templates

Entity

Gene, Anatomical

Behavior, Chemical

Relation

Regulation (Gene-Gene)

Expression (Gene-Anatomy)

Function (Gene-Behavior) Biological Process

Function (Gene-Chemical) Molecular Function

towards the interspace
Towards the Interspace

The Analysis Environment technology is GENERAL! BirdSpace? BeeSpace?

PigSpace? CowSpace?

ArthropodSpace? AnimalSpace?

BioSpace? MedSpace?