BeeSpace: An Interactive Environment for Functional Analysis of Social Behavior Bruce Schatz Institute for Genomic Biology University of Illinois at Urbana-Champaign.

Slides:



Advertisements
Similar presentations
Classification & Your Intranet: From Chaos to Control Susan Stearns Inmagic, Inc. E-Libraries E204 May, 2003.
Advertisements

Zoology 305 Library Databases/Indexes Lab Goals for session: 1) Meet your librarian Kevin Messner 2) Understand.
NCBI/WHO PubMed/Hinari Course NCBI Literature Databases: PubMed Background.
Introduction to BioConductor Friday 23th nov 2007 Ståle Nygård Statistical methods and bioinformatics for the analysis of microarray.
Prof. Carolina Ruiz Computer Science Department Bioinformatics and Computational Biology Program WPI WELCOME TO BCB4003/CS4803 BCB503/CS583 BIOLOGICAL.
The Thomson Reuters CITATION CONNECTION Digital Library st March – 3 rd April 2014, Jasná David Horký Country Manager – Central and Eastern Europe.
The design, construction and use of software tools to generate, store, annotate, access and analyse data and information relating to Molecular Biology.
Who am I Gianluca Correndo PhD student (end of PhD) Work in the group of medical informatics (Paolo Terenziani) PhD thesis on contextualization techniques.
NATIONAL LIBRARY OF MEDICINE The PubMed ID and Entrez, PubMed and PubMed Central Edwin Sequeira National Center for Biotechnology Information June 21,
Computational Biology Workshop, July 24,, 2007 BeeSpace: Integrating the Curriculum by Connecting Learning and Life Chip Bruce Library and Information.
Bioinformatics Director Lecture University of Michigan Medical School February 7, 2000 Building Analysis Environments Beyond the Genome and the Web Bruce.
Michigan Life Sciences Corridor Bioinformatics, University of Michigan March 14, 2001 Building Analysis Environments Beyond the Genome and the Web Bruce.
1 Enriching UK PubMed Central SPIDER launch meeting, Wolfson College, Oxford Paul Davey, UK PubMed Central Engagement Manager.
Jeffery Loo NLM Associate Fellow ’03 – ’05 chemicalinformaticsforlibraries.
Fungal Semantic Web Stephen Scott, Scott Henninger, Leen-Kiat Soh (CSE) Etsuko Moriyama, Ken Nickerson, Audrey Atkin (Biological Sciences) Steve Harris.
Bioinformatics: a Multidisciplinary Challenge Ron Y. Pinter Dept. of Computer Science Technion March 12, 2003.
We are developing a web database for plant comparative genomics, named Phytome, that, when complete, will integrate organismal phylogenies, genetic maps.
Using the Drupal Content Management Software (CMS) as a framework for OMICS/Imaging-based collaboration.
BeeSpace: An Interactive Environment for Analyzing Nature and Nurture in Societal Roles Bruce Schatz Institute for Genomic Biology University of Illinois.
Bioinformatics Jan Taylor. A bit about me Biochemistry and Molecular Biology Computer Science, Computational Biology Multivariate statistics Machine learning.
Ontologies: Making Computers Smarter to Deal with Data Kei Cheung, PhD Yale Center for Medical Informatics CBB752, February 9, 2015, Yale University.
Srihari-CSE730-Spring 2003 CSE 730 Information Retrieval of Biomedical Text and Data Inroduction.
9/30/2004TCSS588A Isabelle Bichindaritz1 Introduction to Bioinformatics.
CS598CXZ Course Summary ChengXiang Zhai Department of Computer Science University of Illinois, Urbana-Champaign.
Analysis Environments For Scientific Communities From Bases to Spaces Bruce R. Schatz Institute for Genomic Biology University of Illinois at Urbana-Champaign.
Bioinformatics Seminar Department of Computer Science, UIUC February 25, 2005 Analysis Environments For Functional Genomics Bruce R. Schatz CANIS Laboratory.
Information Systems Basic Core Specialization Clinical Imaging BioInformatics Public Health Computer Science Methods (formal models) Biomedical Decision.
Bioinformatics and medicine: Are we meeting the challenge?
Session II: Scientific Publishing and Semantic Web W3C Semantic Web for Life Sciences Workshop October 27, 2004 Moderator: Alan R. Aronson.
University of Illinois at Urbana-Champaign INSTITUTE FOR GENOMIC BIOLOGY BeeSpace: An Interactive Environment for Functional Analysis of Social Behavior.
Building Biodiversity Information Education: Next Generation Bioinformaticians P. Bryan Heidorn Carole Palmer Dan Wright Graduate School of Library and.
International Conference on Digital Libraries November 16, 2000 Kyoto, Japan Digital Libraries of Community Knowledge: The Coming World of the Interspace.
IEEE Knowledge Media Networking KMN’02 Keynote Address, CRL, Kyoto Japan, July 11, 2002 Concept Switching in the Interspace: Networking Infrastructure.
Helping scientists collaborate BioCAD. ©2003 All Rights Reserved.
CNI Spring Meeting April 26, 1999 Washington, DC THE NET OF THE 21st CENTURY: Concepts across the Interspace Bruce Schatz CANIS Laboratory Graduate School.
Cell Signaling Ontology Takako Takai-Igarashi and Toshihisa Takagi Human Genome Center, Institute of Medical Science, University of Tokyo.
Department of Computer Science seminar University of Illinois, February 14, 2005 The Evolution of the Net: Predicting Global Infrastructure Bruce R. Schatz.
University of Illinois at Urbana-Champaign BeeSpace Navigator v4.0 and Gene Summarizer beespace.uiuc.edu `
BeeSpace: An Interactive Environment for Analyzing Nature and Nurture in Societal Roles Bruce Schatz Institute for Genomic Biology University of Illinois.
Protein Information Resource Protein Information Resource, 3300 Whitehaven St., Georgetown University, Washington, DC Contact
The Gene Ontology and its insertion into UMLS Jane Lomax.
Indexing Mathematical Abstracts by Metadata and Ontology IMA Workshop, April 26-27, 2004 Su-Shing Chen, University of Florida
Sharing Ontologies in the Biomedical Domain Alexa T. McCray National Library of Medicine National Institutes of Health Department of Health & Human Services.
RESEARCH – DOING AND ANALYSING Gavin Coney Thomson Reuters May 2009.
Using Domain Ontologies to Improve Information Retrieval in Scientific Publications Engineering Informatics Lab at Stanford.
CODE (Committee on Digital Environment) July 26, 2000 Rice University THE NET OF THE 21st CENTURY: Concepts across the Interspace Bruce Schatz CANIS Laboratory.
Ontologies Working Group Agenda MGED3 1.Goals for working group. 2.Primer on ontologies 3.Working group progress 4.Example sample descriptions from different.
Third Annual BeeSpace Workshop, May 21-22, BeeSpace Education Research Chip Bruce Library and Information Science, UIUC Susan.
Mining the Biomedical Research Literature Ken Baclawski.
Workshop on The Transformation of Science Max Planck Society, Elmau, Germany June 1, 1999 TOWARDS INFORMATIONAL SCIENCE Indexing and Analyzing the Knowledge.
Graduate School of Informatics Kyoto University, November 21, 2001 Technologies of the Interspace Peer-Peer Semantic Indexing Bruce Schatz CANIS Laboratory.
Bioinformatics and Computational Biology
Revolutionary System Models, The Net, & The Public Interest The Interspace Prototype ( ) Digital Libraries Initiative ( ) Worm Community.
Revolution & Kids: Building the Future of the Net & Understanding the Structures of the World Bruce R. Schatz CANIS - Community Systems Laboratory University.
BeeSpace Informatics: Interactive System for Functional Analysis Bruce Schatz Institute for Genomic Biology University of Illinois at Urbana-Champaign.
Opportunities for Text Mining in Bioinformatics (CS591-CXZ Text Data Mining Seminar) Dec. 8, 2004 ChengXiang Zhai Department of Computer Science University.
Analysis Environments For Functional Genomics Bruce R. Schatz Institute for Genomic Biology University of Illinois at Urbana-Champaign
University of Illinois at Urbana-Champaign. BeeSpace Project 5-year NSF-funded project Project Goals  Develop open bioinformatics resources  Support.
An Introduction to NCBI & BLAST National Center for Biotechnology Information Richard Johnston Pasadena City College.
1 CS 430: Information Discovery Lecture 26 Architecture of Information Retrieval Systems 1.
NCBI: something old, something new. What is NCBI? Create automated systems for knowledge about molecular biology, biochemistry, and genetics. Perform.
Joined up ontologies: incorporating the Gene Ontology into the UMLS.
1 Survey of Biodata Analysis from a Data Mining Perspective Peter Bajcsy Jiawei Han Lei Liu Jiong Yang.
Genomic Medicine Grid Juan Pedro Sánchez Merino Instituto de Salud Carlos III
Informatics for Scientific Data Bio-informatics and Medical Informatics Week 9 Lecture notes INF 380E: Perspectives on Information.
Graduate School of Informatics Kyoto University, November 14, 2001 Functions of the Interspace Infrastructure for Concept Spaces Bruce Schatz CANIS Laboratory.
Biological Databases By: Komal Arora.
Applications of the Interspace Analysis for Community Repositories
KnowEnG: A SCALABLE KNOWLEDGE ENGINE FOR LARGE SCALE GENOMIC DATA
Introduction to Bioinformatics
Presentation transcript:

BeeSpace: An Interactive Environment for Functional Analysis of Social Behavior Bruce Schatz Institute for Genomic Biology University of Illinois at Urbana-Champaign First Annual BeeSpace Workshop University of Illinois June 6, 2005

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 Bee [Biology] gene expressions Space Space [Informatics] concept navigations

for Social Beehavior

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

for Functional Analysis

Complex Systems II Understanding Functional Analysis Molecular Mechanisms of Social Behavior Can only be Discovered via the Interactive Navigations of Distributed Systems Interspace The Interspace is the next generation of of the Net (beyond the Web) Where Concept Navigation across Distributed Communities is routine

System Architecture

Post-Genome Informatics Classical Organisms have extensive Genetic Descriptions! There will be NO more classical organisms beyond Mice 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 Science Computational 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 for Functional Mining of Information Sources Comparative Analysis within the Dry Lab of Biological Knowledge

Biology: The Model Organism The Western Honey Bee, Apis mellifera has 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 Spaces data Bases support genome data e.g. FlyBase has sequences and maps Genes annotated by GeneOntology and linked to biological literature BeeBase (Christine Elsik, Texas A&M) Uses computed homologies to annotate genes information Spaces support biological literature e.g. BeeSpace uses automatically generated conceptual relationships to navigate functions

Project Investigators BeeSpace project is NSF FIBR flagship Frontiers Integrative Biological Research, $5M for 5 years at University of Illinois Biology Gene Robinson, Entomology (behavioral expression) Susan Fahrbach, Wake Forest (anatomical localization) Sandra Rodriguez-Zas, Animal Sciences (data analysis) Informatics Bruce Schatz, Library & Information Science (systems) ChengXiang Zhai, Computer Science (text analysis) Chip Bruce, Library & Information Science (users )

Education and Outreach Explaining Social Behavior at all Levels Graduate Students and Postdocs as System Users 5 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 GOALS Analyze the relative contributions of Nature and Nurture in Societal 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 BeeSpace

BeeSpace 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 Implementation Natural Language Processing Identify noun phrases Recognize biological entities Statistical Information Retrieval Compute statistical contexts Support conceptual navigation Network Information System Concept switch across community collections Semantic Links into biological databases

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)

Worm Community System (1991) WCS Information Sources Literature Biosis, Medline, newsletters, meetings Data Genes, Maps, Sequences, strains, cells WCS Interactive Environment Browsingsearch, navigation Filteringselection, analysis Sharinglinking, publishing WCS: 250 users at 50 labs across Internet (1991) NSF National Collaboratories Flagship

WCS Molecular

WCS Cellular

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

Concept Search

Concept Navigation

Retrieve Document

CONCEPT SWITCHING “Concept” versus “Term” set of “semantically” equivalent terms Concept switching region to region (set to set) match term Semantic region Concept Space

Biomedical Session

Categories and Concepts

Concept Switching

Document Retrieval

Biological Concept Spaces (2006) 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)

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 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 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. CowSpace Leverage in AIPL Databases

Towards the Interspace The Analysis Environment technology is GENERAL ! BirdSpace? BeeSpace? PigSpace? CowSpace? BehaviorSpace? BrainSpace? BioSpace … Interspace