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Meeting the Bioinformatics Meeting the Bioinformatics Challenges of Functional Challenges of Functional
GenomicsGenomics
VanBUGVanBUG
11 September 200311 September 2003
The TIGR Gene Index TeamThe TIGR Gene Index TeamFoo CheungFoo Cheung
Svetlana KaramychevaSvetlana KaramychevaYudan LeeYudan Lee
Babak ParviziBabak ParviziGeo PerteaGeo Pertea
Razvan SultanaRazvan SultanaJennifer TsaiJennifer Tsai
John QuackenbushJohn QuackenbushJoseph WhiteJoseph White
Funding provided by the Department of EnergyFunding provided by the Department of Energyand the National Science Foundationand the National Science Foundation
TIGR Human/Mouse/Arabidopsis TIGR Human/Mouse/Arabidopsis Expression TeamExpression Team
Emily ChenEmily ChenBryan FrankBryan Frank
Renee GaspardRenee GaspardJeremy HassemanJeremy Hasseman
Lara LinfordLara LinfordFenglong LiuFenglong LiuSimon KwongSimon Kwong
John QuackenbushJohn QuackenbushShuibang WangShuibang WangYonghong WangYonghong Wang
Ivana YangIvana YangYan YuYan Yu
Array Software Hit TeamArray Software Hit TeamNirmal BhagabatiNirmal Bhagabati
John BraistedJohn BraistedTracey CurrierTracey Currier
Jerry LiJerry LiWei LiangWei Liang
John QuackenbushJohn QuackenbushAlexander I. SaeedAlexander I. Saeed
Vasily SharovVasily SharovMathangi ThiagarajanMathangi Thiagarajan
Joseph WhiteJoseph WhiteAssistantAssistantSue MineoSue MineoFunding provided by the National Cancer Institute,Funding provided by the National Cancer Institute,
the National Heart, Lung, Blood Institute,the National Heart, Lung, Blood Institute,and the National Science Foundationand the National Science Foundation
H. Lee Moffitt Center/USFH. Lee Moffitt Center/USFTimothy J. YeatmanTimothy J. Yeatman
Greg BloomGreg Bloom
TIGR PGA CollaboratorsTIGR PGA CollaboratorsNorman LeeNorman LeeRenae MalekRenae Malek
Hong-Ying WangHong-Ying WangTruong LuuTruong Luu
Bobby BehbahaniBobby Behbahani
TIGR Faculty, IT Group, and StaffTIGR Faculty, IT Group, and Staff
<johnq@tigr.org><johnq@tigr.org>AcknowledgmentsAcknowledgments
PGA CollaboratorsPGA CollaboratorsGary Churchill (TJL)Gary Churchill (TJL)Greg Evans (NHLBI)Greg Evans (NHLBI)Harry Gavras (BU)Harry Gavras (BU)
Howard Jacob (MCW)Howard Jacob (MCW)Anne Kwitek (MCW)Anne Kwitek (MCW)Allan Pack (Penn)Allan Pack (Penn)
Beverly Paigen (TJL)Beverly Paigen (TJL)Luanne Peters (TJL)Luanne Peters (TJL)
David Schwartz (Duke)David Schwartz (Duke)
EmeritusEmeritusJennifer Cho (TGI)Jennifer Cho (TGI)
Ingeborg Holt (TGI)Ingeborg Holt (TGI)Feng Liang (TGI)Feng Liang (TGI)
Kristie Abernathy (Kristie Abernathy (A)A)Sonia Dharap (Sonia Dharap (A)A)
Julie Earle-Hughes (Julie Earle-Hughes (A)A)Cheryl Gay (Cheryl Gay (A)A)Priti Hegde (Priti Hegde (A)A)
Rong Qi (Rong Qi (A)A)Erik Snesrud (Erik Snesrud (A)A)Heenam Kim (Heenam Kim (A)A)
<johnq@tigr.org><johnq@tigr.org>
AcknowledgmentsAcknowledgments
Thanks to Thanks to SyntekSyntek, Inc. , Inc. <http://www.syntek.com><http://www.syntek.com>
for GeneShaving MeV module and assistance for GeneShaving MeV module and assistance with MyMADAMwith MyMADAM
Thanks to Thanks to DataNautDataNaut, Inc. , Inc. <http://www.datanaut.com><http://www.datanaut.com>
for RelNet and Terrain Map modules and for RelNet and Terrain Map modules and assistance with Client/Server MeVassistance with Client/Server MeV
<tm4@tigr.org><tm4@tigr.org>
Science is built with facts as a house is with Science is built with facts as a house is with stones – but a collection of facts is no more a stones – but a collection of facts is no more a science than a heap of stones is a house.science than a heap of stones is a house. – – Jules Henri PoincareJules Henri Poincare
There are 10There are 101111 stars in the galaxy. That stars in the galaxy. That used to be a huge number. But it's only a used to be a huge number. But it's only a hundred billion. It's less than the national hundred billion. It's less than the national deficit! We used to call them astronomical deficit! We used to call them astronomical
numbers. Now we should call them numbers. Now we should call them economical numbers.economical numbers.
- Richard Feynman, physicist, Nobel laureate - Richard Feynman, physicist, Nobel laureate (1918-1988)(1918-1988)
Microarray Analysis at TIGRMicroarray Analysis at TIGR
Step 1: Experimental DesignStep 1: Experimental Design
Step 2: Data CollectionStep 2: Data Collection
Step 3: Data AnalysisStep 3: Data Analysis
Step 4: Consulting with the ArraySW gang in the trailerStep 4: Consulting with the ArraySW gang in the trailer
Step 5: Sharing data with our collaboratorsStep 5: Sharing data with our collaborators
Select array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
Steps in the ProcessSteps in the Process
Select array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
Steps in the ProcessSteps in the Process
TIGR Gene Indices TIGR Gene Indices home page home page
www.tigr.org/tdb/tgiwww.tigr.org/tdb/tgi
~60 species~60 species
>16,000,000 sequences>16,000,000 sequences
~60 species~60 species
>16,000,000 sequences>16,000,000 sequences
TGICL Tools are available – with more comingTGICL Tools are available – with more coming
Available with sourceAvailable with source
Geo PerteaGeo PerteaRazvan SultanaRazvan Sultana
Valentin AntonescuValentin Antonescu
High stringency pair-High stringency pair-wise comparisons to wise comparisons to
buildbuild ClustersClusters
Gene Index Assembly processGene Index Assembly process
reduce reduce redundancyredundancy
Expressed Transcripts (ET)Expressed Transcripts (ET)from GenBank CDSfrom GenBank CDS
remove vector, poly-A, remove vector, poly-A, adapter,mitochondrial adapter,mitochondrial
and ribosomal sequenceand ribosomal sequence
ESTs from ESTs from GenBank GenBank (dbEST)(dbEST)
TIGR ESTsTIGR ESTs
Each cluster is Each cluster is assembled to obtainassembled to obtain
Tentative Tentative ConsensusConsensus
sequences (TCs)sequences (TCs)
Annotate TCs Annotate TCs and releaseand release
The Mouse Gene IndexThe Mouse Gene Index <http://www.tigr.org/tdb/mgi><http://www.tigr.org/tdb/mgi>
A TC ExampleA TC Example
Babak ParviziBabak Parvizi
GO Terms GO Terms and EC Numbersand EC Numbers
The TIGR Gene IndicesThe TIGR Gene Indices <http://www.tigr.org.tdb/tdb/tgi><http://www.tigr.org.tdb/tdb/tgi>
Dan Lee, Ingeborg HoltDan Lee, Ingeborg Holt
Tentative OrthologuesTentative Orthologues
And ParaloguesAnd Paralogues
Building TOGs: Reflexive, Transitive ClosureBuilding TOGs: Reflexive, Transitive Closure
Thanks to Woytek Makałowski and Mark Boguski Thanks to Woytek Makałowski and Mark Boguski
TOGA: An Sample Alignment: TOGA: An Sample Alignment: bithoraxoid-like proteinbithoraxoid-like protein
Gene Finding in HumansGene Finding in Humans is easy!is easy!
Razvan SultanaRazvan Sultana
Gene Finding in HumansGene Finding in Humans is easy?is easy?
Razvan SultanaRazvan Sultana
Gene Finding in HumansGene Finding in Humans is difficult?is difficult?
Razvan SultanaRazvan Sultana
Gene Finding in HumansGene Finding in Humans is difficult?is difficult?
Razvan SultanaRazvan Sultana
A genome and its annotation is A genome and its annotation is onlyonly a a hypothesis that must be tested.hypothesis that must be tested.
http://pga.tigr.org/tools.shtmlhttp://pga.tigr.org/tools.shtml
RESOURCERER RESOURCERER Jennifer TsaiJennifer Tsai
RESOURCERER: An ExampleRESOURCERER: An Example
RESOURCERER: Using Genetic MarkersRESOURCERER: Using Genetic Markers
Just added: Integrated QTLsJust added: Integrated QTLs
Select array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
Steps in the ProcessSteps in the Process
SOPs are availableSOPs are available
<http://pga.tigr.org/tools.shtml><http://pga.tigr.org/tools.shtml>
cDNA/template prepcDNA/template prep PCR purificationPCR purification
PrintingPrinting RNA labelingRNA labeling
HybridizationHybridization
Coming: Data QC SOPComing: Data QC SOP
What data should we collect?What data should we collect?Nature GeneticsNature Genetics 29, December 2001 29, December 2001
<http://www.mged.org><http://www.mged.org>MAGE-ML – XML-based data exchange formatMAGE-ML – XML-based data exchange format
EVERYTHINGEVERYTHING
MIAME Relational SchemaMIAME Relational Schema
What’s Wrong with MIAME?MIAME was designed as a model for capturing information MIAME was designed as a model for capturing information necessary to create public databases.necessary to create public databases.
MIAME-based databases lack LIMS capabilities, which are MIAME-based databases lack LIMS capabilities, which are necessary for large-scale studies.necessary for large-scale studies.
We do not want to store images in our database for We do not want to store images in our database for practical reasons – limited space.practical reasons – limited space.
We needed to develop a variety of tools adapted to our We needed to develop a variety of tools adapted to our existing infrastructure and existing infrastructure and legacy data and databaseslegacy data and databases..
Probes are labeled and applied to the arraysProbes are labeled and applied to the arrays An “experiment” is a hybridizationAn “experiment” is a hybridization A “study” is a collection of hybridization experimentsA “study” is a collection of hybridization experiments
MAD Microarray Database SchemaMAD Microarray Database Schema
Conceptual Schema: MADConceptual Schema: MAD
ProtocolProtocolPrimer_pairPrimer_pair
PrimerPrimer
PCRPCR
New_plateNew_plate SlideSlide Slide_typeSlide_type SpotSpot
ScanScan AnalysisAnalysis NormalizeNormalize
ExperimentExperiment ExpressionExpression
Expt_probeExpt_probe
HybHyb
StudyStudy
ProbeProbe Probe_sourceProbe_source
GeneGene
CloneClone
MADAM: Microarray Data ManagerMADAM: Microarray Data Manager
Available with source and MySQLAvailable with source and MySQL
Marie-Michelle Cordonnier-Pratt, UGAMarie-Michelle Cordonnier-Pratt, UGAconverted MySQL to Oracle and madeconverted MySQL to Oracle and madeMADAM work!MADAM work!
ExpDesignerExpDesigner
Select array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
Steps in the ProcessSteps in the Process
Microbial
ORFs
Design PCR Primers
PCR Products
Eukaryotic
Genes
Select cDNA clones
PCR Products
Microarray Overview IMicroarray Overview I
For each plate set,For each plate set,many identical replicasmany identical replicas
Microarray SlideMicroarray Slide(with 60,000 or more(with 60,000 or more
spotted genes)spotted genes)
+
Microtiter PlateMicrotiter Plate
Many different plates Many different plates containing different genescontaining different genes
Microarray OverviewMicroarray Overview
PCR AmplificationPCR Amplification
Selected GenesSelected Genes
Primer DesignPrimer Design
Gel-based ScoringGel-based Scoring
Primer SynthesisPrimer Synthesis
MAD
PCR ScorerPCR Scorer
Reads/loads primer data file Reads/loads primer data file to MAD and allows PCR data entry,to MAD and allows PCR data entry,
and translation of 96 and translation of 96 384. 384.(Alex Saeed, developer and maintainer(Alex Saeed, developer and maintainer
enhancements: Wedge Smith)enhancements: Wedge Smith)
Clone SelectionClone Selection
The Beast: Microarray Robot from Intelligent AutomationThe Beast: Microarray Robot from Intelligent Automation <http://www.ias.com><http://www.ias.com>
Additional Software for Arrays: SchedulerAdditional Software for Arrays: Scheduler
Microarray SchedulerMicroarray SchedulerAllows scheduling Allows scheduling of all instrumentsof all instruments
Designed and maintained Designed and maintained by Jerry Li by Jerry Li
Available with sourceAvailable with source
Microarray OverviewMicroarray Overview
MAD
Amplified/Purified GenesAmplified/Purified Genes
Loaded in ArrayerLoaded in Arrayer
Slides PrintedSlides Printed
Run Parameters SetRun Parameters Set
SliTrack/ControllerSliTrack/ControllerTakes Slide Order Takes Slide Order
and Run parameters,and Run parameters,generates spot order,generates spot order,
IAS control file,IAS control file,launches IAS run software,launches IAS run software,
loads database.loads database.(J. Li, developer and maintainer)(J. Li, developer and maintainer)
Select array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
Steps in the ProcessSteps in the Process
Microarray Overview IIMicroarray Overview II
Prepare FluorescentlyPrepare FluorescentlyLabeled ProbesLabeled Probes
ControlControl
TestTest
Hybridize,Hybridize,WashWash
MeasureMeasureFluorescenceFluorescencein 2 channelsin 2 channels
redred//greengreen
Analyze the dataAnalyze the datato identifyto identifypatterns ofpatterns of
gene expressiongene expression
Microarray Overview IIMicroarray Overview II
Prepare FluorescentlyPrepare FluorescentlyLabeled ProbesLabeled Probes
ControlControl
TestTest
Hybridize,Hybridize,WashWash
MeasureMeasureFluorescenceFluorescencein 2 channelsin 2 channels
redred//greengreen
Analyze the dataAnalyze the datato identifyto identifypatterns ofpatterns of
gene expressiongene expression
WeedWeed
BushBush
Microarray Overview IIMicroarray Overview II
Prepare FluorescentlyPrepare FluorescentlyLabeled ProbesLabeled Probes
ControlControl
TestTest
Hybridize,Hybridize,WashWash
MeasureMeasureFluoresenceFluoresencein 2 channelsin 2 channels
red/greenred/green
Analyze the dataAnalyze the datato identify to identify
differentiallydifferentiallyexpressed genesexpressed genes
Obtain RNA SamplesObtain RNA Samples
Microarray OverviewMicroarray Overview
MAD
MADAMMADAMAllows data entryAllows data entry
(J. Li & J. White, web prototype;(J. Li & J. White, web prototype;A. Saeed, J. White, J.Li, A. Saeed, J. White, J.Li, & V. Sharov, developers)& V. Sharov, developers)
Prepare FluorescentlyPrepare FluorescentlyLabeled ProbesLabeled Probes
ControlControl
TestTest
Hybridize,Hybridize,WashWashObtain RNA SamplesObtain RNA Samples
Microarray OverviewMicroarray Overview
MAD
MABCOSMABCOSUses Bar Codes to track samplesUses Bar Codes to track samples
(J. Li developer)(J. Li developer)
Obtain RNA SamplesObtain RNA Samples Prepare FluorescentlyPrepare FluorescentlyLabeled ProbesLabeled Probes
ControlControl
TestTest
Hybridize,Hybridize,WashWash
Available with sourceAvailable with source
Microarray OverviewMicroarray OverviewPaired TIFFPaired TIFFImage FilesImage Files
MADAM + MADAM + MAPMAPAllows data entry, Allows data entry,
moves files/renames to moves files/renames to long-term storagelong-term storage
(A. Saeed, J. White, J.Li, (A. Saeed, J. White, J.Li, & V. Sharov, developers)& V. Sharov, developers)
MAD
NetAPP
Microarray OverviewMicroarray Overview
NetAPP
Spotfinder Spotfinder Provides Image Analysis, Provides Image Analysis,
writes data towrites data toflat files or directly to dbflat files or directly to db
(V. Sharov, developer and maintainer)(V. Sharov, developer and maintainer)
MAD
Available as Executable for Windows;Available as Executable for Windows;device-independent C/C++ comingdevice-independent C/C++ coming
The TIGR Array Software System
SLITRACK
MADAM
PCRSCORE
ExpDesigner
SpotFinder
MABCOS
McCoder
MeVMIDASMAD
Data Normalization and FilteringData Normalization and Filtering
Lowess NormalizationLowess Normalization
Why LOWESS?Why LOWESS?
-3
-2
-1
0
1
2
3
7 8 9 10 11 12 13 14
log(Cy3*Cy5)
A SD = 0.346
ObservationsObservations1.1. Intensity-dependent structureIntensity-dependent structure2.2. Data not mean centered at logData not mean centered at log22(ratio) = 0(ratio) = 0
LOWESS (Cont’d)LOWESS (Cont’d)
Local linear regression model Local linear regression model
Tri-cube weight function Tri-cube weight function
Least SquaresLeast Squares
Estimated Estimated values of values of loglog22(Cy5/Cy3) as (Cy5/Cy3) as
function of function of loglog1010(Cy3*Cy5)(Cy3*Cy5)
-3
-2
-1
0
1
2
3
7 8 9 10 11 12 13 14
log(Cy3*Cy5)
AA SD = SD = 0.3460.346
WYXWXX
xyxw
xyxw
xy
iii
iii
ii
')'(
0)()(
)()(
1
2
2
LOWESS Results
“Slice Analysis” (Intensity-dependent Z-score)
MIDAS: Data AnalysisMIDAS: Data Analysis Wei LiangWei Liang
Available with OSI sourceAvailable with OSI source
Adding Error Models,Adding Error Models,MAANOVA,MAANOVA,
Automated ReportingAutomated Reporting
Microarray OverviewMicroarray Overview
MAD
MAD
MIDAS MIDAS Performs data normalizationPerforms data normalizationand filtering, including, soon, ANOVAand filtering, including, soon, ANOVA
MIDASMIDAS
Select array elements and annotate themSelect array elements and annotate them
Build a database to manage stuffBuild a database to manage stuff
Print arrays and manage the labPrint arrays and manage the lab
Hybridize and analyze images; manage dataHybridize and analyze images; manage data
Analyze hybridization data and get resultsAnalyze hybridization data and get results
Steps in the ProcessSteps in the Process
MeV: Data Mining ToolsMeV: Data Mining Tools Alexander SaeedAlexander SaeedAlexander SturnAlexander SturnNirmal BhagabatiNirmal Bhagabati
John BraistedJohn BraistedSyntek Inc.Syntek Inc.
Datanaut, Inc.Datanaut, Inc.
Available with OSI sourceAvailable with OSI source
MeV: Metabolic pathway analysis is comingMeV: Metabolic pathway analysis is coming
Maria Klapa and Chris KoenigMaria Klapa and Chris Koenig
Analyses available in MeV...Hierarchical clustering (HCL)Hierarchical clustering (HCL)Bootstrapped/Jackknifed HCLBootstrapped/Jackknifed HCLk-k-means clustering (KMC)means clustering (KMC)k-k-means support (iterative KMC)means support (iterative KMC)Self-Organizing Maps (SOMs)Self-Organizing Maps (SOMs)Cluster Affinity Search Technique (CAST)Cluster Affinity Search Technique (CAST)Figure of Merit for CAST and KMC (soon SOM)Figure of Merit for CAST and KMC (soon SOM)QTQT-clust (Heyer Jackknife)-clust (Heyer Jackknife)Principal component analysis (PCA)Principal component analysis (PCA)Gene ShavingGene ShavingRelevance NetworksRelevance NetworksSupport Vector Machines (SVM)Support Vector Machines (SVM)Self-Organizing TreesSelf-Organizing TreesClassification approaches, including Template MatchingClassification approaches, including Template Matchingt-testst-testsSignificance Analysis of Microarrays (SAM)Significance Analysis of Microarrays (SAM)
ANOVA toolsANOVA toolsGO, Metabolic Pathway, and Genome Localization annotation/clusteringGO, Metabolic Pathway, and Genome Localization annotation/clustering
Client-server mode with well-defined APIClient-server mode with well-defined API
Missing from MeV...
MAGE-ML output for direct submission to MAGE-ML output for direct submission to databases ... Coming in the next MADAM release.databases ... Coming in the next MADAM release.
Links to BioConductor … are coming.Links to BioConductor … are coming.
Array CGH module from Barb Weber and Adam Array CGH module from Barb Weber and Adam Margolin ... is coming.Margolin ... is coming.
EASE module from Doug Hosack ... is comingEASE module from Doug Hosack ... is coming
Lots of stuff we are not smart enough to think Lots of stuff we are not smart enough to think about.about.
00 33 66 99 1212
zz zzzz
zz zzzz
zz zzzz
zz zzzz
zz zzzz
Sleep Deprivation Studies in MouseSleep Deprivation Studies in Mouse
zz zzzz
zz zzzz
zz zzzz
zz zzzz
zz zzzz
zz zzzz
zz zzzz
zz zzzz
zz zzzz
zz zzzz
Experimental ParadigmExperimental ParadigmCompare gene expression between sleeping and Compare gene expression between sleeping and sleep-deprived mice in cortex and hypothalamussleep-deprived mice in cortex and hypothalamus
Perform 3 biological replicatesPerform 3 biological replicates
Normalize and filter data and use data mining techniques to Normalize and filter data and use data mining techniques to select distinct patterns of gene expressionselect distinct patterns of gene expression
Use Gene Ontology (GO) assignments to classify genes by Use Gene Ontology (GO) assignments to classify genes by cellular localization, molecular function, biological processcellular localization, molecular function, biological process
Use GO analysis to develop an understanding of responseUse GO analysis to develop an understanding of response
Differential Expression in CortexDifferential Expression in Cortex
Energy MetabolismTranscription;Mitochondrial and Ribosomal Proteins
Stress Response
IntermediateMetabolism andSignal Transduction
Differential Expression in HypothalamusDifferential Expression in Hypothalamus
Sleep signaling
Cortex – Up-regulated Genes GO Class GO Category p-value
GO Cellular Component endoplasmic reticulum 6.0610-03 GO Molecular Function heat shock protein activity 8.7810-04
pyruvate dehydrogenase (lipoamide) phosphatase activity 3.1710-03 chaperone activity 7.3810-03
Cortex – Down-regulated Genes GO Class Gene Category p-value
GO Biological Process protein biosynthesis 2.8510-25 protein metabolism 1.0010-11 electron transport 6.0410-03
GO Cellular Component ribosome 5.9510-37 ribonucleoprotein complex 1.1710-32 eukaryotic 48S initiation complex 9.7410-18 eukaryotic 43S pre-initiation complex 2.6810-15 mitochondrial inner membrane 3.7010-03
GO Molecular Function structural constituent of ribosome 6.4610-39 RNA binding activity 4.8310-21 cytochrome c oxidase activity 9.7910-04 hydrogen ion transporter activity 1.8810-03
EASE Analysis of GO termsEASE Analysis of GO terms
Hosack, Hosack, et al. 2003et al. 2003
ThemesThemes: : General biological trends based on representation of General biological trends based on representation of functional roles on the arrayfunctional roles on the array
ProblemProblem: : Requirement of functional class assignment limits utility Requirement of functional class assignment limits utility for discovery of new functional networksfor discovery of new functional networks
Thanks to Doug Hosack, NIAIDThanks to Doug Hosack, NIAID
Now available... The TGI databases, including RESOURCERERThe TGI databases, including RESOURCERER
The TGICL Gene Index Clustering and Assembly ToolsThe TGICL Gene Index Clustering and Assembly Tools
A freely-available MySQL version of our MIAME-A freely-available MySQL version of our MIAME-supportive databasesupportive database
A freely-available, open source, java-based set of tools:A freely-available, open source, java-based set of tools: MADAM: MADAM: MMicroicroaarray rray DaData ta MManager anager MIDAS: MIDAS: MiMicroarray croarray DData ata AAnalysis nalysis SSystemystem MeV: MeV: MMultiultieexperiment xperiment VVieweriewer
A freely-available, image processing software system A freely-available, image processing software system linked to the database: TIGR Spotfinderlinked to the database: TIGR Spotfinder
Nobody in the game of football Nobody in the game of football should be called a genius. should be called a genius.
A genius is somebody like Norman Einstein. A genius is somebody like Norman Einstein.
-Joe Theisman, Former quarterback-Joe Theisman, Former quarterback
A theory has only the possibility of being A theory has only the possibility of being right or wrong. A model has a third right or wrong. A model has a third
possibility; it may be right but irrelevant.possibility; it may be right but irrelevant.
–– Manfred EigenManfred Eigen
Unless a reviewer has the courage Unless a reviewer has the courage to give you unqualified praise, I say to give you unqualified praise, I say
ignore the bastard.ignore the bastard.
- John Steinbeck- John Steinbeck
The TIGR Gene Index TeamThe TIGR Gene Index TeamFoo CheungFoo Cheung
Svetlana KaramychevaSvetlana KaramychevaYudan LeeYudan Lee
Babak ParviziBabak ParviziGeo PerteaGeo Pertea
Razvan SultanaRazvan SultanaJennifer TsaiJennifer Tsai
John QuackenbushJohn QuackenbushJoseph WhiteJoseph White
Funding provided by the Department of EnergyFunding provided by the Department of Energyand the National Science Foundationand the National Science Foundation
TIGR Human/Mouse/Arabidopsis TIGR Human/Mouse/Arabidopsis Expression TeamExpression Team
Emily ChenEmily ChenBryan FrankBryan Frank
Renee GaspardRenee GaspardJeremy HassemanJeremy Hasseman
Heenam KimHeenam KimLara LinfordLara Linford
Simon KwongSimon KwongJohn QuackenbushJohn Quackenbush
Shuibang WangShuibang WangYonghong WangYonghong Wang
Ivana YangIvana YangYan YuYan Yu
Array Software Hit TeamArray Software Hit TeamNirmal BhagabatiNirmal Bhagabati
John BraistedJohn BraistedTracey CurrierTracey Currier
Jerry LiJerry LiWei LiangWei Liang
John QuackenbushJohn QuackenbushAlexander I. SaeedAlexander I. Saeed
Vasily SharovVasily SharovMathangi ThaiagarjianMathangi Thaiagarjian
Joseph WhiteJoseph WhiteAssistantAssistantSue MineoSue MineoFunding provided by the National Cancer Institute,Funding provided by the National Cancer Institute,
the National Heart, Lung, Blood Institute,the National Heart, Lung, Blood Institute,and the National Science Foundationand the National Science Foundation
H. Lee Moffitt Center/USFH. Lee Moffitt Center/USFTimothy J. YeatmanTimothy J. Yeatman
Greg BloomGreg Bloom
TIGR PGA CollaboratorsTIGR PGA CollaboratorsNorman LeeNorman LeeRenae MalekRenae Malek
Hong-Ying WangHong-Ying WangTruong LuuTruong Luu
Bobby BehbahaniBobby Behbahani
TIGR Faculty, IT Group, and StaffTIGR Faculty, IT Group, and Staff
<johnq@tigr.org><johnq@tigr.org>AcknowledgmentsAcknowledgments
PGA CollaboratorsPGA CollaboratorsGary Churchill (TJL)Gary Churchill (TJL)Greg Evans (NHLBI)Greg Evans (NHLBI)Harry Gavaras (BU)Harry Gavaras (BU)
Howard Jacob (MCW)Howard Jacob (MCW)Anne Kwitek (MCW)Anne Kwitek (MCW)Allan Pack (Penn)Allan Pack (Penn)
Beverly Paigen (TJL)Beverly Paigen (TJL)Luanne Peters (TJL)Luanne Peters (TJL)
David Schwartz (Duke)David Schwartz (Duke)
EmeritusEmeritusJennifer Cho (TGI)Jennifer Cho (TGI)
Ingeborg Holt (TGI)Ingeborg Holt (TGI)Feng Liang (TGI)Feng Liang (TGI)
Kristie Abernathy (mA)Kristie Abernathy (mA)Sonia Dharap(mA)Sonia Dharap(mA)
Julie Earle-Hughes (mA)Julie Earle-Hughes (mA)Cheryl Gay (mA)Cheryl Gay (mA)Priti Hegde (mA)Priti Hegde (mA)
Rong Qi (mA)Rong Qi (mA)Erik Snesrud (mA)Erik Snesrud (mA)
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