1

Agent Smith: Good bye, Mr. Anderson!Neo : My name IS Neo!

hi, neo…!�

Ju Han Kim, M.D., Ph.D., M.S.Ju Han Kim, M.D., Ph.D., M.S.SNUBiomedicalSNUBiomedical InformaticsInformaticsSeoul Seoul NatNat’’t t Univ. School of MedicineUniv. School of Medicinehttp://www.http://www.snubisnubi.org/.org/

Bioinformatics Bioinformatics andandGenomic Medicine Genomic Medicine

BioinformaticsBioinformatics & Genomic Medicine& Genomic Medicine

•• Who are the driversWho are the drivers•• Problems in Genomics are the classical Problems in Genomics are the classical

problems of Informaticsproblems of Informatics•• Biochip & Functional GenomicsBiochip & Functional Genomics•• My contributionMy contribution•• Integrative Biochip InformaticsIntegrative Biochip Informatics•• Emergence of New MedicineEmergence of New Medicine

BioinformaticsBioinformatics & Genomic Medicine& Genomic Medicine

•• Who are the driversWho are the drivers•• Problems in Genomics are the classical Problems in Genomics are the classical

problems of Informaticsproblems of Informatics•• Biochip & Functional GenomicsBiochip & Functional Genomics•• My contributionMy contribution•• Integrative Biochip InformaticsIntegrative Biochip Informatics•• Emergence of New MedicineEmergence of New Medicine

Who are the drivers?Who are the drivers?

•• Clinical data explosionClinical data explosion•• Genomic data explosionGenomic data explosion•• Databases, algorithms, and HPCDatabases, algorithms, and HPC•• The InternetThe Internet

•• SequencesSequences•• Linkage mapLinkage map•• Physical mapPhysical map•• PolysPolys/gene (1/gene (1--2/kb?)2/kb?)•• Expression profilesExpression profiles•• Structural info.Structural info.•• How would you begin to How would you begin to

estimate?estimate?

Clinical InformationClinical Information

Paradigm Shift Paradigm Shift -- Clinical Knowledge Management Clinical Knowledge Management --

ClinicianClinician--directeddirected ResourceResource--directeddirected

Dr. Abraham

Dr. ElsonDr. Faughnan

Dr. Dandy

Dr. connellyDr. Belsky

Dr. Abraham

Informatics

2

DNADNA

RNARNA

ProteinProtein

The Central Dogma of LifeThe Central Dogma of Life

InteractionsInteractions

Building blocks of life are digital!Building blocks of life are digital!

•• DNA DNA 44--digit {A,G,T,C} stringdigit {A,G,T,C} string•• RNA RNA #of #of mRNA mRNA as the activity of the geneas the activity of the gene•• Protein Protein 2020--digit {amino acids} stringdigit {amino acids} string

functional machineryfunctional machinery33--D structure mattersD structure matters

•• MetabolitesMetabolites•• Cells, Tissues, OrganCells, Tissues, Organ--SystemsSystems•• Individual or PopulationIndividual or Population

NetworksNetworks SystemSystem

BioinformaticsBioinformatics & Genomic Medicine& Genomic Medicine

•• Who are the driversWho are the drivers•• Problems in Genomics are the classical Problems in Genomics are the classical

problems of Informaticsproblems of Informatics•• Biochip & Functional GenomicsBiochip & Functional Genomics•• My contributionMy contribution•• Integrative Biochip InformaticsIntegrative Biochip Informatics•• Emergence of New MedicineEmergence of New Medicine

• Sequence alignment / homology / Sequence alignment / homology / polyspolys:String search (ex. BLAST/FASTA, HMM)String search (ex. BLAST/FASTA, HMM)

•• Combinatorial data explosionCombinatorial data explosion::Optimization (ex. TSP), MCMCOptimization (ex. TSP), MCMC

•• Predictive model buildingPredictive model building & functionSupervised machine learningSupervised machine learning

•• High throughputsHigh throughputsExploratory data analysis, clusteringExploratory data analysis, clustering

Problems in genomics are Problems in genomics are the classical problems in informaticsthe classical problems in informatics

BioinformaticsBioinformatics & Genomic Medicine& Genomic Medicine

•• Who are the driversWho are the drivers•• Problems in Genomics are the classical Problems in Genomics are the classical

problems of Informaticsproblems of Informatics•• Clinical Relevance of Biochip InformaticsClinical Relevance of Biochip Informatics•• My contributionMy contribution•• Integrative Biochip InformaticsIntegrative Biochip Informatics•• Emergence of New MedicineEmergence of New Medicine

Clinical relevance of Clinical relevance of Biochip informaticsBiochip informatics

DxDx.. KnowledgeKnowledgediscoverydiscovery

PxPx..TxTx..

3

Biochip basicsBiochip basics

Bioinformaticspipeline

InterestingPatients

InterestingPatients

InterestingAnimals

InterestingAnimals

InterestingCell Lines

InterestingCell Lines

AppropriateTissue

AppropriateTissue

AppropriateConditions

AppropriateConditions Extract RNAExtract RNA

Scan BiochipScan

Biochip

HybridizeBiochip

HybridizeBiochip

MakeBiochipMake

Biochip

Data Pre-processingData Pre-

processingAccess

SignificanceAccess

Significance

A Functional Genomics StrategyA Functional Genomics Strategy

Post-clusterAnalysis &Integration

Post-clusterAnalysis &IntegrationBiological

ValidationBiologicalValidation

InformaticalValidation?

InformaticalValidation? ??

FunctionalClustering

FunctionalClustering

AstronomerAstronomer’’s Learnings Learning

Babylonians created the map of starry sky.and Astronomy started then…

Organizing complex data into a meaningful structure!

Biochip informatics: clusteringBiochip informatics: clustering

A11A21A31A41A51A61A71A81A91

timetime

A12A22A32A42A52A62A72A82A92

A13A23A33A43A53A63A73A83A93

A14A24A34A44A54A64A74A84A94

A15A25A35A45A55A65A75A85A95

A16A26A36A46A56A66A76A86A96

Biochip informatics: clusteringBiochip informatics: clustering

clusteringclustering

4

Hierarchical & Partitional ClusteringHierarchical & Partitional Clustering

Hierarchical Hierarchical PartitionalPartitional

Hierarchical clustering in GenomicsHierarchical clustering in Genomics

• single-linkage (nearest neighbor)• complete-linkage (farthest neighbor)• weighed pair-group average • unweighed pair-group average• weighted pair-group centroid• unweighted pair-group centroid• Ward’s method: min. sum of squares

KK--means Algorithm (K=2)means Algorithm (K=2) KK--means Algorithm (K=2)means Algorithm (K=2)

KK--means Algorithm (K=2)means Algorithm (K=2) KK--means Algorithm (K=2)means Algorithm (K=2)

5

KK--means Algorithm (K=2)means Algorithm (K=2) KK--means Algorithm (K=2)means Algorithm (K=2)

KK--means Algorithm (K=2)means Algorithm (K=2) KK--means Algorithm (K=2)means Algorithm (K=2)

KK--means Algorithm (K=2)means Algorithm (K=2)

Convergence!!Convergence!!

BioinformaticsBioinformatics & Genomic Medicine& Genomic Medicine

•• Who are the driversWho are the drivers•• Problems in Genomics are the classical Problems in Genomics are the classical

problems of Informaticsproblems of Informatics•• Biochip & Functional GenomicsBiochip & Functional Genomics•• My contributionMy contribution•• Integrative Biochip InformaticsIntegrative Biochip Informatics•• Emergence of New MedicineEmergence of New Medicine

6

XXperantoperanto: : Expressionist’s Esperanto in XMLExpressionist’s Esperanto in XML

MAGEMAGE--ML (ML (MicroArrayMicroArray Gene Expression)Gene Expression)They must They must TALKTALK!!

BioCANDIBioCANDI: integrative : integrative analsysisanalsysis

GRIPGRIP: Genome Research Informatics Pipeline: Genome Research Informatics Pipeline GRIP: gene / protein informationGRIP: gene / protein information

7

ChromoVizChromoVizArrayXPathArrayXPath

BioinformaticsBioinformatics & Genomic Medicine& Genomic Medicine

•• Who are the driversWho are the drivers•• Problems in Genomics are the classical Problems in Genomics are the classical

problems of Informaticsproblems of Informatics•• Biochip & Functional GenomicsBiochip & Functional Genomics•• My contributionMy contribution•• Integrative Biochip InformaticsIntegrative Biochip Informatics•• Emergence of New MedicineEmergence of New Medicine

Integrated biochip informaticsIntegrated biochip informatics

Miniaturization & streamliningMiniaturization & streamlining

Data management layer

clone data

Outside data Slide data

Cell data

Hyb. data

Exp. data

scan data

Inhouse data

Image analysisArray fabrication

Cluster analysisData mining

Pathway/networkanalysis

Clinical Information System

CommunicationStandards &

Ontology

Public & Private Databases

Systematic perturbationBoth Observational and Experimental

IBM/Mayo Clinic CollaborationApplied Genomics Data Analysis

Genomic data (DNA) – GeneChip array data (RNA)Protein data

Clinical DataSigns

SymptomsLaboratoryRadiology

Etc.

Optimized, individualized healthcare

DatabasesGenomeProteomeDiseaseTumorsDrugs

Phase I

8

http://cardiogenomics.med.harvard.edu http://cardiogenomics.med.harvard.edu

BioinformaticsBioinformatics & Genomic Medicine& Genomic Medicine

•• Who are the driversWho are the drivers•• Problems in Genomics are the classical Problems in Genomics are the classical

problems of Informaticsproblems of Informatics•• Biochip & Functional GenomicsBiochip & Functional Genomics•• My contributionMy contribution•• Integrative Biochip InformaticsIntegrative Biochip Informatics•• Emergence of New MedicineEmergence of New Medicine

Emergence of New MedicineEmergence of New Medicine

My view of the My view of the ‘‘OmicOmic’’ revolutionrevolution

Molecularly-informed

Horizontal integration

Biological org. Biome

Gene GenomemRNA TranscriptomeProtein Proteome

Metabolite MetabolomePhysiological dyn Physiome

My view of My view of ‘‘informaticsinformatics’’ revolutionrevolution

Clinical Informatics

Health Science Informatics

Structural Informatics digital anatomy

Biomolecular Informatics structural biologyfunctional genomics

Computational Physiology neuroinformaticscardiovascular sim.

Computational Cell Biology E-cellin silico biology

Chemoinformatics phramacogenomicsdrug design

Informatically-empowered

vertical integration

9

Emergence of New MedicineEmergence of New MedicineWeaving the revolutions!

Molecularly-informed &Informatically-impowered

The new medicine will beThe new medicine will bebothboth

Biomedical Informatics Biomedical Informatics & Genomic Medicine& Genomic Medicine

Thank you!Thank you!http://www.http://www.snubisnubi.org/.org/