Systems biology -the intro 張晃猷分子醫學研究所[email protected].

Systems biologySystems biology-the intro-the intro

張晃猷張晃猷分子醫學研究所分子醫學研究所

[email protected]@life.nthu.edu.tw

What is Systems What is Systems Biology????Biology????

To unravel the mysteries of human biology to identify strategies for predicting and preventing diseases such as cancer, diabetes and AIDS.

http://www.systemsbiology.org/

A cross-disciplinary scienceA cross-disciplinary science

The

The Human Genome ProjectThe Human Genome Project

GoalsGoals

ImpactImpact• Discovery science vs hypothesis-drivenDiscovery science vs hypothesis-driven• Biology is an Informational ScienceBiology is an Informational Science• Tools for high throughput quantitative meTools for high throughput quantitative me

asurement of biological informationasurement of biological information• The use of model organismsThe use of model organisms

Completed prokaryotes eukaryotes

Archae 19 eubacteria 167 ongoing ongoing

Eukaryote 32

Organizational and Organizational and Descriptional LevelsDescriptional Levels

So what is So what is Systems Systems BiologyBiology??

The definitionThe definition The types of biological information (DNA, The types of biological information (DNA, RNA, protein, protein interactions, biomolRNA, protein, protein interactions, biomolecules, cells, tissues, etc.) also have their iecules, cells, tissues, etc.) also have their individual elements (e.g. specific genes or ndividual elements (e.g. specific genes or proteins) and the relationships of these witproteins) and the relationships of these with respect to one another and the elements h respect to one another and the elements of other types of biological information mof other types of biological information must be determined, all of this information iust be determined, all of this information integrated to obtain a view (model) of the sntegrated to obtain a view (model) of the system as a whole. ystem as a whole.

Still vague? Still vague?

Systems Biology is a new field in Systems Biology is a new field in biology that aims at system-level biology that aims at system-level understanding of biological systems.understanding of biological systems.

Hiroaki KitanoHiroaki Kitano(Director, ERATO Kitano Symbiotic Systems Project(Director, ERATO Kitano Symbiotic Systems Project ))

What are biological What are biological systems?systems?

Ranges from Ranges from ecosystemsecosystems (eg. Bi (eg. Biosphere) to the system of reactioosphere) to the system of reactions that form ns that form cellular biochemistcellular biochemistryry

A Systems Approach to the Study A Systems Approach to the Study of Biological Systemsof Biological Systems

Some examplesSome examples

Galactose utilization/galGalactose utilization/galatosemiaatosemia

How a defective How a defective control protein (red control protein (red circle) alters the circle) alters the level of other level of other proteins (circles in proteins (circles in shades of gray) shades of gray) through interactions through interactions among proteins (blue among proteins (blue lines) and lines) and interactions between interactions between proteins and DNA proteins and DNA (yellow arrows). (yellow arrows).

Reverse-engineer the computational principles underlying cellular processes;

Develop tools and techniques for modeling and analysis of experimental data at three levels:

individual genes;network modules; whole networks.

Human immunityHuman immunity

Molecules

Synapses

Neurons

Networks

Systems

CNS

1 cm

100 um

10 cm

m

um

nm

1014 connecting points

Keynote Speakers:

James J. Collins Center for BioDynamics, Boston UniversityJohn Doyle Control and Dynamical Systems, CaltechYoshihide Hayasizaki Genome Exploration Group, RIKEN Genomic Sciences CenterStan LeiblerLaboratory of Living Matter, Rockefeller UniversityMark Ptashne Molecular Biology Program, Sloan-Kettering Institute

System Biology

The quantitative study of biological processes as integrated systems rather than as isolated parts.

The aim is to understand the interactions between the myriad of sub-cellular components.

The traditionally separated scientific disciplines, including physical chemistry, biochemistry, molecular biology, cell physiology and the behaviour of multicellular organisms, are unified by quantitative models.

Advance techniques for global measurements of subcellular dynamics of gene expression, proteins, and metabolites will be applied.

The progress will be crucial for a molecular understanding of many diseases and for development of novel biotechnological applications.

Expression ExperimentsExpression ExperimentsStatic: Snapshot of Static: Snapshot of the activity in the the activity in the cell cell

Time series: Multiple Time series: Multiple arrays at various temporal arrays at various temporal intervals intervals

Time Series Examples: Time Series Examples: DevelopmentDevelopment

Development of fruit flies [Arbeitman, Science 02]

Time Series Examples (cont) Time Series Examples (cont)

Infectious diseases [Huang, Science 01; Nau, PNAS 02]

Function

Transcription factors knockout [Zhu, Nature 00;

Pramilla, Genes Dev. 02]

Interactions

Systems Biology –

from Bioscience to Medicine

Metabolic FluxMetabolic Flux Signal transductionSignal transduction Microbial systemsMicrobial systems Methods and softwaresMethods and softwares Spatial modelsSpatial models Systems biology for medicineSystems biology for medicine

Metabolic fluxMetabolic fluxFrom gene expression to metabolic fluxesFrom gene expression to metabolic fluxes

Vertical genomics: From gene expression to function ... and backVertical genomics: From gene expression to function ... and back

Dynamic metabolomics for systems biologyDynamic metabolomics for systems biology

Metabolic networks in motion: High-throughput analysis of molecular Metabolic networks in motion: High-throughput analysis of molecular fluxesfluxes

Prediction of regulatory pathways using mRNA expression and proteiPrediction of regulatory pathways using mRNA expression and protein-protein interaction data: Application to prediction of galactose ren-protein interaction data: Application to prediction of galactose regulatory pathwaygulatory pathway

Metabolic networks in plants: Statistical analysis and biological interpMetabolic networks in plants: Statistical analysis and biological interpretationretation

Minimal cut sets: Failure modes and target sets in metabolic networkMinimal cut sets: Failure modes and target sets in metabolic networkss

Microbial systems Microbial systems biologybiology

Metabolome analysis and cell simulationMetabolome analysis and cell simulation

Doing it their way: Metabolic differentiation in salmonellaDoing it their way: Metabolic differentiation in salmonella

Receptor cooperativity and signal processing in bacterial cheReceptor cooperativity and signal processing in bacterial chemotaxismotaxis

Bacterial persistence: A phenotypic switch revealed by microflBacterial persistence: A phenotypic switch revealed by microfluidicsuidics

An approach to generate testable hypothesis in microbiologyAn approach to generate testable hypothesis in microbiology

The dynamic response of yeast cells to osmotic shockThe dynamic response of yeast cells to osmotic shock

Methods and Software for Methods and Software for Systems Biology Systems Biology

Software and methods for modeling and simulating biochemical nSoftware and methods for modeling and simulating biochemical networksetworks

A hybrid approach for efficient and robust parameter estimation in A hybrid approach for efficient and robust parameter estimation in biochemical pathwaysbiochemical pathways

A modular approach to building the silicon yeast cellA modular approach to building the silicon yeast cell

Model Orchestration: Addressing the challenges of model managModel Orchestration: Addressing the challenges of model management and model composition in systems biologyement and model composition in systems biology

Dicovering Motifs in Biological Networks using Sub-Graph IsomorDicovering Motifs in Biological Networks using Sub-Graph Isomorphismphism

Principles of Systems Biology, illustrated with modeling of the heaPrinciples of Systems Biology, illustrated with modeling of the heartrt

Spatial ModelSpatial ModelQuantitative temporal and spatial analysis of cell division by 4D iQuantitative temporal and spatial analysis of cell division by 4D i

magingmagingPropagating chemical waves within and among cellsPropagating chemical waves within and among cells

Temporal and spatial control of signaling in the interferon-y/jak/StTemporal and spatial control of signaling in the interferon-y/jak/Stat1 pathwayat1 pathway

Systems analysis of the quorum sensing phenomenon in a peculiSystems analysis of the quorum sensing phenomenon in a peculiar plant pathogen ar plant pathogen Agrobacterium tumefaciensAgrobacterium tumefaciens

Compensation effect of MAPK cascade on formation of phospho-Compensation effect of MAPK cascade on formation of phospho-protein gradientprotein gradient

How to make a neurocrystal: Modelling the development patterninHow to make a neurocrystal: Modelling the development patterning of the fruit fly´s retinag of the fruit fly´s retina

Signal transductionSignal transduction Dynamics and design of signalling networks: The Wnt-paDynamics and design of signalling networks: The Wnt-pa

thwaythway Synaptic signaling: Holding out against noise, diffusion, aSynaptic signaling: Holding out against noise, diffusion, a

nd turnovernd turnover Employing systems biology to quantify receptor tyrosine Employing systems biology to quantify receptor tyrosine

kinase signaling in time and spacekinase signaling in time and space Cellular decision making: Control of kinases and phosphCellular decision making: Control of kinases and phosph

atases on signaling kineticsatases on signaling kinetics Modeling signal transduction systems without ignoring thModeling signal transduction systems without ignoring th

eir combinatorial complexityeir combinatorial complexity New quantitative approaches for modeling and simulatioNew quantitative approaches for modeling and simulatio

n of large signal transduction networks reveal novel insign of large signal transduction networks reveal novel insights into programmed cell deathhts into programmed cell death

Systems Biology and Systems Biology and MedicineMedicine

Mathematical Modelling of metabolic diseasesMathematical Modelling of metabolic diseases

Virus dynamics: Modeling of influenza A virus replicationVirus dynamics: Modeling of influenza A virus replication

Discovering activated regulatory networks in the DNA damage reDiscovering activated regulatory networks in the DNA damage response pathway of yeastsponse pathway of yeast

Metabolic comparison of the in-silico phenotype-genotype relatioMetabolic comparison of the in-silico phenotype-genotype relationship of nship of Pseudomonas putidaPseudomonas putida and and Peudomonas aeruginosaPeudomonas aeruginosa

Systems biology approach to understand the stress response of Systems biology approach to understand the stress response of P. aeruginosaP. aeruginosa to host innate immunity to host innate immunity

Using a mammalian cell cycle simulation in anti-tumor pharmaceUsing a mammalian cell cycle simulation in anti-tumor pharmaceutical development to interpret differential kinase inhibition and biutical development to interpret differential kinase inhibition and biological knock-outsological knock-outs

The position of Systems The position of Systems BiologyBiology

What does it take to carry What does it take to carry out Systems Biology? out Systems Biology?

A cross-disciplinary faculty who speak and understand the A cross-disciplinary faculty who speak and understand the languages of different disciplines languages of different disciplines

Integrate new global technologies with the data acquisition, Integrate new global technologies with the data acquisition, storage, integration, and analysis tools of computational storage, integration, and analysis tools of computational biology and mathematics.biology and mathematics.

High-throughput facilities for genomics, proteomics etc… High-throughput facilities for genomics, proteomics etc…

An integration of effort with academia and industry. An integration of effort with academia and industry.

Integration of discovery science with hypothesis-driven Integration of discovery science with hypothesis-driven science for the integrated global analysis of systems. science for the integrated global analysis of systems.

In another word……In another word……

Why do we care about Why do we care about biological systems?biological systems?

Ability to figure out what the effect will be of Ability to figure out what the effect will be of an intervention in one part of the systeman intervention in one part of the system

What intervention one has to make in order What intervention one has to make in order to obtain some desired resultto obtain some desired result

= Which protein should be either activated or = Which protein should be either activated or deactivated in order to stop a particular deactivated in order to stop a particular disease process while doing the least harm disease process while doing the least harm to the patient?to the patient?

Where do computers Where do computers come in?come in?

Systems modelingSystems modeling simulation, reasoning, discoverysimulation, reasoning, discovery Some properties to investigateSome properties to investigate Structure Structure DynamicsDynamics RobustnessRobustness Methods of control systemsMethods of control systems Methods to design and modify for desired Methods to design and modify for desired propertiesproperties

The SYSTEOME ProjectThe SYSTEOME Project

Systeome is an assembly of system profiles for Systeome is an assembly of system profiles for all genetic variations and environmental stimuli rall genetic variations and environmental stimuli responses.esponses.

Goal: to complete a detailed and comprehensivGoal: to complete a detailed and comprehensive simulation model of the human cell at an estie simulation model of the human cell at an estimated error margin of 20% by year 2020, and to mated error margin of 20% by year 2020, and to finish identifying the system profile for all genetifinish identifying the system profile for all genetic variations, drug responses, and environmental c variations, drug responses, and environmental stimuli by 2030.stimuli by 2030.

Dr. Hiroaki KitanoDr. Hiroaki Kitano

ConclusionConclusion System biology is a new and emerging field in System biology is a new and emerging field in

biologybiology A long ways to go before understanding A long ways to go before understanding

biological systemsbiological systems “… “… systems biology will be the dominant systems biology will be the dominant

paradigm in biology, and many medical paradigm in biology, and many medical applications as well as scientific discoveries are applications as well as scientific discoveries are expected” – Hiroaki Kitanoexpected” – Hiroaki Kitano

Systems biology -the intro 張晃猷分子醫學研究所[email protected].

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Transcript of Systems biology -the intro 張晃猷分子醫學研究所[email protected].