2005-3-24 Chaoqun Wu,Fudan University 1
Systems Biology
复旦大学生命科学学院 吴超群
Chaoqun Wu
The School of Life Sciences
Fudan University
2005-3-24 Chaoqun Wu,Fudan University 2
系统生物学是继人类基因组计划后，
又一个解密生命奥秘的新探索
A new approach to decoding life:
Systems Biology
2005-3-24 Chaoqun Wu,Fudan University 3
讨论的内容
? 什么是系统生物学?
? 什么是生物系统?
? 系统生物学的研究内容
? 系统生物学的技术和方法
? 系统组学（Systeome）
? 癌的系统生物学
? 系统生物学对医学的影响
? 小结
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Approach on human body
Bottom-up
Top-down
整体水平 细胞水平 分子水平器官水平系统生物学
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什么是系统生物学?
什么是系统生物学?
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系统论的创始人是美籍奥地利理论 生物学家 路德维格 ·贝塔朗菲。
系统论是研究系统的一般模式，结构和规律的学问，它研究各种系统的共同特征，用数学方法定量地描述其功能，寻求并确立适用于一切系统的原理、
原则和数学模型，是具有逻辑和数学性质的一门新兴的科学。
研究和认识系统的目的之一，就在于有效地控制和管理系统。控制论 (Cybernetics)则为人们对系统的管理和控制提供了一般方法论的指导，它是数学、
自动控制、电子技术、数理逻辑、生物科学等学科和技术相互渗透而形成的综合性科学。
关于系统论 （ System Theory）
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系统论通常把系统定义为：由若干要素以一定结构形式联结构成的具有某种功能的有机整体。在这个定义中包括了 系统,
要素,结构,功能 四个概念，表明了要素与要素、要素与系统、系统与环境三方面的关系。
系统论认为，整体性、关联性，等级结构性、动态平衡性、时序性等是所有系统的共同的基本特征。
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A systems biology view...
Life‘s Complexity Pyramid (Oltvai-Barabasi,Science 10/25/02)
Components
Building
Blocks
Functional
Modules
System
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Dynamic Systems
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系统生物学是生命科学研究领域的一门新兴学科。
系统生物学是研究一个生物系统中所有组成成分的构成及其在特定条件下相互关系的、以整体性研究为特征一种大学科。
2005-3-24 Chaoqun Wu,Fudan University 11
“系统的水平,与分子的水平不同，
它的研究重点不是在个别核苷酸或蛋白质分子的序列及其功能，而是在由核苷酸、蛋白质、脂质、多糖等分子组成的生物系统。
系统生物学的研究也不是简单地堆积分子生物学研究的结果，而是以 系统论的观点,动态的观点,多样性的观点和 进化的观点 来分析实验结果，研究生物系统。
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Molecular vs,Systems
Biology Biology
? In molecular biology,
gene structure and
function is studied at
the molecular level.
? In systems biology,
specific interactions of
components in the
biological system are
studied – cells,tissues,
organs,and ecological
webs.
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系统生物学的任务是用系统方法实现生物学的革命，并且紧密联系医学应用。
? It is analogous to a static roadmap,whereas
what we really seek to know are the traffic
patterns,why such traffic patterns emerge,
and how we can control them.
Hiroaki Kitano,Science,1 March 2002
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研究方向系统生物学刚刚开始发展，其研究方向有待逐步明确。仅从系统生物学研究院和几次国际学术会议看，所进行的研究方向有：蛋白质组学；遗传网络；代谢网络、发育；空间、结构系统生物学；硅细胞；超细胞系统生物学；计算生物学；软件构架，系统生物学研究的软件平台；系统分析，模式识别，
动力系统理论和代谢控制分析；等等。
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? Biology went top-down for the last 50 years
From cell to protein to gene,.
Huge amounts of data produced
Challenge,put the pieces back together again
? Attempts to create predictive models of cells,
organs,biochemical processes and complete
organisms
Data combined with computational,mathematical
and engineering disciplines
Model simulations experiment
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Systems Biology
Research
Cycle Vision
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系统生物学的特点
?Integrative approach
(整合性研究 )
?Large experimental datasets
(大量的实验数据 )
?Predictive modelling
(预测性模型 )
? Interdisciplinarity
(多学科交叉 )
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整合是系统生物学的灵魂
?信息整合
?研究思路整合
?方法的整合
Systems biology is an integrated process
? Quantitative experiments
? System analysis
? Technology development for experiments
? Computational modeling
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两大类型的信息 整合
第一类信息是指编码蛋白质的基因
第二类信息是指控制基因行为的调控网络。
? 生物信息是有等级次序，沿着不同的层次流动。
DNA→mRNA→蛋白质→蛋白质相互作用网络
→细胞→器官→个体→群体→ 生态。
? 每个层次信息都对理解生命系统运行提供有用的视角。
系统生物学的重要任务就是要尽可能地获得每个层次的信息并将它们进行整合
2005-3-24 Chaoqun Wu,Fudan University 20
整合的内容：
? Factor comprehensiveness:
系统内不同性质的构成要素的整合,如基因、
mRNA、蛋白质、生物小分子等
? Time-line comprehensiveness:
the time frame within which measurements
are made 时间系列的整合
? Item comprehensiveness:
such as mRNA and protein concentrations,
phosphorylation 要素变化的整合总之，对多细胞生物而言，实现从基因到细胞、
组织、器官、系统、个体的各个层次的整合。
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整合的策略：
? 选定一个较为简单的系统，分析尽可能多的构成成分 ——基因组、转录组、蛋白质组、
相互作用组，以揭示整个系统的行为，代表人物：胡德和系统生物学研究所
? 以一个较为复杂的系统为研究对象，采用尽可能多的研究手段去进行分析。代表人物：
吉尔曼（ A,G,Gilman）及其领导的,信号转导同盟,
2005-3-24 Chaoqun Wu,Fudan University 22
A bigger picture of Systems
Biology
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According to a well-accepted tradition,the 5
th
International
conference on Systems Biology 2004programme committee
has coined a moto for the conference in 2004,"Systems
Biology - From Bioscience to Medicine".
Following this guideline session topics for the conference
were chosen that encompass the understanding of
metabolic and signal transduction systems,bacterial
systems biology,hepatocytes and their implication
for systems biology for medicine,and spatial models.
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什么是生物系统?
什么是生物系统?
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What are biological systems?
? Question is,what do we mean by
biological systems?
? By,system”,we mean a bunch of parts
that are connected to one another and
work together,
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What are Biological Systems?
Popular Notion:
It is a complex system consisting of
very many simple and identical elements
interacting to produce what appears to
be complex behavior
Example,Cells,Proteins
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What are Biological Systems?
Realistic Notion:
It is a system composed of many different
kinds of multifunctional elements
interacting selectively and nonlinearly
with others to produce coherent behavior.
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What are Biological Systems?
? Complex systems of simple elements
have functions that emerge from the
properties of the networks they form.
? Biological systems have functions that
rely on a combination of the network
and the specific elements involved.
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Biological systems ranges from:
? Ecosystems to the system of reactions
that form cellular biochemistry.
? Usually,we refer to the latter,systems of
biochemical reactions that make cells
work.
? It is often said that biological systems,
such as cells,are 'complex
systems'
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Features of biological systems
1,Composed of biological elements
（由生物元素组成）
small molecules:
water,inorganic molecules,
organic molecules;
macromolecules,
DNA,mRNA,protein,Lipids
polysaccharides,
cells,tissues,organs,organism,
populations,ecologies.
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Bottom-up approch
Top-down approch
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Network control （网络控制）
? Structure of the systems (Network)
? The dynamics of such systems
? Methods of control systems
? Methods to design and modify for
desired properties
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Yeast map of
protein–protein
interactions
based on yeast
two-hybrid
method
Protein interaction network
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? Networks
? Random & Regular Networks
? Small-world networks
? Scale-free networks
Types of Network
Network
? A collection of nodes (vertices)
? Connected by edges (links)
? Simply a graph
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Concurrency Control (並行控制 )
A concurrent system is one where multiple
processes exist at
the same time,
These processes
execute in parallel
and potentially
interact with each
other.
Internet banking site.
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2,Robustness （稳健性）
鲁棒性,稳健性,适应性/牢固性,強健性,健壮性控制理论和应用中的 Robustness问题是一个极活跃的研究课题，各种 Robustness 的概念相继提出
? Adaptation（适应性）
the ability to cope with environmental
changes
? Parameters in sensitivity（参数不敏感性）
indicates a relative insensitivity to specific
kinetic parameters
? Graceful degeneration（细微功能退化）
slow degeneration of function after damage
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稳健性 （ Robustness ）
是生物系统的基本特征
Robustness is an essential property of
biological systems,Understanding the
mechanisms and principles underlying
biological robustness is necessary for
an in-depth understanding of biology at
the system level,
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The robustness of a system can manifest
itself in one of two ways,the system
returns to its current attractor or moves to
a new attractor that maintains the system’s
functions.
Robustness is the maintenance of specific
functionalities of the system against
perturbations,and it often requires the
system to change its mode of operation in
a flexible way.
( Nature Review,Genetics 5,826,2004 )
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Explaining
robustness — the
aeroplane
example,
The concept of
robustness is best
described using
the example of
modern aeroplanes.
AFCS：
automatic flight control
system
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3,Maintain of Robustness
? System control（系统控制）,such as
negative- feedback and feed-forward control
? Redundancy（冗余性）,multiple components
of equal functions are introduced for backup
? Modularity（模块性）,subsystems are
physically or functionally insulated so that
failure in one module does not spread
? Structural stability （结构稳定性）
where intrinsic mechanisms are built to
promote stability
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? 系统控制：
前馈控制：开环、简单，仅仅在可能情形与对策都高度可预见情况下使用。
反馈控制：反馈期望值和实际值的反误差输入，使输入信号收到正比于误差的调整。
在生物学过程中扮演着重要角色，如 E.Coli 趋化性，热休克反应，生理节奏，细胞周期以及发育的不同方面。
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P53 related
feedback loop
and feedforward
control
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? 冗余性
应付系统组件的意外损坏。
冗余也可以用来应付统计过程中的不确定性。
Different pathways are used to attain essentially
the same objective function.
MAPK
pathway
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?
模块化
确保系统一部分的失效不会扩散到整个系统。
确保进化过程的高效重构，从而获取新特征。
现在对模块形是如何维持及其原因仍不了解。
? 结构稳定性
一些回路在系统受到多种扰动情况下恢复多个亚应答子回路的一个（糖代谢）。
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Complicacy of
biologic systems
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Biological System Sample(1)
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Biological System Sample(2)
Metabolism
of amino acids
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Biological System Sample(3)
Regulation of insulin and IGF signaling
Science,302( 5651),1710-1711,2003
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系统生物学的研究内容系统生物学的研究内容
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系统生物学的研究包括：
1.生物系统的结构确定
2.生物系统的动力学( dynamics of the system)
它们的定性与定量分析。
3.构建具有强大预测功能的理论模型
（ theory/model ）。
4.生物系统的控制机理( control methods of
the system)。
5.人工设计生物系统调控方法（ Artificial
controls）。
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1,Structure of the systems
These include the network of gene
interactions and biochemical pathways,as
well as the mechanisms by which such
interactions modulate the physical
properties of intracellular and multicellular
structures,
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?基因表达的调控网络 (gene regulation )、
?生物化学的网络 (biochemical networks )、
?物理结构 (physical structures)：
生物体，细胞，细胞器，染色质，等。
?参数系列（ parameter set）等。
多数情况下参数在实验结果基础上推算得到，
又通过实验反复检测确定。参数用于对生物系统的反应和行为的计算机模拟定量分析。
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2,The dynamics of such systems
How a system behaves over time under various
conditions can be understood through:
metabolic analysis,
sensitivity analysis
dynamic analysis methods (such as phase
portrait,相描写 ）
bifurcation analysis（ 二态性 ）
Through identifying essential mechanisms
underlying specific behaviors,
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Bifurcation of p53 Pathway
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3,Methods of control systems
Mechanisms that systematically
control the state of the cell can be
modulated to minimize malfunctions
and provide potential therapeutic
targets for treatment of disease,
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4,Methods to design and modify
for desired properties
Strategies to modify and construct
biological systems having desired
properties can be devised based on
definite design principles and
simulations,instead of blind trial-and-
error.
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Properties of biological systems,such as
robustness,emerge as central issues,and
understanding these properties may have
an impact on the future of medicine,
However,many breakthroughs in
experimental devices,advanced software,
and analytical methods are required before
the achievements of systems biology can
live up to their much-touted potential.
Science,295(5560),1662-1664,2002
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系统生物学的技术和方法系统生物学的技术和方法
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"four M's" of systems biology,
Measurement （ 测量 ）
Mining（ 采集 ）
Modeling（ 建模 ）
Manipulation（ 操纵 ）
Experimental
side
Computational
side
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These four M's are part of an iterative
process,beginning with manipulating
the system,Once a system is perturbed,
it is measured using a high-throughput,
multivariate technology,The data are
then mined to elucidate hypotheses that,
when cast in terms of formal
computational models,form the basis for
a new manipulation of the system.
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基本工作流程
? 了解选定系统所有元素（ element），描绘结构，建立初步模型
? 系统地改变被研究对象的内部组成元素或外部生长条件，观测相应变化。
? 整合相关信息，比较实验数据与模型预测，
修订初始模型。
? 设定和实施实验，重复第二步和第三步，
不断地通过实验数据对模型进行修订和精练。
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“Wet” Experiments of Biological Systems
High throughput and accurate measurements
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在生物系统正在发挥功能的时候研究它们的所有组件的行为和相互作用。综合通过系统开发方法得到的数据，直至系统阐述可以被实验检测的假设；把信息学的方法用于图形可视化，建模和工程化。大量搜集有效数字，系统地干预生物系统，来研究功能基因组学和系统生物学。
大量的结构，功能和生物系统各个组件的相互关系的数据对于理解生物表型来说是必要的，但不足够。
我们需要真正地把生物系统系统化；数据，反馈，冗余和建模能够使系统优化，稳定,有生命力。
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Complete system-level analysis of biological
regulation requires data that are perhaps
beyond the scope of current experimental
practices,Technical innovations in
experimental devices,single-molecule
measurements,femto-lasers that permit
visualization of molecular interactions,and
nano-technologies are critical aspects of
systems biology research,For example,
microfluidic systems,also known as micro-
TAS (total analysis system),enable minute
quantities (picoliters) of samples to be
measured more rapidly and more precisely,
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Gene sequencing
Establishment of a High-Throughput Laboratory
In reality the gels look like this.
Using gels researchers then read
the sequence from it bottom to
top.
An automated DNA sequencer
does this for large scale
readings,(3-4 meters long!)
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基因芯片（ DNA Microarray）
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在基因功能研究基础上，特别是确立了与某些疾病相关基因的表达变化情况后，就可针对疾病发生机理进行药物 筛选工作。将这些基因特异性片段固定在芯片上，研究病变组织和正常组只 在某些药物刺激下这些基因表达的变化，可快速判断药物作用的效果，并进行高通量筛选（high throughout
screening），可使新药开发获得技术上的突破。
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Protein microarray
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Tissue microarray
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Cell microarray
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Lab on chips
7 mm
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Proteomics analysis
mRNA
primary protein
product
mature?
protein
Active
protein
protein
degradation
Transcriptome
Proteome
primary RNA
transcript
DNA
Genome
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蛋白质组学的研究方法，主要包括：
待測蛋白质的分离（ Analytical protein separations）
蛋白质的分解（ Protein digestion）
质谱仪的分析和database的搜寻（ MS analysis and database searching）
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Next Generation Experimental Systems
? Better automation to produce high
throughput experiments
? The use cutting-edge technologies such
as micro-fluid systems,nano-technology
(纳米技术 ) and femto-chemistry (毫微微化学 ) in developing next-generation
experimental devices.
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“Dry” Experiments of Biological Systems
Where do computers come in?
? Systems data mining
? Systems discovery
? Systems simulation
? Systems modeling
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What’s to come?
Development of Precision Models
Simulation requires the integration of multiple
hierarchies(层次 )of models that have different
scales and qualitative properties
Some biological processes take place within
milliseconds while others may take hours or
days,Example,Protein folding vs,Cell Mitosis
Biological processes can involve the interaction
of different types of processes
(i.e,biochemical networks coupled to protein
transport,chromosome dynamics,cell
migration or morphological changes in tissues)
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What’s to come?
? Development of Precision Models
Types of modeling:
?Using differential equations(微分方程) and
stochastic simulation(随机模拟)
?Many cell biological phenomena require
calculation of structural dynamics
?Deformation of elastic bodies(弹性体)
?Spring-mass(分子弹簧) models and other
physical processes
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Consider the system of two masses and two
springs with no external force,Visualize a wall
on the left and to the right a spring,a mass,a
spring and another mass.
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系统组计划（ Systeome）
? 为了促进系统生物学研究，建立一个全面的数据源来描述系统特征十分重要。
系统组 是对所有遗传变异、环境刺激反应下系统特征的组合。
系统特征 包括系统的属性信息，如系统结构及其行为、一些分析结果等。
系统结构 包括基因、代谢网络结构及其相关常数、物理结构及其性质。
系统组不同于简单的级链图，因为它对系统状态而并非静态实体采用了主动的、动态的仿真和剖析。
Computational Biology
2005-3-24 Chaoqun Wu,Fudan University 83
Problems of Knowledge Discovery
? Too much data!
Solution:
use heuristics(启发式演算法 )
use Hidden Markov Model
(HMM,隐马尔可夫模型 )
2005-3-24 Chaoqun Wu,Fudan University 84
Heuristics被译为,启发式演算法,,“助发现法,,
有时也被译为,启发力,,“探试方式,等，与发现的方法论相似的逻辑分析和科学学习功能，
以寻找 可行解 为基础,有效率地求解网路组合最佳化问题（ 最优解 ） 。
有许多计算机化了的启发式方法，可解决达几百、几千的问题。
● 启发力与问题模型,
● 科学发现,
● 类比与隐喻,
● 分析与综合 。
模拟方法
（ simulation）
优化方法
（ optimization）
2005-3-24 Chaoqun Wu,Fudan University 85
隐马尔科夫模型 (Hidden Markov Model,
HMM)是一个二重马尔科夫随机过程，它包括具有状态转移概率的 Markov链和输出观测值的随机过程。其状态是不确定或不可见的，只有通过观测序列的随机过程才能表现出来。按状态的观测概率密度的连续性，隐马尔科夫模型可分为连续隐马尔科夫模型（ Continuous Hidden Markov
Model,CHMM）、半连续隐马尔科夫模型 (Semi-
Continuous Hidden Markov Model,SCHMM)、
离散隐马尔科夫模型 (Discrete Hidden Markov
Model,DHMM).
Nature Biotechnology,2004,22;1315
2005-3-24 Chaoqun Wu,Fudan University 86
Simulation-based Analysis
? Simulation-based analysis tests hypotheses
with in silico experiments,providing
predictions to be tested by in vitro and in
vivo studies,
? faster and more economical,
2005-3-24 Chaoqun Wu,Fudan University 87
Modeling for Gene Expression and Regulation
2005-3-24 Chaoqun Wu,Fudan University 88
Modeling for Intra- and Inter-Cellular Dynamics
2005-3-24 Chaoqun Wu,Fudan University 89
System Behavior Analysis
? Once we understand the structures of the
system,research will focus on dynamic
behaviors of the system.
? How does it adapt to changes in the
environment,such as nutrition,and various
stimuli?
Bifurcation analysis（ 两叉分析 ）
metabolic control analysis(新陈代谢控制分析 )
Sensitivity analysis (灵敏度分析 ).
2005-3-24 Chaoqun Wu,Fudan University 90
? Simulation
系统行为分析方法－模拟
2005-3-24 Chaoqun Wu,Fudan University 91
SBML(Systems Biology Markup Language)
SBML是一个基于XML的描述语言，用于用系统生物学表达计算模型。
(http://sourceforge.net/projects/sbml/)
? a description language for simulations in
systems biology
? meant to support non-spatial biochemical
models and the kinds of operations that are
possible in existing analysis/simulation tools
2005-3-24 Chaoqun Wu,Fudan University 92
Future of SBML
? Arrays（线阵）
? Connections（联结）
? Database Interoperability（互用性）
? Geometry （几何学）
? Submodels（子模型）
? Component Identification（成分识别）
? References （参照）
? Diagrams（图解）
2005-3-24 Chaoqun Wu,Fudan University 93
系统生物学的钥匙 —干涉（ perturbation）
对实验对象的人为影响。
? 系统生物学中的干涉的特点：
系统性。例如人为诱导基因突变，过去大多是随机的；而在进行系统生物学研究时，应该采用的是定向的突变技术。
高通量的干涉能力。如高通量的遗传变异。
随着研究技术的发展，一定还会有许多新的干涉技术应用于系统生物学。
2005-3-24 Chaoqun Wu,Fudan University 94
E-cell
E-CELL is actually a model-building kit,a set
of software tools that allows a user to specify
a cell's genes,proteins,and other molecules,
describe their individual interactions,and then
compute how they work together as a system,
It should ultimately allow investigators to
conduct experiments "in silico," offering a
cheap,fast way to screen drug candidates,
study the effects of mutations or toxins,or
simply probe the networks that govern cell
behavior,(www.e-cell.org)
2005-3-24 Chaoqun Wu,Fudan University 95
Stripped-down cell.
Biochemistry simulated by E-CELL Software.
2005-3-24 Chaoqun Wu,Fudan University 96
Advantages of Computational
Systems Biology
? It is highly relevant in discovering more
complex relationships involving multiple
genes
? This may create new opportunities for drug
discovery
? Better medical therapies for individual
treatments
The Physiome Project,Available,
[online] http://www.physiome.org
(February 2003)
The Physiome Project
(生理组计划 )
?,A worldwide effort to define the physiome
by developing databases and models which
will facilitate the understanding of the
integrative functions of cells,organs and
organisms.”
def,Physiome is the quantitative and integrated
description of the functional behavior of the
physiological state of an individual or species.
2005-3-24 Chaoqun Wu,Fudan University 98
1989年美国国立医学图书馆（NLM）发起可视人计划（ Visible Human Project)；美国国家橡树岭实验室（ORNL）1996年开始虚拟人计划 (Virtual Human
Project Initiative)；1997年华盛顿大学发起了 生理人计划 (The Physiome Project)；由韩国可视人计划于2000年开始；日本从2002年起实施,日本虚拟人计划,。在欧洲，除了汉堡大学著名的Voxel-Man系统之外，还有英国和法国的项目。九十年代，多位中国科学家开始筹划中国数字化虚拟人计划，包括中国数字人模型数据的获取方案与技术、医学图像处理方法学和数字化虚拟人体应用及平台等。最大特点是以医学和计算机科学为中心的跨领域的多学科交叉。
2005-3-24 Chaoqun Wu,Fudan University 99
The Physiome Project
Main Objective:
“… to understand and
describe the human
organism,its
physiology and
pathophysiology
quantitatively,and to
use this understanding
to improve human
health.”
2005-3-24 Chaoqun Wu,Fudan University 100
The Physiome Project
Specific Objectives:
1,To develop and database observations of
physiological phenomenon and interpret
these in terms of mechanism (a
fundamentally reductionist goal).
2,To integrate experimental information into
quantitative descriptions of the functioning
of humans and other organisms (modern
integrative biology glued together via
modeling).
3,To disseminate experimental data and
integrative models for teaching and
research.
2005-3-24 Chaoqun Wu,Fudan University 101
The Physiome Project
Specific Objectives:
4,To foster collaboration amongst
investigators worldwide,in an effort to speed
up the discovery of how biological systems
work.
5,To determine the most effective targets
(molecules or systems) for therapy,either
pharmaceutic or genomic.
6,To provide information for the design tissue-
engineered,biocompatible implants.
2005-3-24 Chaoqun Wu,Fudan University 102
The Physiome Project
Sub-Projects
1,Microcirculation
A common functional
system between organs; It
provides an important
coupling between cells,
tissues,and organs.
Available [online],
http://www.bme.jhu.edu/news/microp
hys
2005-3-24 Chaoqun Wu,Fudan University 103
The Physiome Project
Sub-Projects
2,Musculo-skeletal
system
Continues to extend the
database of
parameterised bone
geometry to individual
muscles,ligaments and
tendons.
Available [online],
http://www.bioeng.auckland.ac.n
z/projects/nerf/skeletal.php
(a) (b)
(a) Anatomically detailed model of
Skeleton.
(b) Rendered finite element mesh for
the bones and a subset of the muscles
2005-3-24 Chaoqun Wu,Fudan University 104
The Physiome Project
Sub-Projects
(a) (b)
Computational model of the skull and torso,(a) The layer of
skeletal muscle is highlighted,(b) The heart and lungs
shown within the torso.
2005-3-24 Chaoqun Wu,Fudan University 105
The Physiome Project
Sub-Projects
3,Cardiome Project
An attempt to provide an
integrated model of the
heart,incorporating
electrical activation,
mechanical contraction,
energy supply and
utilization,cell signaling
and many other
biochemical processes.
Heart model with a textured
epidermal surface
2005-3-24 Chaoqun Wu,Fudan University 106
The Physiome Project
A) Heart Structure
(a) (b) (c)
Fibrous-sheet architecture of the heart,Ribbons are drawn in the plane of
the myocardial sheets (a) on the epicardial surface of the heart,(b) at
midwall,and (c) on the endocardial surface,Note the large fibre angle
changes,These fibre-sheet material axes are needed for computation of
both myocardial activation and ventricular mechanics.
2005-3-24 Chaoqun Wu,Fudan University 107
The Physiome Project
A) Heart Structure
The finite element model of the right and left ventricle of the heart
showing various anatomical structures,Geometric information is carried
at the nodes of the finite element mesh and interpolated with cubic
Hermite basis functions.
2005-3-24 Chaoqun Wu,Fudan University 108
The Physiome Project
B) Ventricular Mechanics
Mechanics of the cardiac cycle,computed by large deformation finite element
analysis,at (a) zero pressure state,(b) end-diastole,(c) mid-systole,(d) end-
systole,Note the apex to base shortening and the twisting about the long axis,
Also note the six generations of discretely modeled coronary vessels embedded
within the myocardial elements which are used to compute coronary flow
throughout the cardiac cycle.
2005-3-24 Chaoqun Wu,Fudan University 109
The Physiome Project
B) Ventricular Mechanics
The collagenous structure of the
extracellular myocardial tissue
matrix,as revealed by confocal
microscopy,The material axes
used for defining mechanical and
electrical constitutive laws in the
continuum modeling of the
myocardium are based on these
microstructurally defined axes.
2005-3-24 Chaoqun Wu,Fudan University 110
The Physiome Project
C) Myocardial Activation
Activation wavefront computed on the finite element model using
finite difference techniques based on grid points which move with the
deforming myocardium,Bidomain current conservation equations
are solved with transmembrane ionic currents,The stimulus in this
case is a point on the left ventricular endocardial surface near the
apex,The activation sequence is heavily influenced by the fibrous-
sheet architecture of the myocardium.
2005-3-24 Chaoqun Wu,Fudan University 111
The Physiome Project
E) Ventricular Fluid Flow
F) Human Torso
model has been developed
which includes the heart,
lungs and the layers of
skeletal muscle,fat and skin,
Current flow from the heart
into the torso is computed in
order to predict the body
surface potentials arising
from activation of the
myocardium.
D) Coronary Perfusion
Computed flow in the
coronary vasculature
2005-3-24 Chaoqun Wu,Fudan University 112
The Physiome Project
Sub-Projects
4,Lungs
Development of models of the
integrated function of various
physical processes operating
in the lung.
5,Bladder and Prostate
An anatomically detailed
model of the bladder and
prostate is developed,
6,Circulation System
A model of the circulation
system is being developed
based on the Visual Human
Project dataset
(http://www.nlm.nih.gov/resear
ch/visible)
2005-3-24 Chaoqun Wu,Fudan University 113
癌的系统生物学癌的系统生物学
2005-3-24 Chaoqun Wu,Fudan University 114
Integrative Cancer Biology
Program (ICBP)
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2005-3-24 Chaoqun Wu,Fudan University 115
ICBP Goals
? To promote the analysis of cancer as a complex
biological system,with an ultimate goal of
developing reliably predictive in silico or
computational models of cancer initiation and
progression and for the development of cancer
interventions.
? Integrate experimental and computational
approaches towards the understanding of
cancer biology.
? Encourage the emergence of integrative cancer
biology as a distinct field,
2005-3-24 Chaoqun Wu,Fudan University 116
Cancer Complexity:,The Black Box”
Cell,parts
list”
Genome
Transcrip-
tome
Proteome
Metabalome
Interactome
Location
Stochiometry
Stability
Modification
Variation
Organelle
Micro-
environment
Macro-
environment
Histology
Physiology
Tissue
Organism
2005-3-24 Chaoqun Wu,Fudan University 117
Challenge,Addressing the
Complexities of Cancer Research
? Complexity of Cancer:
Multiplicity of cancer types
Multiplicity of genes and networks
Micro and macro environmental effects
Dynamic systems
?Initiation
?Progression
?Metastasis
? Complexity of Information
,omic” approaches
?Genome,transcriptome,proteome,interactome
Sophistication of data
2005-3-24 Chaoqun Wu,Fudan University 118
Opportunities
? Large scale data sets are available
Human and mouse genome
? Modeling or Systems Design being applied
to biological problems
? Necessary infrastructure,in place”
? Multi-discipline interactions and
associations more common
?,Systems Biology” is here
2005-3-24 Chaoqun Wu,Fudan University 119
Data/Obser
-vation
Model Generation,Dry”
Model
Refinement
Hypothesis
generation
Experimental,Wet” Validation
2005-3-24 Chaoqun Wu,Fudan University 120
?Practical Application:
Predict function of critical molecules,
pathways,cells and disease states
Identify and validate potential
therapeutic and diagnostic molecules
Complement the development of
animal model systems
Develop predictive in silico
surrogates for therapeutic studies
2005-3-24 Chaoqun Wu,Fudan University 121
Outline of the Integrative Cancer
Biology Program (ICBP)
? Establish multidisciplinary Programs
with the expertise,knowledge,and
infrastructure necessary to undertake a
systems approach to cancer
2005-3-24 Chaoqun Wu,Fudan University 122
?Programs will be structured to enhance
our understanding of cancer biology,
Potential areas of focus include:
Mechanisms of gene expression
Metabolic networks and components
in cell physiology
Cancer-related pathology
Signaling networks and the control of
cellular processes
Cell-cell and cell-matrix interactions
2005-3-24 Chaoqun Wu,Fudan University 123
Cancer robustness
Viewing cancer as a robust
System with potential points of
fragility opens up new strategies
for the development of drugs and
therapies.
2005-3-24 Chaoqun Wu,Fudan University 124
Robustness allows tumours to promote
growth and survival in several ways,
For example,heterogeneity among
tumour cells provides a high level of
redundancy,and hence increased
chances of survival and growth; these
benefits are further enhanced by
feedback controls at the cellular level.
2005-3-24 Chaoqun Wu,Fudan University 125
We need to find a method that will systematically
control the cell’s activities,such as the cell cycle,
growth decisions and apoptosis,
Computer simulations have shown that a cell
cycle that is robust against certain perturbations
can be made extremely fragile when specific
feedback loops are removed or attenuated,
meaning that the cell cycle can be arrested with
minimum perturbation.
2005-3-24 Chaoqun Wu,Fudan University 126
The computational results suggest that
robustness can be controlled by carefully
selecting modulation targets and the
systematic use of multiple drugs.
This ‘systems drug-discovery’ approach
aims to control the cell’s dynamics,
rather than its components,and although
only speculative at present,may turn out
to be critical for the development of new
cancer therapies,
2005-3-24 Chaoqun Wu,Fudan University 127
系统生物学对医学的影响系统生物学对医学的影响
2005-3-24 Chaoqun Wu,Fudan University 128
系统生物学的影响系统生物学必然对医学研究与实践产生巨大的影响 。
首先，个体系统组的快速、精确测量将使我们可以精确的评估、模拟疾病的危险。
其次每个病人精确的系统动力学可以改变药物设计和治疗程序，可以减少副作用，维持疾病治疗的最大效果。
第三，系统水平地理解，特别是仿真、控制、
设计能力为器官克隆提供全新地方法。加速系统水平生物学技术发展的最佳方法。
2005-3-24 Chaoqun Wu,Fudan University 129
Impact of Systems Biology
? Combined with genomic
and other projects,it
may have major
impacts on medical
research and practice.
? In-depth knowledge of
dynamical state of cells
and development of
high-performance
measurements will
drastically change
medical practice.
2005-3-24 Chaoqun Wu,Fudan University 130
The global tools of systems biology are
rapidly moving us toward predictive
medicine,For example,the technique of
single DNA molecule sequencing will move
us toward the rapid and inexpensive
sequencing of entire human genomes over
the next 10-15 years,This would allow us to
search through hundreds,if not thousands
of combinations of genes that might
predispose individuals to a late onset
disease (such as cancer,cardiovascular
disease,diabetes,etc.) and determine a
probabilistic health history for each,
2005-3-24 Chaoqun Wu,Fudan University 131
Linkage of a basic systems biology
research cycle with drug discovery
and treatment cycles
2005-3-24 Chaoqun Wu,Fudan University 132
With sufficient progress in basic systems
biology,this cycle can be applied to drug
discovery and the development of new
treatments,In the future,in silico
experiments and screening of lead
candidates and multiple drug systems,as
well as introduced genetic circuits,will
have a key role in the 'upstream'
processes of the pharmaceutical industry,
significantly reducing costs and
increasing the success of product and
service development.
2005-3-24 Chaoqun Wu,Fudan University 133
Medical systems biology
Medical systems biology has generated
widespread interest because of its bold
conception and exciting potential,but the
field is still in its infancy.
?metabolomics,
?proteomics,
?data handling
?multivariate biostatistics
2005-3-24 Chaoqun Wu,Fudan University 134
Interest in the application of systems biology
to the life sciences has become widespread
over the past five years,although systems
perspectives have been applied to many
sciences,ranging from biology to cosmology,
since at least the beginning of the 20th
century.
Current Opinion in Chemical Biology
2004,8:559–565
2005-3-24 Chaoqun Wu,Fudan University 135
Biochemical Networks
2005-3-24 Chaoqun Wu,Fudan University 136
2005-3-24 Chaoqun Wu,Fudan University 137
Discover the biomarkers of diseases
An important principal for the discovery of
biomarkers for drug discovery,drug
development and disease diagnosis is that
multi-factorial disease involves studying
complex and dynamic biomarker patterns
rather than a single biomarker such as
cholesterol,prostate-specific antigen or glucose.
Different biomarker profiles are found at the
onset of a disease versus the late stage where
symptoms and indirect effects are prominent.
2005-3-24 Chaoqun Wu,Fudan University 138
The development of disease from healthy (homeostasis within black
dotted lines) to sub-optimal health and eventually an overt disease state.
Biomarker patterns (for graphical reasons represented as a single line)
are essential to describe the changes from normality
to dysfunction.
—Adapted from,Metabolic Profiling,2003,Kluwer
Academic Publishers.
2005-3-24 Chaoqun Wu,Fudan University 139
Systemic tools to identify
disease biomarkers
?Metabolome analysis
— NMR and hyphenated MS technology
— Nanoprobe technology
?proteome analysis
— iTRAQ (isobaric tags for relative and
absolute quantification)
— direct tissue profiling and imaging mass
spectrometry
?From data to information and knowledge
2005-3-24 Chaoqun Wu,Fudan University 140
The correlation network of all biomarkers found in a
study on the early onset of atherosclerosis in the
ApoE3 transgenic mouse model.
2005-3-24 Chaoqun Wu,Fudan University 141
Disease Map Created From Disease-
specific Pathways
2005-3-24 Chaoqun Wu,Fudan University 142
Drug Toxicity Prediction
Prediction of Pyrazinamide（吡嗪酰胺） Side Effects
2005-3-24 Chaoqun Wu,Fudan University 143
Tissue-specific Maps for Human Metabolism
The functional models are tissue-specific,i.e,they consist of the
pathways predominantly active in a particular tissue and/or disease
condition,
2005-3-24 Chaoqun Wu,Fudan University 144
Systems Reconstruction Map,Signaling pathways and cascades that regulate
fatty acid oxidation in hepatocytes
2005-3-24 Chaoqun Wu,Fudan University 145
小结
? System biology is a new and emerging field
in biology
? A long ways to go before understanding
biological systems
? Systems biology will be the dominant
paradigm in biology,and many medical
applications as well as scientific discoveries
are expected.
2005-3-24 Chaoqun Wu,Fudan University 146
Although systems biology is in its infancy,
its potential benefits are enormous in
both scientific and practical terms,A
transition is occurring in biology from the
molecular level to the system level that
promises to revolutionize our
understanding of complex biological
regulatory systems and to provide major
new opportunities for practical application
of such knowledge.
2005-3-24 Chaoqun Wu,Fudan University 147
“系统生物学将是21世纪医学和生物学的核心驱动力,
——莱诺伊 ·胡德（ Leroy Hood）
J Proteome Res,2002
2005-3-24 Chaoqun Wu,Fudan University 148
References:
1,Ideker T,Thorsson V,et al,Integrated genomic and proteomic
analyses of a systematically perturbed metabolic network,
Science( 2001)
2,H,Kitano,Systems Biology,A brief overview,Science,295(2002),
1662-1664
3,Eldar A,Dorfman R,Weiss D,Ashe H,Shilo BZ,Barkai N.,
Robustness of the BMP morphogen gradient in Drosophila embryonic
patterning,Nature (2002)
4,Charles Auffray et al,Molecular biology and genetics From functional
genomics to systems biology,concepts and practices,Biologies 326
(2003) 879–892
5,Alan Aderema,Kelly D,Smith,A systems approach to dissecting
immunity and inflammation,Seminars in Immunology 16 (2004) 55–
67
6,EDITORIAL,Scaling cell biology,all systems go! Nature cell biology,
6 (2004) 79
7,Jason A,Papin et al,Reconstruction of cellular signalling networks and
analysis of their properties,Nature reviews,molecular cell biology
6(2005),99-111.
2005-3-24 Chaoqun Wu,Fudan University 149
Thank you
Systems Biology
复旦大学生命科学学院 吴超群
Chaoqun Wu
The School of Life Sciences
Fudan University
2005-3-24 Chaoqun Wu,Fudan University 2
系统生物学是继人类基因组计划后，
又一个解密生命奥秘的新探索
A new approach to decoding life:
Systems Biology
2005-3-24 Chaoqun Wu,Fudan University 3
讨论的内容
? 什么是系统生物学?
? 什么是生物系统?
? 系统生物学的研究内容
? 系统生物学的技术和方法
? 系统组学（Systeome）
? 癌的系统生物学
? 系统生物学对医学的影响
? 小结
2005-3-24 Chaoqun Wu,Fudan University 4
Approach on human body
Bottom-up
Top-down
整体水平 细胞水平 分子水平器官水平系统生物学
2005-3-24 Chaoqun Wu,Fudan University 5
什么是系统生物学?
什么是系统生物学?
2005-3-24 Chaoqun Wu,Fudan University 6
系统论的创始人是美籍奥地利理论 生物学家 路德维格 ·贝塔朗菲。
系统论是研究系统的一般模式，结构和规律的学问，它研究各种系统的共同特征，用数学方法定量地描述其功能，寻求并确立适用于一切系统的原理、
原则和数学模型，是具有逻辑和数学性质的一门新兴的科学。
研究和认识系统的目的之一，就在于有效地控制和管理系统。控制论 (Cybernetics)则为人们对系统的管理和控制提供了一般方法论的指导，它是数学、
自动控制、电子技术、数理逻辑、生物科学等学科和技术相互渗透而形成的综合性科学。
关于系统论 （ System Theory）
2005-3-24 Chaoqun Wu,Fudan University 7
系统论通常把系统定义为：由若干要素以一定结构形式联结构成的具有某种功能的有机整体。在这个定义中包括了 系统,
要素,结构,功能 四个概念，表明了要素与要素、要素与系统、系统与环境三方面的关系。
系统论认为，整体性、关联性，等级结构性、动态平衡性、时序性等是所有系统的共同的基本特征。
2005-3-24 Chaoqun Wu,Fudan University 8
A systems biology view...
Life‘s Complexity Pyramid (Oltvai-Barabasi,Science 10/25/02)
Components
Building
Blocks
Functional
Modules
System
2005-3-24 Chaoqun Wu,Fudan University 9
Dynamic Systems
2005-3-24 Chaoqun Wu,Fudan University 10
系统生物学是生命科学研究领域的一门新兴学科。
系统生物学是研究一个生物系统中所有组成成分的构成及其在特定条件下相互关系的、以整体性研究为特征一种大学科。
2005-3-24 Chaoqun Wu,Fudan University 11
“系统的水平,与分子的水平不同，
它的研究重点不是在个别核苷酸或蛋白质分子的序列及其功能，而是在由核苷酸、蛋白质、脂质、多糖等分子组成的生物系统。
系统生物学的研究也不是简单地堆积分子生物学研究的结果，而是以 系统论的观点,动态的观点,多样性的观点和 进化的观点 来分析实验结果，研究生物系统。
2005-3-24 Chaoqun Wu,Fudan University 12
Molecular vs,Systems
Biology Biology
? In molecular biology,
gene structure and
function is studied at
the molecular level.
? In systems biology,
specific interactions of
components in the
biological system are
studied – cells,tissues,
organs,and ecological
webs.
2005-3-24 Chaoqun Wu,Fudan University 13
系统生物学的任务是用系统方法实现生物学的革命，并且紧密联系医学应用。
? It is analogous to a static roadmap,whereas
what we really seek to know are the traffic
patterns,why such traffic patterns emerge,
and how we can control them.
Hiroaki Kitano,Science,1 March 2002
2005-3-24 Chaoqun Wu,Fudan University 14
研究方向系统生物学刚刚开始发展，其研究方向有待逐步明确。仅从系统生物学研究院和几次国际学术会议看，所进行的研究方向有：蛋白质组学；遗传网络；代谢网络、发育；空间、结构系统生物学；硅细胞；超细胞系统生物学；计算生物学；软件构架，系统生物学研究的软件平台；系统分析，模式识别，
动力系统理论和代谢控制分析；等等。
2005-3-24 Chaoqun Wu,Fudan University 15
? Biology went top-down for the last 50 years
From cell to protein to gene,.
Huge amounts of data produced
Challenge,put the pieces back together again
? Attempts to create predictive models of cells,
organs,biochemical processes and complete
organisms
Data combined with computational,mathematical
and engineering disciplines
Model simulations experiment
2005-3-24 Chaoqun Wu,Fudan University 16
Systems Biology
Research
Cycle Vision
2005-3-24 Chaoqun Wu,Fudan University 17
系统生物学的特点
?Integrative approach
(整合性研究 )
?Large experimental datasets
(大量的实验数据 )
?Predictive modelling
(预测性模型 )
? Interdisciplinarity
(多学科交叉 )
2005-3-24 Chaoqun Wu,Fudan University 18
整合是系统生物学的灵魂
?信息整合
?研究思路整合
?方法的整合
Systems biology is an integrated process
? Quantitative experiments
? System analysis
? Technology development for experiments
? Computational modeling
2005-3-24 Chaoqun Wu,Fudan University 19
两大类型的信息 整合
第一类信息是指编码蛋白质的基因
第二类信息是指控制基因行为的调控网络。
? 生物信息是有等级次序，沿着不同的层次流动。
DNA→mRNA→蛋白质→蛋白质相互作用网络
→细胞→器官→个体→群体→ 生态。
? 每个层次信息都对理解生命系统运行提供有用的视角。
系统生物学的重要任务就是要尽可能地获得每个层次的信息并将它们进行整合
2005-3-24 Chaoqun Wu,Fudan University 20
整合的内容：
? Factor comprehensiveness:
系统内不同性质的构成要素的整合,如基因、
mRNA、蛋白质、生物小分子等
? Time-line comprehensiveness:
the time frame within which measurements
are made 时间系列的整合
? Item comprehensiveness:
such as mRNA and protein concentrations,
phosphorylation 要素变化的整合总之，对多细胞生物而言，实现从基因到细胞、
组织、器官、系统、个体的各个层次的整合。
2005-3-24 Chaoqun Wu,Fudan University 21
整合的策略：
? 选定一个较为简单的系统，分析尽可能多的构成成分 ——基因组、转录组、蛋白质组、
相互作用组，以揭示整个系统的行为，代表人物：胡德和系统生物学研究所
? 以一个较为复杂的系统为研究对象，采用尽可能多的研究手段去进行分析。代表人物：
吉尔曼（ A,G,Gilman）及其领导的,信号转导同盟,
2005-3-24 Chaoqun Wu,Fudan University 22
A bigger picture of Systems
Biology
2005-3-24 Chaoqun Wu,Fudan University 23
According to a well-accepted tradition,the 5
th
International
conference on Systems Biology 2004programme committee
has coined a moto for the conference in 2004,"Systems
Biology - From Bioscience to Medicine".
Following this guideline session topics for the conference
were chosen that encompass the understanding of
metabolic and signal transduction systems,bacterial
systems biology,hepatocytes and their implication
for systems biology for medicine,and spatial models.
2005-3-24 Chaoqun Wu,Fudan University 24
2005-3-24 Chaoqun Wu,Fudan University 25
什么是生物系统?
什么是生物系统?
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What are biological systems?
? Question is,what do we mean by
biological systems?
? By,system”,we mean a bunch of parts
that are connected to one another and
work together,
2005-3-24 Chaoqun Wu,Fudan University 27
What are Biological Systems?
Popular Notion:
It is a complex system consisting of
very many simple and identical elements
interacting to produce what appears to
be complex behavior
Example,Cells,Proteins
2005-3-24 Chaoqun Wu,Fudan University 28
What are Biological Systems?
Realistic Notion:
It is a system composed of many different
kinds of multifunctional elements
interacting selectively and nonlinearly
with others to produce coherent behavior.
2005-3-24 Chaoqun Wu,Fudan University 29
What are Biological Systems?
? Complex systems of simple elements
have functions that emerge from the
properties of the networks they form.
? Biological systems have functions that
rely on a combination of the network
and the specific elements involved.
2005-3-24 Chaoqun Wu,Fudan University 30
Biological systems ranges from:
? Ecosystems to the system of reactions
that form cellular biochemistry.
? Usually,we refer to the latter,systems of
biochemical reactions that make cells
work.
? It is often said that biological systems,
such as cells,are 'complex
systems'
2005-3-24 Chaoqun Wu,Fudan University 31
Features of biological systems
1,Composed of biological elements
（由生物元素组成）
small molecules:
water,inorganic molecules,
organic molecules;
macromolecules,
DNA,mRNA,protein,Lipids
polysaccharides,
cells,tissues,organs,organism,
populations,ecologies.
2005-3-24 Chaoqun Wu,Fudan University 32
Bottom-up approch
Top-down approch
2005-3-24 Chaoqun Wu,Fudan University 33
Network control （网络控制）
? Structure of the systems (Network)
? The dynamics of such systems
? Methods of control systems
? Methods to design and modify for
desired properties
2005-3-24 Chaoqun Wu,Fudan University 34
Yeast map of
protein–protein
interactions
based on yeast
two-hybrid
method
Protein interaction network
2005-3-24 Chaoqun Wu,Fudan University 35
? Networks
? Random & Regular Networks
? Small-world networks
? Scale-free networks
Types of Network
Network
? A collection of nodes (vertices)
? Connected by edges (links)
? Simply a graph
2005-3-24 Chaoqun Wu,Fudan University 36
Concurrency Control (並行控制 )
A concurrent system is one where multiple
processes exist at
the same time,
These processes
execute in parallel
and potentially
interact with each
other.
Internet banking site.
2005-3-24 Chaoqun Wu,Fudan University 37
2,Robustness （稳健性）
鲁棒性,稳健性,适应性/牢固性,強健性,健壮性控制理论和应用中的 Robustness问题是一个极活跃的研究课题，各种 Robustness 的概念相继提出
? Adaptation（适应性）
the ability to cope with environmental
changes
? Parameters in sensitivity（参数不敏感性）
indicates a relative insensitivity to specific
kinetic parameters
? Graceful degeneration（细微功能退化）
slow degeneration of function after damage
2005-3-24 Chaoqun Wu,Fudan University 38
稳健性 （ Robustness ）
是生物系统的基本特征
Robustness is an essential property of
biological systems,Understanding the
mechanisms and principles underlying
biological robustness is necessary for
an in-depth understanding of biology at
the system level,
2005-3-24 Chaoqun Wu,Fudan University 39
The robustness of a system can manifest
itself in one of two ways,the system
returns to its current attractor or moves to
a new attractor that maintains the system’s
functions.
Robustness is the maintenance of specific
functionalities of the system against
perturbations,and it often requires the
system to change its mode of operation in
a flexible way.
( Nature Review,Genetics 5,826,2004 )
2005-3-24 Chaoqun Wu,Fudan University 40
Explaining
robustness — the
aeroplane
example,
The concept of
robustness is best
described using
the example of
modern aeroplanes.
AFCS：
automatic flight control
system
2005-3-24 Chaoqun Wu,Fudan University 41
3,Maintain of Robustness
? System control（系统控制）,such as
negative- feedback and feed-forward control
? Redundancy（冗余性）,multiple components
of equal functions are introduced for backup
? Modularity（模块性）,subsystems are
physically or functionally insulated so that
failure in one module does not spread
? Structural stability （结构稳定性）
where intrinsic mechanisms are built to
promote stability
2005-3-24 Chaoqun Wu,Fudan University 42
? 系统控制：
前馈控制：开环、简单，仅仅在可能情形与对策都高度可预见情况下使用。
反馈控制：反馈期望值和实际值的反误差输入，使输入信号收到正比于误差的调整。
在生物学过程中扮演着重要角色，如 E.Coli 趋化性，热休克反应，生理节奏，细胞周期以及发育的不同方面。
2005-3-24 Chaoqun Wu,Fudan University 43
P53 related
feedback loop
and feedforward
control
2005-3-24 Chaoqun Wu,Fudan University 44
? 冗余性
应付系统组件的意外损坏。
冗余也可以用来应付统计过程中的不确定性。
Different pathways are used to attain essentially
the same objective function.
MAPK
pathway
2005-3-24 Chaoqun Wu,Fudan University 45
?
模块化
确保系统一部分的失效不会扩散到整个系统。
确保进化过程的高效重构，从而获取新特征。
现在对模块形是如何维持及其原因仍不了解。
? 结构稳定性
一些回路在系统受到多种扰动情况下恢复多个亚应答子回路的一个（糖代谢）。
2005-3-24 Chaoqun Wu,Fudan University 46
Complicacy of
biologic systems
2005-3-24 Chaoqun Wu,Fudan University 47
Biological System Sample(1)
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Biological System Sample(2)
Metabolism
of amino acids
2005-3-24 Chaoqun Wu,Fudan University 49
Biological System Sample(3)
Regulation of insulin and IGF signaling
Science,302( 5651),1710-1711,2003
2005-3-24 Chaoqun Wu,Fudan University 50
系统生物学的研究内容系统生物学的研究内容
2005-3-24 Chaoqun Wu,Fudan University 51
系统生物学的研究包括：
1.生物系统的结构确定
2.生物系统的动力学( dynamics of the system)
它们的定性与定量分析。
3.构建具有强大预测功能的理论模型
（ theory/model ）。
4.生物系统的控制机理( control methods of
the system)。
5.人工设计生物系统调控方法（ Artificial
controls）。
2005-3-24 Chaoqun Wu,Fudan University 52
1,Structure of the systems
These include the network of gene
interactions and biochemical pathways,as
well as the mechanisms by which such
interactions modulate the physical
properties of intracellular and multicellular
structures,
2005-3-24 Chaoqun Wu,Fudan University 53
?基因表达的调控网络 (gene regulation )、
?生物化学的网络 (biochemical networks )、
?物理结构 (physical structures)：
生物体，细胞，细胞器，染色质，等。
?参数系列（ parameter set）等。
多数情况下参数在实验结果基础上推算得到，
又通过实验反复检测确定。参数用于对生物系统的反应和行为的计算机模拟定量分析。
2005-3-24 Chaoqun Wu,Fudan University 54
2,The dynamics of such systems
How a system behaves over time under various
conditions can be understood through:
metabolic analysis,
sensitivity analysis
dynamic analysis methods (such as phase
portrait,相描写 ）
bifurcation analysis（ 二态性 ）
Through identifying essential mechanisms
underlying specific behaviors,
2005-3-24 Chaoqun Wu,Fudan University 55
Bifurcation of p53 Pathway
2005-3-24 Chaoqun Wu,Fudan University 56
3,Methods of control systems
Mechanisms that systematically
control the state of the cell can be
modulated to minimize malfunctions
and provide potential therapeutic
targets for treatment of disease,
2005-3-24 Chaoqun Wu,Fudan University 57
4,Methods to design and modify
for desired properties
Strategies to modify and construct
biological systems having desired
properties can be devised based on
definite design principles and
simulations,instead of blind trial-and-
error.
2005-3-24 Chaoqun Wu,Fudan University 58
Properties of biological systems,such as
robustness,emerge as central issues,and
understanding these properties may have
an impact on the future of medicine,
However,many breakthroughs in
experimental devices,advanced software,
and analytical methods are required before
the achievements of systems biology can
live up to their much-touted potential.
Science,295(5560),1662-1664,2002
2005-3-24 Chaoqun Wu,Fudan University 59
2005-3-24 Chaoqun Wu,Fudan University 60
系统生物学的技术和方法系统生物学的技术和方法
2005-3-24 Chaoqun Wu,Fudan University 61
"four M's" of systems biology,
Measurement （ 测量 ）
Mining（ 采集 ）
Modeling（ 建模 ）
Manipulation（ 操纵 ）
Experimental
side
Computational
side
2005-3-24 Chaoqun Wu,Fudan University 62
These four M's are part of an iterative
process,beginning with manipulating
the system,Once a system is perturbed,
it is measured using a high-throughput,
multivariate technology,The data are
then mined to elucidate hypotheses that,
when cast in terms of formal
computational models,form the basis for
a new manipulation of the system.
2005-3-24 Chaoqun Wu,Fudan University 63
基本工作流程
? 了解选定系统所有元素（ element），描绘结构，建立初步模型
? 系统地改变被研究对象的内部组成元素或外部生长条件，观测相应变化。
? 整合相关信息，比较实验数据与模型预测，
修订初始模型。
? 设定和实施实验，重复第二步和第三步，
不断地通过实验数据对模型进行修订和精练。
2005-3-24 Chaoqun Wu,Fudan University 64
“Wet” Experiments of Biological Systems
High throughput and accurate measurements
2005-3-24 Chaoqun Wu,Fudan University 65
在生物系统正在发挥功能的时候研究它们的所有组件的行为和相互作用。综合通过系统开发方法得到的数据，直至系统阐述可以被实验检测的假设；把信息学的方法用于图形可视化，建模和工程化。大量搜集有效数字，系统地干预生物系统，来研究功能基因组学和系统生物学。
大量的结构，功能和生物系统各个组件的相互关系的数据对于理解生物表型来说是必要的，但不足够。
我们需要真正地把生物系统系统化；数据，反馈，冗余和建模能够使系统优化，稳定,有生命力。
2005-3-24 Chaoqun Wu,Fudan University 66
Complete system-level analysis of biological
regulation requires data that are perhaps
beyond the scope of current experimental
practices,Technical innovations in
experimental devices,single-molecule
measurements,femto-lasers that permit
visualization of molecular interactions,and
nano-technologies are critical aspects of
systems biology research,For example,
microfluidic systems,also known as micro-
TAS (total analysis system),enable minute
quantities (picoliters) of samples to be
measured more rapidly and more precisely,
2005-3-24 Chaoqun Wu,Fudan University 67
Gene sequencing
Establishment of a High-Throughput Laboratory
In reality the gels look like this.
Using gels researchers then read
the sequence from it bottom to
top.
An automated DNA sequencer
does this for large scale
readings,(3-4 meters long!)
2005-3-24 Chaoqun Wu,Fudan University 68
基因芯片（ DNA Microarray）
2005-3-24 Chaoqun Wu,Fudan University 69
在基因功能研究基础上，特别是确立了与某些疾病相关基因的表达变化情况后，就可针对疾病发生机理进行药物 筛选工作。将这些基因特异性片段固定在芯片上，研究病变组织和正常组只 在某些药物刺激下这些基因表达的变化，可快速判断药物作用的效果，并进行高通量筛选（high throughout
screening），可使新药开发获得技术上的突破。
2005-3-24 Chaoqun Wu,Fudan University 70
Protein microarray
2005-3-24 Chaoqun Wu,Fudan University 71
Tissue microarray
2005-3-24 Chaoqun Wu,Fudan University 72
Cell microarray
2005-3-24 Chaoqun Wu,Fudan University 73
Lab on chips
7 mm
2005-3-24 Chaoqun Wu,Fudan University 74
Proteomics analysis
mRNA
primary protein
product
mature?
protein
Active
protein
protein
degradation
Transcriptome
Proteome
primary RNA
transcript
DNA
Genome
2005-3-24 Chaoqun Wu,Fudan University 75
蛋白质组学的研究方法，主要包括：
待測蛋白质的分离（ Analytical protein separations）
蛋白质的分解（ Protein digestion）
质谱仪的分析和database的搜寻（ MS analysis and database searching）
2005-3-24 Chaoqun Wu,Fudan University 76
2005-3-24 Chaoqun Wu,Fudan University 77
Next Generation Experimental Systems
? Better automation to produce high
throughput experiments
? The use cutting-edge technologies such
as micro-fluid systems,nano-technology
(纳米技术 ) and femto-chemistry (毫微微化学 ) in developing next-generation
experimental devices.
2005-3-24 Chaoqun Wu,Fudan University 78
“Dry” Experiments of Biological Systems
Where do computers come in?
? Systems data mining
? Systems discovery
? Systems simulation
? Systems modeling
2005-3-24 Chaoqun Wu,Fudan University 79
What’s to come?
Development of Precision Models
Simulation requires the integration of multiple
hierarchies(层次 )of models that have different
scales and qualitative properties
Some biological processes take place within
milliseconds while others may take hours or
days,Example,Protein folding vs,Cell Mitosis
Biological processes can involve the interaction
of different types of processes
(i.e,biochemical networks coupled to protein
transport,chromosome dynamics,cell
migration or morphological changes in tissues)
2005-3-24 Chaoqun Wu,Fudan University 80
What’s to come?
? Development of Precision Models
Types of modeling:
?Using differential equations(微分方程) and
stochastic simulation(随机模拟)
?Many cell biological phenomena require
calculation of structural dynamics
?Deformation of elastic bodies(弹性体)
?Spring-mass(分子弹簧) models and other
physical processes
2005-3-24 Chaoqun Wu,Fudan University 81
Consider the system of two masses and two
springs with no external force,Visualize a wall
on the left and to the right a spring,a mass,a
spring and another mass.
2005-3-24 Chaoqun Wu,Fudan University 82
系统组计划（ Systeome）
? 为了促进系统生物学研究，建立一个全面的数据源来描述系统特征十分重要。
系统组 是对所有遗传变异、环境刺激反应下系统特征的组合。
系统特征 包括系统的属性信息，如系统结构及其行为、一些分析结果等。
系统结构 包括基因、代谢网络结构及其相关常数、物理结构及其性质。
系统组不同于简单的级链图，因为它对系统状态而并非静态实体采用了主动的、动态的仿真和剖析。
Computational Biology
2005-3-24 Chaoqun Wu,Fudan University 83
Problems of Knowledge Discovery
? Too much data!
Solution:
use heuristics(启发式演算法 )
use Hidden Markov Model
(HMM,隐马尔可夫模型 )
2005-3-24 Chaoqun Wu,Fudan University 84
Heuristics被译为,启发式演算法,,“助发现法,,
有时也被译为,启发力,,“探试方式,等，与发现的方法论相似的逻辑分析和科学学习功能，
以寻找 可行解 为基础,有效率地求解网路组合最佳化问题（ 最优解 ） 。
有许多计算机化了的启发式方法，可解决达几百、几千的问题。
● 启发力与问题模型,
● 科学发现,
● 类比与隐喻,
● 分析与综合 。
模拟方法
（ simulation）
优化方法
（ optimization）
2005-3-24 Chaoqun Wu,Fudan University 85
隐马尔科夫模型 (Hidden Markov Model,
HMM)是一个二重马尔科夫随机过程，它包括具有状态转移概率的 Markov链和输出观测值的随机过程。其状态是不确定或不可见的，只有通过观测序列的随机过程才能表现出来。按状态的观测概率密度的连续性，隐马尔科夫模型可分为连续隐马尔科夫模型（ Continuous Hidden Markov
Model,CHMM）、半连续隐马尔科夫模型 (Semi-
Continuous Hidden Markov Model,SCHMM)、
离散隐马尔科夫模型 (Discrete Hidden Markov
Model,DHMM).
Nature Biotechnology,2004,22;1315
2005-3-24 Chaoqun Wu,Fudan University 86
Simulation-based Analysis
? Simulation-based analysis tests hypotheses
with in silico experiments,providing
predictions to be tested by in vitro and in
vivo studies,
? faster and more economical,
2005-3-24 Chaoqun Wu,Fudan University 87
Modeling for Gene Expression and Regulation
2005-3-24 Chaoqun Wu,Fudan University 88
Modeling for Intra- and Inter-Cellular Dynamics
2005-3-24 Chaoqun Wu,Fudan University 89
System Behavior Analysis
? Once we understand the structures of the
system,research will focus on dynamic
behaviors of the system.
? How does it adapt to changes in the
environment,such as nutrition,and various
stimuli?
Bifurcation analysis（ 两叉分析 ）
metabolic control analysis(新陈代谢控制分析 )
Sensitivity analysis (灵敏度分析 ).
2005-3-24 Chaoqun Wu,Fudan University 90
? Simulation
系统行为分析方法－模拟
2005-3-24 Chaoqun Wu,Fudan University 91
SBML(Systems Biology Markup Language)
SBML是一个基于XML的描述语言，用于用系统生物学表达计算模型。
(http://sourceforge.net/projects/sbml/)
? a description language for simulations in
systems biology
? meant to support non-spatial biochemical
models and the kinds of operations that are
possible in existing analysis/simulation tools
2005-3-24 Chaoqun Wu,Fudan University 92
Future of SBML
? Arrays（线阵）
? Connections（联结）
? Database Interoperability（互用性）
? Geometry （几何学）
? Submodels（子模型）
? Component Identification（成分识别）
? References （参照）
? Diagrams（图解）
2005-3-24 Chaoqun Wu,Fudan University 93
系统生物学的钥匙 —干涉（ perturbation）
对实验对象的人为影响。
? 系统生物学中的干涉的特点：
系统性。例如人为诱导基因突变，过去大多是随机的；而在进行系统生物学研究时，应该采用的是定向的突变技术。
高通量的干涉能力。如高通量的遗传变异。
随着研究技术的发展，一定还会有许多新的干涉技术应用于系统生物学。
2005-3-24 Chaoqun Wu,Fudan University 94
E-cell
E-CELL is actually a model-building kit,a set
of software tools that allows a user to specify
a cell's genes,proteins,and other molecules,
describe their individual interactions,and then
compute how they work together as a system,
It should ultimately allow investigators to
conduct experiments "in silico," offering a
cheap,fast way to screen drug candidates,
study the effects of mutations or toxins,or
simply probe the networks that govern cell
behavior,(www.e-cell.org)
2005-3-24 Chaoqun Wu,Fudan University 95
Stripped-down cell.
Biochemistry simulated by E-CELL Software.
2005-3-24 Chaoqun Wu,Fudan University 96
Advantages of Computational
Systems Biology
? It is highly relevant in discovering more
complex relationships involving multiple
genes
? This may create new opportunities for drug
discovery
? Better medical therapies for individual
treatments
The Physiome Project,Available,
[online] http://www.physiome.org
(February 2003)
The Physiome Project
(生理组计划 )
?,A worldwide effort to define the physiome
by developing databases and models which
will facilitate the understanding of the
integrative functions of cells,organs and
organisms.”
def,Physiome is the quantitative and integrated
description of the functional behavior of the
physiological state of an individual or species.
2005-3-24 Chaoqun Wu,Fudan University 98
1989年美国国立医学图书馆（NLM）发起可视人计划（ Visible Human Project)；美国国家橡树岭实验室（ORNL）1996年开始虚拟人计划 (Virtual Human
Project Initiative)；1997年华盛顿大学发起了 生理人计划 (The Physiome Project)；由韩国可视人计划于2000年开始；日本从2002年起实施,日本虚拟人计划,。在欧洲，除了汉堡大学著名的Voxel-Man系统之外，还有英国和法国的项目。九十年代，多位中国科学家开始筹划中国数字化虚拟人计划，包括中国数字人模型数据的获取方案与技术、医学图像处理方法学和数字化虚拟人体应用及平台等。最大特点是以医学和计算机科学为中心的跨领域的多学科交叉。
2005-3-24 Chaoqun Wu,Fudan University 99
The Physiome Project
Main Objective:
“… to understand and
describe the human
organism,its
physiology and
pathophysiology
quantitatively,and to
use this understanding
to improve human
health.”
2005-3-24 Chaoqun Wu,Fudan University 100
The Physiome Project
Specific Objectives:
1,To develop and database observations of
physiological phenomenon and interpret
these in terms of mechanism (a
fundamentally reductionist goal).
2,To integrate experimental information into
quantitative descriptions of the functioning
of humans and other organisms (modern
integrative biology glued together via
modeling).
3,To disseminate experimental data and
integrative models for teaching and
research.
2005-3-24 Chaoqun Wu,Fudan University 101
The Physiome Project
Specific Objectives:
4,To foster collaboration amongst
investigators worldwide,in an effort to speed
up the discovery of how biological systems
work.
5,To determine the most effective targets
(molecules or systems) for therapy,either
pharmaceutic or genomic.
6,To provide information for the design tissue-
engineered,biocompatible implants.
2005-3-24 Chaoqun Wu,Fudan University 102
The Physiome Project
Sub-Projects
1,Microcirculation
A common functional
system between organs; It
provides an important
coupling between cells,
tissues,and organs.
Available [online],
http://www.bme.jhu.edu/news/microp
hys
2005-3-24 Chaoqun Wu,Fudan University 103
The Physiome Project
Sub-Projects
2,Musculo-skeletal
system
Continues to extend the
database of
parameterised bone
geometry to individual
muscles,ligaments and
tendons.
Available [online],
http://www.bioeng.auckland.ac.n
z/projects/nerf/skeletal.php
(a) (b)
(a) Anatomically detailed model of
Skeleton.
(b) Rendered finite element mesh for
the bones and a subset of the muscles
2005-3-24 Chaoqun Wu,Fudan University 104
The Physiome Project
Sub-Projects
(a) (b)
Computational model of the skull and torso,(a) The layer of
skeletal muscle is highlighted,(b) The heart and lungs
shown within the torso.
2005-3-24 Chaoqun Wu,Fudan University 105
The Physiome Project
Sub-Projects
3,Cardiome Project
An attempt to provide an
integrated model of the
heart,incorporating
electrical activation,
mechanical contraction,
energy supply and
utilization,cell signaling
and many other
biochemical processes.
Heart model with a textured
epidermal surface
2005-3-24 Chaoqun Wu,Fudan University 106
The Physiome Project
A) Heart Structure
(a) (b) (c)
Fibrous-sheet architecture of the heart,Ribbons are drawn in the plane of
the myocardial sheets (a) on the epicardial surface of the heart,(b) at
midwall,and (c) on the endocardial surface,Note the large fibre angle
changes,These fibre-sheet material axes are needed for computation of
both myocardial activation and ventricular mechanics.
2005-3-24 Chaoqun Wu,Fudan University 107
The Physiome Project
A) Heart Structure
The finite element model of the right and left ventricle of the heart
showing various anatomical structures,Geometric information is carried
at the nodes of the finite element mesh and interpolated with cubic
Hermite basis functions.
2005-3-24 Chaoqun Wu,Fudan University 108
The Physiome Project
B) Ventricular Mechanics
Mechanics of the cardiac cycle,computed by large deformation finite element
analysis,at (a) zero pressure state,(b) end-diastole,(c) mid-systole,(d) end-
systole,Note the apex to base shortening and the twisting about the long axis,
Also note the six generations of discretely modeled coronary vessels embedded
within the myocardial elements which are used to compute coronary flow
throughout the cardiac cycle.
2005-3-24 Chaoqun Wu,Fudan University 109
The Physiome Project
B) Ventricular Mechanics
The collagenous structure of the
extracellular myocardial tissue
matrix,as revealed by confocal
microscopy,The material axes
used for defining mechanical and
electrical constitutive laws in the
continuum modeling of the
myocardium are based on these
microstructurally defined axes.
2005-3-24 Chaoqun Wu,Fudan University 110
The Physiome Project
C) Myocardial Activation
Activation wavefront computed on the finite element model using
finite difference techniques based on grid points which move with the
deforming myocardium,Bidomain current conservation equations
are solved with transmembrane ionic currents,The stimulus in this
case is a point on the left ventricular endocardial surface near the
apex,The activation sequence is heavily influenced by the fibrous-
sheet architecture of the myocardium.
2005-3-24 Chaoqun Wu,Fudan University 111
The Physiome Project
E) Ventricular Fluid Flow
F) Human Torso
model has been developed
which includes the heart,
lungs and the layers of
skeletal muscle,fat and skin,
Current flow from the heart
into the torso is computed in
order to predict the body
surface potentials arising
from activation of the
myocardium.
D) Coronary Perfusion
Computed flow in the
coronary vasculature
2005-3-24 Chaoqun Wu,Fudan University 112
The Physiome Project
Sub-Projects
4,Lungs
Development of models of the
integrated function of various
physical processes operating
in the lung.
5,Bladder and Prostate
An anatomically detailed
model of the bladder and
prostate is developed,
6,Circulation System
A model of the circulation
system is being developed
based on the Visual Human
Project dataset
(http://www.nlm.nih.gov/resear
ch/visible)
2005-3-24 Chaoqun Wu,Fudan University 113
癌的系统生物学癌的系统生物学
2005-3-24 Chaoqun Wu,Fudan University 114
Integrative Cancer Biology
Program (ICBP)
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2005-3-24 Chaoqun Wu,Fudan University 115
ICBP Goals
? To promote the analysis of cancer as a complex
biological system,with an ultimate goal of
developing reliably predictive in silico or
computational models of cancer initiation and
progression and for the development of cancer
interventions.
? Integrate experimental and computational
approaches towards the understanding of
cancer biology.
? Encourage the emergence of integrative cancer
biology as a distinct field,
2005-3-24 Chaoqun Wu,Fudan University 116
Cancer Complexity:,The Black Box”
Cell,parts
list”
Genome
Transcrip-
tome
Proteome
Metabalome
Interactome
Location
Stochiometry
Stability
Modification
Variation
Organelle
Micro-
environment
Macro-
environment
Histology
Physiology
Tissue
Organism
2005-3-24 Chaoqun Wu,Fudan University 117
Challenge,Addressing the
Complexities of Cancer Research
? Complexity of Cancer:
Multiplicity of cancer types
Multiplicity of genes and networks
Micro and macro environmental effects
Dynamic systems
?Initiation
?Progression
?Metastasis
? Complexity of Information
,omic” approaches
?Genome,transcriptome,proteome,interactome
Sophistication of data
2005-3-24 Chaoqun Wu,Fudan University 118
Opportunities
? Large scale data sets are available
Human and mouse genome
? Modeling or Systems Design being applied
to biological problems
? Necessary infrastructure,in place”
? Multi-discipline interactions and
associations more common
?,Systems Biology” is here
2005-3-24 Chaoqun Wu,Fudan University 119
Data/Obser
-vation
Model Generation,Dry”
Model
Refinement
Hypothesis
generation
Experimental,Wet” Validation
2005-3-24 Chaoqun Wu,Fudan University 120
?Practical Application:
Predict function of critical molecules,
pathways,cells and disease states
Identify and validate potential
therapeutic and diagnostic molecules
Complement the development of
animal model systems
Develop predictive in silico
surrogates for therapeutic studies
2005-3-24 Chaoqun Wu,Fudan University 121
Outline of the Integrative Cancer
Biology Program (ICBP)
? Establish multidisciplinary Programs
with the expertise,knowledge,and
infrastructure necessary to undertake a
systems approach to cancer
2005-3-24 Chaoqun Wu,Fudan University 122
?Programs will be structured to enhance
our understanding of cancer biology,
Potential areas of focus include:
Mechanisms of gene expression
Metabolic networks and components
in cell physiology
Cancer-related pathology
Signaling networks and the control of
cellular processes
Cell-cell and cell-matrix interactions
2005-3-24 Chaoqun Wu,Fudan University 123
Cancer robustness
Viewing cancer as a robust
System with potential points of
fragility opens up new strategies
for the development of drugs and
therapies.
2005-3-24 Chaoqun Wu,Fudan University 124
Robustness allows tumours to promote
growth and survival in several ways,
For example,heterogeneity among
tumour cells provides a high level of
redundancy,and hence increased
chances of survival and growth; these
benefits are further enhanced by
feedback controls at the cellular level.
2005-3-24 Chaoqun Wu,Fudan University 125
We need to find a method that will systematically
control the cell’s activities,such as the cell cycle,
growth decisions and apoptosis,
Computer simulations have shown that a cell
cycle that is robust against certain perturbations
can be made extremely fragile when specific
feedback loops are removed or attenuated,
meaning that the cell cycle can be arrested with
minimum perturbation.
2005-3-24 Chaoqun Wu,Fudan University 126
The computational results suggest that
robustness can be controlled by carefully
selecting modulation targets and the
systematic use of multiple drugs.
This ‘systems drug-discovery’ approach
aims to control the cell’s dynamics,
rather than its components,and although
only speculative at present,may turn out
to be critical for the development of new
cancer therapies,
2005-3-24 Chaoqun Wu,Fudan University 127
系统生物学对医学的影响系统生物学对医学的影响
2005-3-24 Chaoqun Wu,Fudan University 128
系统生物学的影响系统生物学必然对医学研究与实践产生巨大的影响 。
首先，个体系统组的快速、精确测量将使我们可以精确的评估、模拟疾病的危险。
其次每个病人精确的系统动力学可以改变药物设计和治疗程序，可以减少副作用，维持疾病治疗的最大效果。
第三，系统水平地理解，特别是仿真、控制、
设计能力为器官克隆提供全新地方法。加速系统水平生物学技术发展的最佳方法。
2005-3-24 Chaoqun Wu,Fudan University 129
Impact of Systems Biology
? Combined with genomic
and other projects,it
may have major
impacts on medical
research and practice.
? In-depth knowledge of
dynamical state of cells
and development of
high-performance
measurements will
drastically change
medical practice.
2005-3-24 Chaoqun Wu,Fudan University 130
The global tools of systems biology are
rapidly moving us toward predictive
medicine,For example,the technique of
single DNA molecule sequencing will move
us toward the rapid and inexpensive
sequencing of entire human genomes over
the next 10-15 years,This would allow us to
search through hundreds,if not thousands
of combinations of genes that might
predispose individuals to a late onset
disease (such as cancer,cardiovascular
disease,diabetes,etc.) and determine a
probabilistic health history for each,
2005-3-24 Chaoqun Wu,Fudan University 131
Linkage of a basic systems biology
research cycle with drug discovery
and treatment cycles
2005-3-24 Chaoqun Wu,Fudan University 132
With sufficient progress in basic systems
biology,this cycle can be applied to drug
discovery and the development of new
treatments,In the future,in silico
experiments and screening of lead
candidates and multiple drug systems,as
well as introduced genetic circuits,will
have a key role in the 'upstream'
processes of the pharmaceutical industry,
significantly reducing costs and
increasing the success of product and
service development.
2005-3-24 Chaoqun Wu,Fudan University 133
Medical systems biology
Medical systems biology has generated
widespread interest because of its bold
conception and exciting potential,but the
field is still in its infancy.
?metabolomics,
?proteomics,
?data handling
?multivariate biostatistics
2005-3-24 Chaoqun Wu,Fudan University 134
Interest in the application of systems biology
to the life sciences has become widespread
over the past five years,although systems
perspectives have been applied to many
sciences,ranging from biology to cosmology,
since at least the beginning of the 20th
century.
Current Opinion in Chemical Biology
2004,8:559–565
2005-3-24 Chaoqun Wu,Fudan University 135
Biochemical Networks
2005-3-24 Chaoqun Wu,Fudan University 136
2005-3-24 Chaoqun Wu,Fudan University 137
Discover the biomarkers of diseases
An important principal for the discovery of
biomarkers for drug discovery,drug
development and disease diagnosis is that
multi-factorial disease involves studying
complex and dynamic biomarker patterns
rather than a single biomarker such as
cholesterol,prostate-specific antigen or glucose.
Different biomarker profiles are found at the
onset of a disease versus the late stage where
symptoms and indirect effects are prominent.
2005-3-24 Chaoqun Wu,Fudan University 138
The development of disease from healthy (homeostasis within black
dotted lines) to sub-optimal health and eventually an overt disease state.
Biomarker patterns (for graphical reasons represented as a single line)
are essential to describe the changes from normality
to dysfunction.
—Adapted from,Metabolic Profiling,2003,Kluwer
Academic Publishers.
2005-3-24 Chaoqun Wu,Fudan University 139
Systemic tools to identify
disease biomarkers
?Metabolome analysis
— NMR and hyphenated MS technology
— Nanoprobe technology
?proteome analysis
— iTRAQ (isobaric tags for relative and
absolute quantification)
— direct tissue profiling and imaging mass
spectrometry
?From data to information and knowledge
2005-3-24 Chaoqun Wu,Fudan University 140
The correlation network of all biomarkers found in a
study on the early onset of atherosclerosis in the
ApoE3 transgenic mouse model.
2005-3-24 Chaoqun Wu,Fudan University 141
Disease Map Created From Disease-
specific Pathways
2005-3-24 Chaoqun Wu,Fudan University 142
Drug Toxicity Prediction
Prediction of Pyrazinamide（吡嗪酰胺） Side Effects
2005-3-24 Chaoqun Wu,Fudan University 143
Tissue-specific Maps for Human Metabolism
The functional models are tissue-specific,i.e,they consist of the
pathways predominantly active in a particular tissue and/or disease
condition,
2005-3-24 Chaoqun Wu,Fudan University 144
Systems Reconstruction Map,Signaling pathways and cascades that regulate
fatty acid oxidation in hepatocytes
2005-3-24 Chaoqun Wu,Fudan University 145
小结
? System biology is a new and emerging field
in biology
? A long ways to go before understanding
biological systems
? Systems biology will be the dominant
paradigm in biology,and many medical
applications as well as scientific discoveries
are expected.
2005-3-24 Chaoqun Wu,Fudan University 146
Although systems biology is in its infancy,
its potential benefits are enormous in
both scientific and practical terms,A
transition is occurring in biology from the
molecular level to the system level that
promises to revolutionize our
understanding of complex biological
regulatory systems and to provide major
new opportunities for practical application
of such knowledge.
2005-3-24 Chaoqun Wu,Fudan University 147
“系统生物学将是21世纪医学和生物学的核心驱动力,
——莱诺伊 ·胡德（ Leroy Hood）
J Proteome Res,2002
2005-3-24 Chaoqun Wu,Fudan University 148
References:
1,Ideker T,Thorsson V,et al,Integrated genomic and proteomic
analyses of a systematically perturbed metabolic network,
Science( 2001)
2,H,Kitano,Systems Biology,A brief overview,Science,295(2002),
1662-1664
3,Eldar A,Dorfman R,Weiss D,Ashe H,Shilo BZ,Barkai N.,
Robustness of the BMP morphogen gradient in Drosophila embryonic
patterning,Nature (2002)
4,Charles Auffray et al,Molecular biology and genetics From functional
genomics to systems biology,concepts and practices,Biologies 326
(2003) 879–892
5,Alan Aderema,Kelly D,Smith,A systems approach to dissecting
immunity and inflammation,Seminars in Immunology 16 (2004) 55–
67
6,EDITORIAL,Scaling cell biology,all systems go! Nature cell biology,
6 (2004) 79
7,Jason A,Papin et al,Reconstruction of cellular signalling networks and
analysis of their properties,Nature reviews,molecular cell biology
6(2005),99-111.
2005-3-24 Chaoqun Wu,Fudan University 149
Thank you
