01. a short introduction to system biology
DESCRIPTION
Brief Introduction and background to biological systems.TRANSCRIPT
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A Short Introduction to Systems Biology
Olaf Wolkenhauer
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Complex Systems
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Cell Functions
Growth Proliferation
ApoptosisDifferentiation
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Systems biology is the science that studies how biological function emerges from the interactions between the
components of living systems
The Systems Biology APPROACH
and how these emergent properties enable/constrain the behavior of these components.
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Systems Biology
Systems biology is an emerging research field, which aims at understanding the dynamic interactions between components of a living system [].
Systems Biology in the European Research Area, p.9, www.erasysbio.net
Modelling is not the final goal, but is a tool to increase understanding of the system, to develop more directed experiments and finally allow predictions.
Systems biology is an approach by which biological questions are addressed through integrating experiments in iterative cycles with computational modelling, simulation and theory.
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Key cellular processes and the network concept
Metabolism Cell signallingGene expression
Pathway, Network
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Examples of signaling pathways
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Complex Systems
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Yes, this is state-of-the-art
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Why Mathematical Modeling?
Biological complexity:
- (time-varying) dynamics,
- nonlinearity,
- self-organization,
- multilevelness.
dxdt = f (x ; t)
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The Systems (Biology) Approach
Observa(ons+Experiments+ Modeling+
Explana(on+
Claim+
Hypothesis+Simula(on+
Predic'ons+
Contextual*Assump/ons**
Narra/ve*
Understanding+
Rebu>al+
Analyses+Concepts+
!!
dRdt
= k0E*(R)+k1S k2R
t+
S+
S+
Rss+
e.g.+Feedback+regula(on,+Bistability+
R+
S+
E*+ E+
R"
R"
freq
uenc
y)
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The Network Approach to Systems Biology
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Biological Complexity: Nonlinear Dynamics
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Signal S
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Multilevelness
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Multilevel Tissue Organization
crypt
107 crypts (14000 / cm2) 2000 cells per crypt
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Multilevelness of Tissue Organization
Stru
ctur
al O
rgan
isat
ionLarge
Intestine
Lumen Crypt
Molecules
Stress
Mutations
Cell Functions
Tissue Function
ReactionsFun
ctio
nal O
rgan
isat
ion
CO
OR
DIN
AT
ION
EM
ER
GE
NC
E
progressive determination
regressive determination
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In a tissue, every cell owes its presence to the behavior of all the remaining cells, and also functions for the
sake of the others.
Maurits C. Escher: Drawing Hands, 1948
Tissue Self-Organization Principle
The whole (tissue) and its parts (cells) reciprocally produce each other; determine the functioning of
each other.
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Emergence
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How do I model and simulate a system?
Statistics and Probability Theory Machine-learning Clustering and Classification
Dynamical Systems Theory ODE-based mechanistic modeling Stochastic modeling & simulation Simulation/Agent-based modeling Logical Representations
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Kinds of Modeling
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Kinds of modeling (contd)
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Mechanistic Modeling
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There is nothing more practical than a good theory!
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Why model?
Explain (very distinct from predict!) Guide data collection Illuminate core dynamics Suggest dynamical analogies Discover new questions Promote scientific habit of mind Bound outcomes to plausible ranges Illuminate core uncertainties Formulate hypotheses Reveal simplicity in complexity
cf. JM Epstein JASSS 11 (4) 2008
Ren Magritte: La Clairvoyance, 1936
Modelling is a means for theorizing: We construct and analyse models in order to formulate hypotheses about general law-like (organising) principles.
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Omnis cellular e cellula
M: Cell division (mitosis)
S: DNA replication/synthesis
G1: Cell growth
G2: Preparation for division
Go: Cell cycle arrest (senescence)
G0
Rudolf Virchow
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CDK-Protein
Cyclin
Cyclin
CDK = Cyclin-abhngige Protein-Kinase
CDK proteins control the cell cylce by binding
CDK2
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3D-Visualisierung fr CDK2_HUMAN
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S: DNA-Doubling
G1: Growth
G2: Synthesis
M: Division
Steps in the cell cycle
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Modelling the Cell Cycle
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Simulating the cell cycle
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Changing the binding properties of Cdc25 und Wee1
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Brahe Kepler Newton
Large scale data gathering
Idea for this slide from J.E.Ferrell, who got it from Stas Shvartsman
First data-driven models (strongly context-dependent)
Generalisation into universal laws
Systems Biology general principles
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Brahes universe
Johannes Kepler (1571-1630)
Tycho Brahe (1546-1601)
Copernicus universe
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Take Home Messages
Cellular Systems: Cell functions: growth, proliferation, differentiation, apopotosis. The network/pathway concept.
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Systems Biology: Studying how biological function emerges from molecular and cellular interactions. An interdisciplinary approach addressing biological and biomedical questions with
the help of mathematical modeling and computer simulations.
Biological Complexity: Nonlinear spatio-temporal interactions of molecules and cells: Feedback. Multilevelness: Self-organisation, emergence.
Mathematical modeling: Statistics, machine learning: Clustering, classification. Dynamical systems theory: Rate equations, logic representations, stochastic
processes. Modeling as a way of thinking.
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The Teaching Crew
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Faiz Khan
Dr Shailendra GuptaDr Anu R Jauhan
Florian Wendland
Dr Dagmar Waltemath
Haus 3, Ulmentrae 69
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