In silico discovery of principles in multiscale Systems Biology
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Transcript of In silico discovery of principles in multiscale Systems Biology
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale Systems Biology
Manchester Centre for Integrative Systems Biology
Doctoral Training Centre for Systems Biology from Molecules to Life
Hans V. Westerhoff and friends
Netherlands Institute for Systems Biology, Amsterdam
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale Systems Biology• The paradigm of the replica model• Discovery through replica modelling of reality:
– Time invariance and distributed control– Robust biology– Irreducible complexity– Drug target discovery– Hierarchies in scales: gene expression and time
• We have a problem• Multiscale ITFoM as a solution• Out of my comfort zone
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
• X=X(time, X0, e1, e2,.., en, enzyme parameters, [S])
The enzymes are like elementary particles for biology!
∙ chemical ─ reaction
Constituent equation:
𝑑𝑥𝑖=∑𝑗=1
𝑛
𝑁 𝑖𝑗 ∙𝑒 𝑗 ∙𝑣 𝑗(𝑥 ,𝑝)∙𝑑𝑡
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
The paradigm of the replica model• Model reality using multiscaling that does
not loose essential complexity• Genes/enzymes as elementary particles• Describe them with rate equations (v(X))• Describe metabolites with node equations
(dX/dt) = N.v)• Integrate• Repeat at higher scales in terms of
modules, keeping relationships with fine-grained levels
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Silicon / virtual biochemical organisms
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale Systems Biology• The paradigm of the replica model• Discovery through replica modelling of reality:
– Time invariance and distributed control– Irreducible complexity– Robust biology– Drug target discovery– Hierarchies in scales: gene expression and time
• We have a problem• Multiscale ITFoM as a solution• Out of my comfort zone
![Page 8: In silico discovery of principles in multiscale Systems Biology](https://reader035.fdocuments.us/reader035/viewer/2022062500/5681594d550346895dc68b4b/html5/thumbnails/8.jpg)
Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
If the model is a replica, it is as complex as the real system, hence offers no advantages for understanding
Replica models can be used for computational investigations of reality
They greatly facilitate discovery ofPrinciples that govern reality
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Hendrik Antoon Lorentz
• 1900: Maxwell equations are• invariant under the Lorentz
transformation
• Lorentz contraction
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology∙ chemical ─ reaction
Constituent equation:
𝑑𝑥𝑖=∑𝑗=1
𝑛
𝑁 𝑖𝑗 ∙𝑒 𝑗 ∙𝑣 𝑗(𝑥 ,𝑝)∙𝑑𝑡
Our transformation
𝑡′≡𝑡 /𝜆𝑒𝑖′≡ 𝜆 ∙𝑒𝑖
Seconds instead of minutes as time unit
All processes 60 times faster
There should be no effect
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
logarithm of time
lnJ
SS
n
j
xt
xe tCtCj
1
0)()(
Westerhoff (2008) J Theor Biol 252, 555 - 567
Law/principle of Systems Biology
Steady state or maximum:
C=Control of concentration by enzyme
𝐶1𝑥+𝐶2
𝑥+𝐶3𝑥+….+𝐶𝑛
𝑥=0lo
g of
con
cent
rati
on
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Silicon / virtual biochemical organisms\validated in silico
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
The principle we discovered
E EP
F FP
G GP
For the maximum level of EP the phosphatases are equally important as the kinases
Transcription of ‘growth’genes
Growth factor
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale Systems Biology• The paradigm of the replica model• Discovery through replica modelling of reality:
– Time invariance and distributed control– Irreducible complexity– Robust biology– Drug target discovery– Hierarchies in scales: gene expression and time
• We have a problem• Multiscale ITFoM as a solution• Out of my comfort zone
![Page 16: In silico discovery of principles in multiscale Systems Biology](https://reader035.fdocuments.us/reader035/viewer/2022062500/5681594d550346895dc68b4b/html5/thumbnails/16.jpg)
Simplicity: Control essentially in one component(the key gene/enzyme catalyzing the first irreversible step)
Irreducible complexity:Control is distributed And not even uniformly
Which is it?
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
MAP kinase signaling: which are the fragile steps?
0.03
0.06
-0.43
-0.18 0.21
0.00
0.43 0.01
-1.47
-1.12
-0.44
0.44
1.47
Hornberg et al. Oncogene
Healthy tissueCalculations based on
Schöberl model
At JWS/SiC
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale Systems Biology• The paradigm of the replica model• Discovery through replica modelling of reality:
– Time invariance and distributed control– Irreducible complexity– Robust biology– Drug target discovery– Hierarchies in scales: gene expression and time
• We have a problem• Multiscale ITFoM as a solution• Out of my comfort zone
![Page 19: In silico discovery of principles in multiscale Systems Biology](https://reader035.fdocuments.us/reader035/viewer/2022062500/5681594d550346895dc68b4b/html5/thumbnails/19.jpg)
To discover & certify network principles of
robustness (and disease)
We need a definition of robustness
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Definition of robustness
The percentage by which one can interfere
with a molecular process without reducing system
function by more than 1 %
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Principle 1
Networking enhances robustness
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Enzyme activity
Func
tion
Robustness is 1 for processes in isolation
1%1
%1
ffunctionindecrease
activityenzymeindecreasefei
Process in isolation
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robustness of isolated processes =1
Is the robustness in networks larger?
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Silicon / virtual biochemical organisms
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Robustness of vital flux of Trypanosomes vis-à-vis perturbation of various glycolytic steps
step Robustness
Glctr 1.1
GAPdh 42
HK 42
PGI 1546
PFK 234
ALD 38
TPI 482
GDH 66
GPO -251
PGK 61
PK 691
ATPase 2744
GlyK 389
Answer:
Yes, most robustnesses in networks in living organisms are large; average is 468 here
Question:
Is robustness higher (than 1) in networks of living cells?
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Principle 2???
Trade-off???:
Does making the system more robust vis-à-vis one perturbation make it equally less robust for a
different perturbation???
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Precise trade-off for robustness?
step Robustness
Robustness doubled glucose
transporter
Glctr 1.1 88
GAPdh 42 4
HK 42 20
PGI 1546 412
PFK 234 56.
ALD 38 3
TPI 482 64
GDH 66 6
GPO -251 -15
PGK 61 7
PK 691 73
ATPase 2744 313
GlyK 389 26
Sum (average) 6085 (468) 1055(81)
No, robustness is not conserved
No precise trade-off for robustness
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Principle 2???
Trade-off???:
making the system more robust vis-à-vis one perturbation makes it less
robust for a different perturbation???
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No principle then?No trade-off?
Yes, there is one!
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Sum over all inverse robustnesses = 1= conserved
step 1/robustness
1/robustness (doubled glc transporter)
Glctr 0.887 0.011
GAPdh 0.024 0.249
HK 0.024 0.051
PGI 0.001 0.002
PFK 0.004 0.018
ALD 0.026 0.354
TPI 0.002 0.016
GDH 0.015 0.166
GPO -0.004 -0.068
PGK 0.016 0.144
PK 0.001 0.014
ATPase 0 0.003
GlyK 0.003 0.039
Sum 0.999 0.999
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale Systems Biology• The paradigm of the replica model• Discovery through replica modelling of reality:
– Time invariance and distributed control– Irreducible complexity– Robust biology– Drug target discovery– Hierarchies in scales: gene expression and time
• We have a problem• Multiscale ITFoM as a solution• Out of my comfort zone
![Page 32: In silico discovery of principles in multiscale Systems Biology](https://reader035.fdocuments.us/reader035/viewer/2022062500/5681594d550346895dc68b4b/html5/thumbnails/32.jpg)
Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Trypanosomiasis
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Silicon / virtual biochemical organisms
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
The most fragile step is…..
stepFragility=C=1/
robustness
1/robustness (doubled glc transporter)
Glucose transport 0.887 0.011
GAPdh 0.024 0.249
HK 0.024 0.051
PGI 0.001 0.002
PFK 0.004 0.018
ALD 0.026 0.354
TPI 0.002 0.016
GDH 0.015 0.166
GPO -0.004 -0.068
PGK 0.016 0.144
PK 0.001 0.014
ATPase 0 0.003
GlyK 0.003 0.039
Sum 0.999 0.999
?
?
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Differential network-based drug design
Target where the difference between
parasite and host is the largest
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Trypanosome in the host
T. brucei…..
us et al.
Holzhütter et al.
Red blood cell
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
TRYPANOSOMEERYTHROCYTE
GOODTARGET
Differential fragility analysis TRYP and ERY
Fragility of ATP synthesis flux
(Bakker, Holzhütter, Snoep, Westerhoff)
0.680.00
0.01
0.03
0.001
0.07
0.060.01
0.05
0.001
0.005
0.02
0.00
0.02
-0.01
0.00
0.00
0.03
0.940.00 0
0.00 FAIRTARGET
BADTARGET
BADTARGET
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Haanstra
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Fragilities of PGK mRNA and protein versus perturbations in ..
Fragility of for →:
Targeting the networks: multiple targets at the same time in hierarchical networks!
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The multiscale problemand transcription
activation
• Time: • How to bridge the various time scales?
Molecular <1 s versus Cellular >1 h
• The multidimension problem:• How to enable regulation by 20
information flows rather than by 1?
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A
A B
A B
C
A B
CD
AB
CD
B
C
D
C
B
A
D
D
D
C
The clock model for mammalian transcription activation
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Slow macroscopic dynamics caused by, rapid, molecular processes!
Metivier, R. et al. Estrogen receptor-alpha directs ordered, cyclical, and combinatorial recruitment of cofactors on a natural target promoter. Cell 115, 751-763 (2003).
Karpova, T. S. et al. Concurrent fast and slow cycling of a transcriptional activator at an endogenous promoter. Science (New York, N.Y 319, 466-469 (2008).
Saramaki, A. et al. Cyclical chromatin looping and transcription factor association on the regulatory regions of the p21 (CDKN1A) gene in response to 1alpha,25-dihydroxyvitamin D3. J Biol Chem 284, 8073-8082, doi:M808090200 [pii]
Note! Transcription synchrony in population of cells!
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale Systems Biology• The paradigm of the replica model• Discovery through replica modelling of reality:
– Time invariance and distributed control– Irreducible complexity– Robust biology– Drug target discovery– Hierarchies in scales: gene expression and time
• We have a problem• Multiscale ITFoM as a solution• Out of my comfort zone
![Page 45: In silico discovery of principles in multiscale Systems Biology](https://reader035.fdocuments.us/reader035/viewer/2022062500/5681594d550346895dc68b4b/html5/thumbnails/45.jpg)
Why?Well, we have ‘a’ problem
• Definitive cures are lacking for most
diseases
• The health care budget will cripple the
economy
• The life sciences are tremendously
successful but ….. not in empowering
medicine
• ………….
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Increased spending has not improved cancer mortality
1970 1975 1980 1985 1990 1995 2000 2005 20100
5
10
15
20
25
30
35
40
45
50
cumulative NCI funding (G$)
cancer mortality (/1000)
+2000 %
-10 %
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Global prevalence of diabetes and impaired glucose tolerance (IGT) in 2010 and 2030
Boyle, 2011
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
genomicstranscriptomics
proteomics
metabolomics
structural biology
biophysics biologybiochemistry
physiology
Yet…We can measure almost everything now
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
>1 trillion €/year spent on biomedical research: Tower of Babel?
Brueghel
health
disease
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale Systems Biology• The paradigm of the replica model• Discovery through replica modelling of reality:
– Time invariance and distributed control– Irreducible complexity– Robust biology– Drug target discovery– Hierarchies in scales: gene expression and time
• We have a problem• Multiscale ITFoM as a solution• Out of my comfort zone
![Page 51: In silico discovery of principles in multiscale Systems Biology](https://reader035.fdocuments.us/reader035/viewer/2022062500/5681594d550346895dc68b4b/html5/thumbnails/51.jpg)
Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
IT Future of Medicinea FET Flagship project
A CERN-like project:1.3 G€
Idea 1: Use computable replica model to organize and integrate the data
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
genomicstranscriptomics
proteomics
metabolomics
structural biology
biophysics biologybiochemistry
physiology
project all information into a computer replica
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Integration of all information through the ITFoM flagship into computable human
models!
Brueghel
An ICT model of the human
health
disease
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Idea 2: to deal with otherwise impossible complexity
The human body is a computer using simple
principles
We should borrow its computation strategy
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The virtual patient – a “person simulator”
New ICT for medicine
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The virtual patient – a “person simulator”
And 7 billion of these…..:one man one vote := therapy
New ICT for medicine
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Silicon / virtual biochemical human
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Melanoma
Hepato-cyte
Red blood cell
Virtual heart
Integrating
Models
Models from Molecular Systems Biology
Physiological models from VPH
Statistical models
Epidemiological models
Clinical models
Patients’ concepts
…….
T. bruc
ei
Microbiome
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Integration WP#6
Medical user and expertise
Instrumentation and assays
Medical WP1Analytical
WP2
Hard- & SoftwareWP#3
Data PipelinesWP#4
ComputationalWP#5
Programing industry & academia
Databases and repositories
Hardware
/Software industry
CoordinationWP#7
Final WP numbering and organization: blue is ICT, red is medical and green is analytical expertise. The end product
is ICT models of individual humans for individualized medicine.
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4.6(I) Map
s
4.8(I) Mo
dels
4.7(I) Data
4.9(I) Too
ls
ICT-integration challengesmolecules – tissues - patients
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4.5(I) Maps
4.7(I) Models
4.6(I) Data
4.8(I) Tools
ICT-modelling Strategies
4.1 (S) Watchmaker’s models (SiC)
4.2 (S) Engineer’s models
4.3 (S) Mechanic’s models (VPH)
4.4 (S) Learner’s models
4.5 (S) Combinations
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale Systems Biology• The paradigm of the replica model• Discovery through replica modelling of reality:
– Time invariance and distributed control– Irreducible complexity– Robust biology– Drug target discovery– Hierarchies in scales: gene expression and time
• We have a problem• Multiscale ITFoM as a solution• Out of my comfort zone
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• How to link down (enzyme MD)
Antreas Kalli
Use essential dynamicsReduce to essential statesCompute affinitiesValidate experimentallyInsert into enzyme kinetics
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• Pathway complexity
Eytan Rubin, Mattias Reuss, and us and others
Use exometabolomics, FBA and objective functions to find where most of the flux is
Project SNPs into those pathways
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• Parameter finding intracellular networksMartine SmitsBob van de Water
Rich data setsMultiple RNAi7 billion humans
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• Cell heterogeneity
Single cell analyses
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• Towards tissue• Katarina Wolf• David Basanta• Chris Adami• Andreas Deutsch
Transparent black box approachFocus on dominant behavior firstAgent based modelsEvolutionary games, but extended to continuous variablesAnd connect parameters between levels!
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• True tissue dynamics and anatomy• Bernard Corfe
Transparent black box approachFocus on dominant behavior firstAgent based modelsEvolutionary games, but extended to continuous variablesAnd connect parameters between levels!
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• Lifestyle and ethics• Angela Brand, Bernard Corfe
Insert substrates= food into pathwaysInsert movement as muscle activityInsert brain through measured hormone levels
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Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale Systems Biology• The paradigm of the replica model• Discovery through replica modelling of reality:
– Time invariance and distributed control– Irreducible complexity– Robust biology– Drug target discovery– Hierarchies in scales: gene expression and time
• We have a problem• Multiscale ITFoM as a solution• Out of my comfort zone
![Page 71: In silico discovery of principles in multiscale Systems Biology](https://reader035.fdocuments.us/reader035/viewer/2022062500/5681594d550346895dc68b4b/html5/thumbnails/71.jpg)
Westerhoff et al., Leiden 20121116 Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale Systems Biology
Manchester Centre for Integrative Systems Biology
Doctoral Training Centre for Systems Biology from Molecules to Life
friends
Netherlands Institute for Systems Biology, Amsterdam