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Crisis responses
and crisis management
What can we learn from biological networks?
www.linkgroup.hu
[email protected]
Prof. Peter Csermely
and the LINK-Group
Semmelweis University, Budapest, Hungary
How can we learn from biological networks?
Networks have general properties
• small-worldness
• hubs (scale-free degree distribution)
• nested hierarchy
• stabilization by weak links
Karinthy, Watts & Strogatz,
1929
1998
Barabasi & Albert, 1999
Csermely, 2004; 2009
Generality of network properties offers
• utilization of billion-years crisis experience
• judgment of importance
• innovation-transfer across different layers of complexity
Crisis-prevention in different systems:
example to break conceptual barriers
Aging is an early warning signal
of a critical transition: death
ecosystem, market, climate
• slower recovery from perturbations
• increased self-similarity of behaviour
• increased variance of fluctuation-patterns
Nature 461:53
Prevention: elements
with less predictable behaviour
• omnivores, top-predators
• market gurus
• stem cells
Farkas et al., Science Signaling 4:pt3
Creative nodes:
life-insurance of complex systems
Creative: few links to
hubs, unexpected re-routing,
flexible, unpredictable
Distributor: hub,
specialized to signal
distribution, predictable
change of roles
Csermely,
Nature 454:5
TiBS 33:569
TiBS 35:539
Problem solver:
specialized to a task,
predictable
The creative person
has an insatiable appetite to discover
new and new network environments
The creative person is a
network-entrepreneur
in a Schumpeterian sense
For this the creative person
needs a continuous refocusing
in the social categories (dimensions)
By this refocusing the creative person
• understands others better
• let others know her/his values better
• connects isolated people
• and exponentially enriches her/himself.
Moreover: this is a self-amplifying circle.
A creative person always lets others
go to the centre – to remain free
Detoxifying
protein
Creative amino acids
• centre of residue-network
• in structural holes
Creative proteins
• stress proteins
• signaling switches
drug-binding
Csermely,
Nature 454:5
TiBS 33:569
TiBS 35:539
detoxification
Creative cells
• stem cells
• our brain
Creative persons
• firms
• societies
mobile
Network changes in cellular crisis
a short intro to the messy life of cells
networks:
• STRING 7
(5329/190018)
• BioGRID
(5329/91749)
• Ekman
(2444/6271)
resting
protein weight
mRNA expression
multiplication
average
resting link-weight
weights:
• equal units
• proteins
continuous
weights
discrete
weights
unique
stress
average
stress
stressed
protein weight
multiplication
average
stressed link-weight
13 stress conditions, 65 experiments
(Gasch et al, Mol. Biol. Cell 11:4241)
6 stress conditions, 32 experiments
(Nature 441:840)
(Causton et al, Mol. Biol. Cell 12:323)
• mRNA-s
(Cell 95:717)
analysis of overlapping network modules:
ModuLand method
Mihalik & Csermely
PLoS Comput. Biol. 7:e1002187
The ModuLand method family detects
overlapping network communities
community
landscape
community
centrality:
a measure
of the influence
of all other nodes
influence
zones of all
nodes/links
communities
as landscape hills
network
hierachy
available as
a Cytoscape
plug-in
Kovacs et al, PLoS ONE 5:e12528
www.linkgroup.hu/modules.php
network of network scientists; Newman PRE 74:036104
shows the
centre of
modules too!
Community centrality reflects
node-(link)-importance in crisis-survival
protein
synthesis
energy
distribution
community
centrality
protein
degradation
energy
distribution
survival
processes
Mihalik & Csermely
PLoS Comput. Biol. 7:e1002187
• yeast protein-protein interaction
network: 5223 nodes, 44314 links
• stress: 15 min 37°C heat shock
• link-weight changes: mRNA
expression level changes
Changes of yeast interactome in crisis:
a model of systems level adaptation
• BioGrid yeast interactome:
5223 nodes, 44314 links
• stress: 15 min 37°C heat shock
+ Gasch et al. MBC 11:4241
• link-weight changes: mRNA
expression level changes
Stressed yeast cell:
• nodes belong to less modules
• modules have less intensive contacts
smaller overlaps between modules,
more condensed modules
Mihalik & Csermely
PLoS Comput. Biol. 7:e1002187
Crisis survival: of
creative
elements
Consequences
network
crisis
cell
death
creative
elements*
stress
network
desintegration
increased network flexibility
• spared links
• noise and damage localization
• modular independence: larger
response-space and better conflict
management
*Schumpeterian
destruction
Szalay et al, FEBScreative
Lett. 581:3675;
Palotai et al. IUBMB Life 60:10
Mihalik and Csermely PLoS Comput. Biol. 7:e1002187
Bacteria living in a variable environment
have more separate network modules
more
separate
modules
metabolic networks
of 117 bacteria
Parter, Kashtan & Alon
BMC Evol. Biol. 7:169
larger environmental variability
Bacteria living in a variable environment
have more separate network modules
community
landscapes
(red/yellow: tops)
Szalay-Bekő et al.
arxiv.org/1111.3033
Multimodular
metabolic network
of the free living E. coli
Single major core
of the metabolic network
of the symbiont Buchnera
Telecommunication network modules
become more cohesive in social crisis
cohesive
modules
phone
call
intensity
more than 10 million people
Bagrow, Wang & Barabasi
PLoS ONE 6:e17680
time
diffuse
modules
in crisis we call our mother
and not a distant friend…
Vassy, Wang, Barabasi & Csermely
in preparation
Generality: emergence of two phenotypes
• ecosystems: food limitation see otters, patchiness in drought
• brain: modular reorganization in learning
• social networks: broker stress, Schumpeterian creative destruction
Haldane & May: US Volcker Rule separates bank system modules
Topological phase transitions reflect the overlap-decrease at one level higher
network diameter
degrees of freedom
stress
assembly >
disassembly
Physica A 334:583
Csermely:
Weak Links
disassembly >
assembly
Many resources: large phenotype
few resources: small phenotype
Bateson et al.
Nature 430:419
Janos Kornai: Thoughts about capitalism
(in Hungarian, in preparation in English)
Metabolism:
large: rapid, overspending
small: slow, ‘thrifty’
‘overeating’ society: diabetes
Society:
large: capitalism
small: socialism
surplus and shortage economies
5% of phenotypes
can be reached
all phenotypes
can be reached
Low adaptation potential
of ‘small’ and large’
phenotypes
Draghi, Parsons,
Wagner & Plotkin,
Nature 463:353
stress, crisis
‘small’
+
‘balanced’
+
+
‘large’
+
possibility of adaptation
effect of adaptation
Take-home messages
1.
Biological networks offer the experience of
billion years in crisis-survival
2.
Community rearrangements may be a general
mechanism of system level adaptation
‘small’
+
‘balanced’
+
+
‘large’
+
stress, crisis
A network component
of evolvability?
possibility of adaptation
effect of adaptation
Acknowledgments
Robin
Palotai
Stress Ágoston
Mihalik
potential new
collaborators
Springer, 2009
Aging
Zsolt Vassy
Shijun Wang
ModuLand
Games
István A. Kovács
Gábor I. Simkó
Máté Szalay-Bekő
www.linkgroup.hu
[email protected]
Peter Csermely:
Weak Links
Marcell
Stippinger
András
London
available free:
Google-books
Influence zones
using the NodeLand method
startingzones
node
influence
community-44: 1127 schoolchildren, 5096 friendships; Add-Health