http://www.cds.caltech.edu/~doyle/shortcourse.htm

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http//www.cds.caltech.edu/doyle/shortcourse.htm
Systems Biology Shortcourse May 21-24 Winnett
Lounge, Caltech Speakers Adam Arkin (UC
Berkeley), Frank Doyle (UCSB), Drew Endy (MIT),
Dan Gillespie (Caltech), Michael Savageau (UC
Davis) Organized by John Doyle (Caltech). There
is no registration or fees. Note Friday 4pm talk
by Adam Arkin in Beckman Institute Auditorium.
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Collaborators and contributors(partial list)

• Theory Parrilo, Carlson, Paganini,
  Papachristodoulo, Prajna, Goncalves, Fazel, Lall,
  DAndrea, Jadbabaie, many current and former
  students,
• Web/Internet Low, Willinger, Vinnicombe, Kelly,
  Zhu,Yu, Wang, Chandy, Effros,
• Biology Csete,Yi, Tanaka, Arkin, Savageau,
  Simon, AfCS, Kurata, Khammash, El-Samad, Gross,
  Bolouri, Kitano, Hucka, Sauro, Finney,
• Turbulence Bamieh, Dahleh, Bobba, Gharib,
  Marsden,
• Physics Mabuchi, Doherty, Barahona, Reynolds,
  Asimakapoulos,
• Engineering CAD Ortiz, Murray, Schroder,
  Burdick,
• Disturbance ecology Moritz, Carlson, Robert,
• Finance Martinez, Primbs, Yamada, Giannelli,

Caltech faculty
Other Caltech
Other
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Whole cell metabolism
Core metabolism
Autocatalytic and regulatory feedback
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Autocatalysis
Enzyme
Metabolite
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Autocatalysis
Enzyme
Metabolite
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Enzyme
Metabolite
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Stoichiometry or mass and energy balance
Internal
Products
Nutrients
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Core metabolism
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Whole cell metabolism
Core metabolism
Autocatalytic and regulatory feedback
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Polymerization and assembly
Nested bowties
Core metabolism
transport
Autocatalytic and regulatory feedback
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Nested bowties
Our first universal architecture
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The core metabolism bowtie
Nutrients
Products
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Catabolism
Carriers and Precursor Metabolites
Cartoon metabolism
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Catabolism
Nucleotides
Carriers and Precursor Metabolites
Sugars
Amino Acids
Fatty acids
Energy and reducing
The metabolism bowtie protocol
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Uncertain
Uncertain
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Uncertain
Uncertain
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Almost everything complex is made this way Cars,
planes, buildings, power, fuel, laptops,
This cartoon is pure protocol.
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Manufacturing and metabolism
Collect and import raw materials
Common currencies and building blocks
Complex assembly
Collect and import raw materials
Common currencies and building blocks
Complex assembly
Polymerization and assembly
Taxis and transport
Core metabolism
Autocatalytic and regulatory feedback
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Electric power
Variety of producers
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Electric power
Variety of consumers
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Variety of consumers
Variety of producers
Energy carriers

• 110 V, 60 Hz AC
• (230V, 50 Hz AC)
• Gasoline
• ATP, glucose, etc
• Proton motive force

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Raw materials
Complex assembly
Raw materials
Complex assembly
Building blocks
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Collect and import raw materials
Common currencies and building blocks
Complex assembly
Steel manufacturing
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assembly
metabolism
transport
Core special purpose machines controlled by
allostery
Variety of consumers
Variety of producers
Energy carriers
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assembly
metabolism
transport
Edges general purpose machines controlled by
regulated recruitment
Variety of consumers
Variety of producers
Energy carriers
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assembly
metabolism
transport
Robust and evolvable
Variety of consumers
Variety of producers
Energy carriers
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assembly
metabolism
transport
Fragile and hard to change
Variety of consumers
Variety of producers
Energy carriers
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assembly
metabolism
transport

• Preserved by selection on three levels
• Fragile to change (short term)
• Facilitates robustness elsewhere (short term)
• Facilitates evolution (long term)

Variety of consumers
Variety of producers
Energy carriers
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Modules and protocols

• Much confusion surrounds these terms
• Biologists already understand the important
  distinction
• Most of basic sciences doesnt

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Modules and protocols in experiments

• Modules components of experiments
• Protocols rules or recipes by which the modules
  interact
• This generalizes to most important situations
• Important distinction in experiments
• Even more important in understanding the
  complexity of biological networks

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Modules and protocols example

• Suppose some specific experimental protocol has a
  step that requires the use of a PCR machine
  module.
• The PCR machine in turn implements a complex
  protocol with its own modules.
• Thus protocols and modules are hierarchically
  nested.
• A nested collection of protocols/modules is
  called an architecture or protocol suite.

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Modules and protocols example

• Consider this laptop/projector combination.
• The modules include software, hardware, and
  connectors.
• The protocols are the rules by which these
  modules must interact.
• Hardware modules change between talks
• Within talks slides change, not hardware
• Robust and evolvable yet fragile

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Modules and protocols example

• Consider this laptop/projector combination.
• The modules include software, hardware, and
  connectors.
• The protocols are the rules by which these
  modules must interact.
• Hardware modules change between talks
• Within talks slides change, not hardware
• Robust and evolvable yet fragile

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The LEGO connector protocol
Robust Mesoscale
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Various functionality
Digital
Analog substrate
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Applications
Software Hardware
Modern Computing
Operating System
Hardware
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Applications
Software Hardware
Modern Computing
Operating System
Hardware
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Modules and protocols

• Protocols and modules are complementary (dual)
  notions
• Primitive technologies modules are more
  important than protocols
• Advanced technologies protocols are at least as
  important
• Even bacteria are advanced technology

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Reductionism and protocols

• Reductionism modules are more important than
  protocols
• Usually Huh? Whats a protocol?
• Systems approach Protocols are as important as
  modules

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Necessity or frozen accident?

• Laws are absolute necessity.
• Conjecture Protocols in biology are largely
  necessary. (More so than in engineering!)
• Modules??? Appear to be more of a mix of
  necessity and accident.

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Necessity or frozen accident?

• Conservation laws are necessary.
• Bowtie protocols are essentially necessary if
  robustness and efficiency are required.
• Conjecture It is necessary that there is an
  energy carrier, it may not be necessary that it
  be ATP.

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Conjectures on laws and protocols

• The important laws governing biological
  complexity have yet to be fully articulated
• Biology has highly organized dynamics using
  protocol suites
• Both are true for advanced technologies

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Nested bowtie and hourglass
Polymerization and assembly
Core metabolism
Conservation of energy and moiety is a law.
Taxis and transport
Enzymes are modules.
Bowtie architectures is a protocol.
Autocatalytic and regulatory feedback
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essential 230   nonessential 2373  
unknown 1804   total 4407
http//www.shigen.nig.ac.jp/ecoli/pec
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assembly
metabolism
transport
Autocatalytic feedback
Regulatory feedback
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assembly
metabolism
transport
Knockouts often lethal
Autocatalytic feedback
Knockouts often lose robustness, not minimal
functionality
Regulatory feedback
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Steering
Brakes
Mirrors
Wipers
Anti-skid
Cruise control
GPS
Radio
Traction control
Headlights
Shifting
Electronic ignition
Temperature control
Seats
Electronic fuel injection
Seatbelts
Fenders
Bumpers
Airbags
Suspension (control)
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Knockouts often lethal
Steering
Brakes
Mirrors
Wipers
Anti-skid
Knockouts often lose robustness, not minimal
functionality
Cruise control
GPS
Radio
Traction control
Headlights
Shifting
Electronic ignition
Temperature control
Seats
Electronic fuel injection
Seatbelts
Fenders
Bumpers
Airbags
Suspension (control)
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assembly
metabolism
transport
Supplies Materials Energy
Autocatalytic feedback
Robustness ? Complexity
Regulatory feedback
Supplies Robustness
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assembly
metabolism
transport
Autocatalytic feedback
If feedback regulation is the dominant protocol,
what are the laws constraining whats possible?
Regulatory feedback
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assembly
metabolism
transport

• A historical aside
• These systems are not at the edge-of-chaos,
  self-organized critical, scale-free, at an
  order-disorder transition, etc
• Not only are they as opposite from this as can
  possibly be (an observational fact)
• But also, it is provably impossible for robust
  systems to have it otherwise (a theoretical
  assertion)
• The facts are easily checked, what is the
  theoretical foundation?

Autocatalytic feedback
Regulatory feedback
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assembly
metabolism
transport
Supplies Materials Energy
Autocatalytic feedback
What are the laws of robustness?
Regulatory feedback
Supplies Robustness
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Whole cell metabolism
Core metabolism
Transport
Autocatalytic and regulatory feedback
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Autocatalysis
Enzyme
Metabolite
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Autocatalysis
Enzyme
Metabolite
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Enzyme
Metabolite
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Yi, Ingalls, Goncalves, Sauro
Product inhibition
perturbation
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1.05
Step increase in demand for ATP.
ATP
1
0.95
0.9
0.85
0.8
0
5
10
15
20
Time (minutes)
h 0 1 2 3
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h 3
h 2
h 1
h 0
Time
0
5
10
15
20
Higher feedback gain
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1.05
ATP
1
h 3
0.95
Time response
0.9
0.85
h 0
0.8
0
5
10
15
20
Time (minutes)
0.8
h 3
0.6
Spectrum
0.4
0.2
h 0
Log(Sn/S0)
0
-0.2
-0.4
-0.6
-0.8
0
2
4
6
8
10
Frequency
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Yet fragile
0.8
h 3
0.6
Robust
0.4
0.2
h 0
Log(Sn/S0)
0
-0.2
-0.4
-0.6
-0.8
0
2
4
6
8
10
Frequency
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Yet fragile
0.8
0.6
Robust
0.4
0.2
h 0
Log(Sn/S0)
0
-0.2
-0.4
-0.6
-0.8
0
2
4
6
8
10
Frequency
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Theorem
Transients, Oscillations
0.8
h 3
0.6
Tighter steady-state regulation
0.4
h 2
0.2
h 0
Log(Sn/S0)
0
h 1
-0.2
-0.4
-0.6
-0.8
0
2
4
6
8
10
Frequency
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This tradeoff is a law.
Transients, Oscillations
logS
?
Biological complexity is dominated by the
evolution of mechanisms to more finely tune this
robustness/fragility tradeoff.
Tighter regulation
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This tradeoff is a law.
Product inhibition is a protocol.
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This tradeoff is a law.
PFK and ATP are modules.
Product inhibition is a protocol.
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logS
?
Conservation of fragility
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Diseases of complexity
Fragile

• Parasites
• Cancer
• Epidemics
• Auto-immune disease

Complex development Regeneration/renewal Complex
societies Immune response
Uncertainty
Robust
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logS
?
We have a proof of this.
X0
X1
Xi
Xn


Error
Xn1
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This is a cartoon. We have no proof of this.
Yet.
Fragile

• Parasites
• Cancer
• Epidemics
• Auto-immune disease

Complex development Regeneration/renewal Complex
societies Immune response
Uncertainty
Robust
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Why should any biologists care about this? How
does it effect what can be done to understand
complex biological networks?
Fragile
Immune response Development Regeneration renewal S
ocieties
Parasites Cancer Epidemics Auto-immune disease
Robust
Uncertainty
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Modeling robust yet fragile systems
May need great detail here
Fragile
And much less detail here.
Uncertainty
Robust
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Fragile
Robust (fragile) to perturbations in components
and environment ? Robust (fragile) to errors and
simplifications in modeling
More detail.
Required model complexity
Less detail.
Uncertainty
Robust
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h 3
h 2
h 1
h 0
Time
0
5
10
15
20
0.8
h 3
0.6
0.4
h 2
0.2
h 0
Log(Sn/S0)
0
h 1
-0.2
-0.4
-0.6
-0.8
0
2
4
6
8
10
Frequency
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Autocatalysis
Regulation
Enzyme
Metabolite
Energy and materials
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assembly
metabolism
transport
Autocatalytic feedback
Even though autocatalytic feedback contributes
relatively modestly to complexity, it has a huge
indirect impact on regulatory complexity.
Regulatory feedback
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assembly
metabolism
transport
Autocatalytic feedback

• Autocatalysis is everywhere in human and natural
  systems as well as biology
• Make energy, materials, and machines to make
  energy, materials, and machines to make
• Consumers are investors are labor

Regulatory feedback
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Regulatory feedback only
h 3
h 2
h 1
h 0
Time
0
5
10
15
20
0.8
h 3
0.6
0.4
h 2
0.2
h 0
Log(Sn/S0)
0
h 1
-0.2
-0.4
-0.6
-0.8
0
2
4
6
8
10
Frequency
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Add autocatalytic feedback
more
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Add autocatalytic feedback
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Add more regulator feedback
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More instability aggravates
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Control demo
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assembly
metabolism
transport
Conservation of energy, moiety, and fragility are
laws.
Autocatalytic feedback
Enzymes are modules.
Bowtie architectures with product inhibition is
a protocol suite.
Regulatory feedback
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Nested bowtie and hourglass
Polymerization and assembly
Core metabolism
Conservation of energy and moiety is a law.
Taxis and transport
Enzymes are modules.
Bowtie architectures is a protocol.
Autocatalytic and regulatory feedback
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Key themes

1. Multiscale and large-scale stochastic simulation
   is an essential technology for systems biology.
2. Simulation alone is not scalable to larger
   network problems because complex, uncertain
   systems need an exponentially large number of
   simulations to answer biologically meaningful
   questions.
3. There are fundamental laws governing the
   organization of biological networks.

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Hypotheses

1. Multiscale and large-scale stochastic simulation.
   Gillespie Petzold for stiff stochastic systems.
2. Simulation alone is not scalable. Automated
   scalable inference using SOSTOOLS.
3. There are fundamental laws governing the
   organization of biological networks. Without
   exploiting these, the complexity is
   overwhelming.

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Complexity
Recently, there has been a remarkable
convergences.
A coherent foundation for a general
understanding of highly evolved complexity
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Complexity
Biology
Molecular biology has catalogued cellular
components, and network structure is becoming
more apparent.
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Complexity
Advanced Technology
Biology
Advanced technologies are producing networks
approaching biological levels of complexity
(which is hidden to the user).
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Complexity
Advanced Technology
Math
Biology
New mathematics provides for the first time a
coherent theoretical framework for complex
networks (but not yet an accessible one).
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Complexity
Advanced Technology
Math
Biology
A coherent foundation for a general
understanding of highly evolved complexity
After many false starts.
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Complexity
Advanced Technology
Math
Biology

• Complementary ways to tell this story
• Give lots of examples from biology and technology
• Prove relevant theorems
• Deliver useful software tools

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Complexity
Advanced Technology
Math
Biology

• Today an attempt to distill an accessible
  message from enormous amount of detail
• Focus on universal laws that transcend details
• Minimize math, maximize examples
• Provide broader context for the rest of the
  shortcourse

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Complexity
Advanced Technology
Biology
Math

• This week
• Case studies in microbial signaling and
  regulation networks
• Will attempt to put details into broader context
• Saturday will consider computational challenges

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Hard Problems
coNP
NP
P easy
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Hard Problems
coNP
Economics
Algorithms
Controls
NP
Communications
P
Dynamical Systems
Physics
98

• Domain-specific assumptions
• Enormously successful
• Handcrafted theories
• Incompatible assumptions
• Tower of Babel where even experts cannot
  communicate
• Unified theories failed
• New challenges unmet

Economics
Algorithms
Controls
Communications
P
Dynamical Systems
Physics
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Hard Problems
coNP
Internet
Economics
Algorithms
Controls
NP
Communications
P
Dynamical Systems
Physics
100
Hard Problems
coNP
Biology
Economics
Algorithms
Controls
NP
Internet
Communications
P
Dynamical Systems
Physics
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Biology and advanced technology

• Biology
• Integrates control, communications, computing
• Into distributed control systems
• Built at the molecular level
• Advanced technologies will increasingly do the
  same
• We need new theory and math, plus unprecedented
  connection between systems and devices
• Two challenges for greater integration
• Unified theory of systems
• Multiscale from devices to systems

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Hard Problems
coNP
Unified Theory
Goal
Economics
Algorithms
Biology
Controls
NP
Goal
Internet
Communications
P
Dynamical Systems
Physics
103
Hard Problems
coNP
Biology
Economics
Algorithms
Controls
NP
Internet
Communications
P
Dynamical Systems
Physics