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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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Transport Polymerization and assembly Core metabolism Autocatalytic and regulatory feedback Whole cell metabolism
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Metabolite Enzyme +Regulation Autocatalysis
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Metabolite Enzyme +Regulation Autocatalysis
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Metabolite Enzyme + - +
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Stoichiometry or mass and energy balance Nutrients Products Interna l
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Core metabolism
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Transport Polymerization and assembly Core metabolism Autocatalytic and regulatory feedback Whole cell metabolism
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transport Polymerization and assembly Core metabolism Autocatalytic and regulatory feedback Nested bowties
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Polymerization and assembly transport Core metabolism Nested bowties Our first universal architecture
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The core metabolism bowtie Nutrients Products
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Energy and reducing Fatty acids Sugars Nucleotides Amino Acids Biosynthesis Catabolism Carriers and Precursor Metabolites Cartoon metabolism
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Catabolism Carriers and Precursor Metabolites The metabolism bowtie protocol Energy and reducing Fatty acids Sugars Nucleotides Amino Acids Nutrients Products Catabolism Synthesis
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Core: special purpose enzymes controlled by competitive inhibition and allostery Edges: general purpose polymerases and machines controlled by regulated recruitment Uncertain
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Core: Highly efficient Edges: Robustness and flexibility 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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Collect and import raw materials Common currencies and building blocks Complex assembly Manufacturing and metabolism Collect and import raw materials Common currencies and building blocks Complex assembly Taxis and transport Polymerization and assembly Core metabolism Autocatalytic and regulatory feedback
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Variety of producers Electric power
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Variety of consumers Electric power
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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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Complex assembly Raw materials Complex assembly Raw materials Building blocks
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Collect and import raw materials Common currencies and building blocks Complex assembly Steel manufacturing
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Variety of consumers Variety of producers Energy carriers transport assemblymetabolism Core: special purpose machines controlled by allostery
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Variety of consumers Variety of producers Energy carriers transport assemblymetabolism Edges: general purpose machines controlled by regulated recruitment
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Variety of consumers Variety of producers Energy carriers transport assemblymetabolism Robust and evolvable
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Variety of consumers Variety of producers Energy carriers transport assemblymetabolism Fragile and hard to change
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Variety of consumers Variety of producers Energy carriers transport assemblymetabolism Preserved by selection on three levels: 1.Fragile to change (short term) 2.Facilitates robustness elsewhere (short term) 3.Facilitates evolution (long term)
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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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Varied components Varied systems Robust Mesoscale The LEGO connector protocol
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Software Hardware Early computing Analog substrate Various functionality Digital
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Software Hardware Applications Operating System Modern Computing
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Software Hardware Applications Operating System Modern Computing
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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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Taxis and transport Polymerization and assembly Core metabolism Autocatalytic and regulatory feedback Nested bowtie and hourglass Enzymes are modules. Bowtie architectures is a protocol. Conservation of energy and moiety is a law.
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essential : 230 nonessential:2373 unknown:1804 total:4407 http://www.shigen.nig.ac.jp/ecoli/pec
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Autocatalytic feedback Regulatory feedback transport assemblymetabolism
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Autocatalytic feedback Regulatory feedback transport assemblymetabolism Knockouts often lose robustness, not minimal functionality Knockouts often lose robustness, not minimal functionality Knockouts often lethal
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Brakes Airbags Seatbelts MirrorsWipers Headlights Steering GPS Radio Shifting Traction control Anti-skid Electronic ignition Electronic fuel injection Temperature control Cruise control Bumpers Fenders Suspension (control) Seats
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Brakes Airbags Seatbelts MirrorsWipers Headlights Steering GPS Radio Shifting Traction control Anti-skid Electronic ignition Electronic fuel injection Temperature control Cruise control Bumpers Fenders Suspension (control) Seats Knockouts often lose robustness, not minimal functionality Knockouts often lose robustness, not minimal functionality Knockouts often lethal
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Autocatalytic feedback Regulatory feedback transport assemblymetabolism Supplies Materials & Energy Supplies Materials & Energy Supplies Robustness Supplies Robustness Complexity Robustness Complexity
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Autocatalytic feedback Regulatory feedback transport assemblymetabolism If feedback regulation is the dominant protocol, what are the laws constraining whats possible?
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Autocatalytic feedback Regulatory feedback transport assemblymetabolism 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? 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?
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Autocatalytic feedback Regulatory feedback transport assemblymetabolism Supplies Materials & Energy Supplies Materials & Energy Supplies Robustness Supplies Robustness What are the laws of robustness?
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Transport Polymerization and assembly Core metabolism Autocatalytic and regulatory feedback Whole cell metabolism
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Metabolite Enzyme +Regulation Autocatalysis
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Metabolite Enzyme +Regulation Autocatalysis
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Metabolite Enzyme + - +
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perturbation Product inhibition Yi, Ingalls, Goncalves, Sauro
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h = [0 1 2 3] 05101520 0.8 0.85 0.9 0.95 1 1.05 Time (minutes) [ATP] h = 2 h = 1 h = 0 Step increase in demand for ATP. h = 3
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05101520 Time h = 3 h = 2 h = 1 h = 0 Tighter steady-state regulation Transients, Oscillations Higher feedback gain
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05101520 0.8 0.85 0.9 0.95 1 1.05 Time (minutes) [ATP] h = 3 h = 0 0246810 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Frequency Log(Sn/S0) h = 3 h = 0 Spectrum Time response Robust Yet fragile
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0246810 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Frequency Log(Sn/S0) h = 3 h = 0 Robust Yet fragile
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0246810 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Frequency Log(Sn/S0) h = 0 Robust Yet fragile
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0246810 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Frequency Log(Sn/S0) h = 3 h = 2 h = 1 h = 0 Tighter steady-state regulation Transients, Oscillations Theorem
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log|S | Tighter regulation Transients, Oscillations Biological complexity is dominated by the evolution of mechanisms to more finely tune this robustness/fragility tradeoff. This tradeoff is a law.
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Product inhibition is a protocol. log|S | This tradeoff is a law.
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Product inhibition is a protocol. log|S | This tradeoff is a law. PFK and ATP are modules.
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log|S | Conservation of fragility
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Robust Fragile Uncertainty Diseases of complexity Parasites Cancer Epidemics Auto-immune disease Complex development Regeneration/renewal Complex societies Immune response
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X n+1 X0X0 X1X1 XiXi XnXn ……Error log|S | We have a proof of this.
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Robust Fragile Uncertainty Parasites Cancer Epidemics Auto-immune disease Complex development Regeneration/renewal Complex societies Immune response This is a cartoon. We have no proof of this. Yet.
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Robust Fragile Uncertainty Parasites Cancer Epidemics Auto-immune disease Immune response Development Regeneration renewal Societies Why should any biologists care about this? How does it effect what can be done to understand complex biological networks?
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Robust Fragile Uncertainty Modeling robust yet fragile systems Required model complexity May need great detail here And much less detail here.
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Robust Fragile Uncertainty Required model complexity More detail. Less detail. Robust (fragile) to perturbations in components and environment Robust (fragile) to errors and simplifications in modeling
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05101520 Time h = 3 h = 2 h = 1 h = 0 0246810 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Frequency Log(Sn/S0) h = 3 h = 2 h = 1 h = 0 Tighter steady-state regulation Transients, Oscillations
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Metabolite Enzyme +Regulation Autocatalysis Energy and materials
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Autocatalytic feedback Regulatory feedback transport assemblymetabolism Even though autocatalytic feedback contributes relatively modestly to complexity, it has a huge indirect impact on regulatory complexity.
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Autocatalytic feedback Regulatory feedback transport assemblymetabolism 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… 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…
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05101520 Time h = 3 h = 2 h = 1 h = 0 0246810 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Frequency Log(Sn/S0) h = 3 h = 2 h = 1 h = 0 Tighter steady-state regulation Transients, Oscillations Regulatory feedback only
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Add autocatalytic feedback more
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Add autocatalytic feedback Transients, Oscillations
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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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Autocatalytic feedback Regulatory feedback transport assemblymetabolism Enzymes are modules. Bowtie architectures with product inhibition is a protocol suite. Conservation of energy, moiety, and fragility are laws.
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Taxis and transport Polymerization and assembly Core metabolism Autocatalytic and regulatory feedback Nested bowtie and hourglass Enzymes are modules. Bowtie architectures is a protocol. Conservation of energy and moiety is a law.
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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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A coherent foundation for a general understanding of highly evolved complexity Recently, there has been a remarkable convergences.
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Molecular biology has catalogued cellular components, and network structure is becoming more apparent. Biology
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Advanced technologies are producing networks approaching biological levels of complexity (which is hidden to the user). Biology Advanced Technology
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Biology Advanced Technology Math New mathematics provides for the first time a coherent theoretical framework for complex networks (but not yet an accessible one).
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A coherent foundation for a general understanding of highly evolved complexity Biology Advanced Technology Math After many false starts.
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Complementary ways to tell this story: 1.Give lots of examples from biology and technology 2.Prove relevant theorems 3.Deliver useful software tools Biology Advanced Technology Math
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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 Biology Advanced Technology Math
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This week: Case studies in microbial signaling and regulation networks Will attempt to put details into broader context Saturday will consider computational challenges Biology Advanced Technology Math
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NP coNP P easy Hard Problems
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NP coNP P Controls Communications Economics Dynamical Systems Physics Algorithms Hard Problems
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P Controls Communications Economics Dynamical Systems Physics Algorithms Domain-specific assumptions Enormously successful Handcrafted theories Incompatible assumptions Tower of Babel where even experts cannot communicate Unified theories failed New challenges unmet
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NP coNP P Controls Communications Economics Dynamical Systems Physics Algorithms Hard Problems Internet
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NP coNP P Controls Communications Economics Dynamical Systems Physics Algorithms Hard Problems Biology Internet
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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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NP coNP P Hard Problems Controls Communications Economics Dynamical Systems Physics Algorithms Goal Internet Biology Unified Theory
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NP coNP P Controls Communications Economics Dynamical Systems Physics Algorithms Hard Problems Biology Internet
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