Doylelicious+Thoughts+of+the+Day

//Page created on Monday July 25th, 2011 @ 6:51 p.m. (PDT)//

Tuesday August 2nd, 2011, 4:00 p.m.
=John Doyle (Caltech and KITP) will give a joint talk between KITP and CCDC = =** Title of the talk: Hard constraints on robust efficiency in metabolism and other complex networks **= = (Location: Main Seminar Room) = Please see abstract below. Feel free to add your comments and/or questions here.

This talk will review recent progress on developing a “unified” theory for complex networks involving three elements: hard limits on achievable robust performance (tradeoffs, misnamed “laws”), the organizing principles that succeed or fail in achieving them (architectures and protocols), and the resulting high variability data and “robust yet fragile” behavior observed in real systems and case studies (behavior, data). We will focus primarily on “hard limits” using glycolytic oscillations as a case study. We will also review the structure of metabolic networks (including that they are neither scale-free nor small-world), how autocatalysis aggravates control, and what cells do to ameliorate this. Insights into what universal laws, architecture, and organizational principles might look like can be drawn from three converging research themes. First, the organizational principles of organisms and evolution are becoming increasingly apparent. Richly detailed mechanistic explanations of biological complexity, robustness, and evolvability point to universal principles and architectures. Second, while the components differ and the system processes are far less integrated, advanced technology’s complexity is now approaching biology’s and there are striking convergences at the level of organization and architecture. Determining what is essential about this convergence and what is merely historical accident requires a deeper understanding of architecture — the most universal, high-level, persistent elements of organization — and protocols. Protocols define how diverse modules interact, and architecture defines how sets of protocols are organized. Third, new mathematical frameworks for the study of complex networks suggests that this apparent network-level evolutionary convergence within/between biology/technology is not accidental, but follows necessarily from their universal system requirements to be fast, efficient, adaptive, evolvable, and most importantly, robust to perturbations in their environment and component parts. The universal hard limits on systems and their components have until recently been studied separately in fragmented domains of physics, chemistry, biology, communications, computation, and control, but a unified theory is needed and appears feasible. We have the beginnings of the underlying mathematical framework and also a series of case studies in classical problems in complexity from statistical mechanics, turbulence, cell biology, human physiology and medicine, neuroscience, wildfire ecology, earthquakes, economics, the Internet, and smartgrid. A confounding commonality we must both overcome and exploit is that the most robust and powerful mechanisms are also the most cryptic, hidden from introspection or simple investigation. These mechanisms can give rise to a host of illusions, errors, and confusion, but are also the essential keys to reverse engineering hidden network complexity.

Chandra F, Buzi G, Doyle JC (2011) Glycolytic oscillations and limits on robust efficiency. //Science//. Vol 333, pp 187-192. http://brain-m11.wikispaces.com/file/view/ScienceGlycolyticOscOnlineFinal.pdf
 * References: **

JC Doyle, ME Csete (2011) Architecture, Constraints, and Behavior, //P Natl Acad Sci// //USA//, in press http://brain-m11.wikispaces.com/file/view/PNAS-2011-Doyle-1103557108.pdf

Nuno Martins’ website: [|http://terpconnect.umd.edu/~nmartins/Nuno_C_Martins_University_of_Maryland_Personal_Site/Home.html]

Monday July 25th, 2011
=John Doyle (Caltech and KITP) gave the Director's Blackboard Seminar on ** Architecture, Constraints, Behavior in Your Brain (and Zombies) **in the KITP Auditorium (Room 1403) = Please see abstract below. Feel free to add your comments and/or questions here.

Abstract (from Doyle and Csete, 2011)

This talks aims to bridge progress in neuroscience involving sophisticated quantitative analysis of behavior, including the new use of robust control, with other relevant conceptual and theoretical frameworks from systems engineering, systems biology, and mathematics. Familiar and accessible case studies are used to illustrate concepts of robustness, organization, and architecture (modularity and protocols) that are central to understanding complex networks. These essential organizational features are hidden during normal function of a system, but fundamental for understanding the nature, design, and function of complex biologic and technologic systems. Systems approaches to biology, medicine, engineering, and neuroscience face converging challenges, as modern science, technology, and culture create dauntingly complex but similar and overlapping problems in these domains. Our goal is to develop more integrated theory and methods applicable to all systems including neuroscience, by concentrating on organizational principles of complex systems. Beyond scientific understanding of systems, practitioners want to avoid and fix network errors, failures, and fragilities. This practical necessity requires mechanistic and often domain-specific explanations, not vague generalities. So “universal” theories must facilitate the inclusion of domain mechanisms and details, and manage rather than trivialize their complexity. Here we aim to put recent progress in both experimental and theoretical neuroscience in the context of a shared conceptual and mathematical framework, in which a main theme is that complexity is driven by robustness, not by minimal functionality. We will emphasize robustness and efficiency tradeoffs and constraints and the control systems that balance them, their highly organized architecture, and its resulting side effects and fragilities. A confounding commonality we must both overcome and exploit is that the most robust and powerful mechanisms are also the most cryptic, hidden from introspection or simple investigation. These mechanisms can give rise to a host of illusions, errors, and confusion, but are also the essential keys to reverse engineering hidden network complexity.


 * References: **



[|Chandra F, Buzi G, Doyle JC (2011) Glycolytic oscillations and limits on robust efficiency. //Science//. Vol 333, pp 187-192.]