PRINCIPIS DE DISSENY BIOLÒGIC (BIOLOGICAL DESIGN PRINCIPLES)
Engineering approaches to biologic systems often ignore the fact that they are the by-product of evolutionary forces, thus incorporating historical accidents, tinkering and constraints that have shaped their organisation. That means that, whereas some structures reveal optimal solutions, others very well illustrate completely suboptimal designs indicating the historical role played by accidents.
What determines the structure and functional traits of biological systems? Why are biological systems modular? Is biological complexity the result of a pure optimization process? What is the role of natural selection? What is the evolutionary origin of aging and cancer? What is the origin of asymmetry in the brain? How can a system store memories as it occurs in the brain? These are questions that we address within this course using relevant biological examples along with mathematical and computational models.
CONTINGUTS / CONTENTS1. Design, optimisation and evolution: tinkering versus engineering. Examples of non-optimaldesigns in human bodies. Darwinian medicine: a case for function versus structure. 2. Optimization on fitness landscapes. Examples from technology. Branching structures and biological fractals.Simple models can explain very complex dynamics: chaos and th problem of prediction. Adaptive walks.String models, genomes and information thresholds. 3. Information, order and disorder. Randomness and how to measure it. What makesbiological systems different? Self-organization and form: looking for Blade Runner. 4. Robustness, reliability and distributed functionality: relevance and theoretical models.Modularity and design. Modules and building blocks. Hierarchies in biology. 5. Gene networks and switches: is biology Boolean? Boolean circuits and their equivalentsin biology. Series and parallel circuits. Synthetic biology and engineering metaphors. 6. Aging, stem cells and robust design. Why is human decay similar to machine malfunction?
ARTICLES (BASIC CONCEPTS)
- Evolving Inventions
John Koza et al., Scientific American 2003
- Evolution and the origins of disease
R.Nesse and G. Williams, Scientific American 1998
- Antichaos and adaptation
- Cellular automata as models for complexity
- Genetic algorithms principles of natural selection applied to computation
Forrest, Science 1993
- Why we fall apart
L. Gavrilov & N. Gavrilova IEEE Spectrum
- Fractals in physiology and medicine
A. Goldberger & B. West, Yale J. Biol. Med. 1973