Class Notes (810,913)
Canada (494,374)
Biology (6,684)
Biology 1002B (1,340)

Lecture 25.docx

4 Pages
Unlock Document

Western University
Biology 1002B
Denis Maxwell

Lecture 25: Life as a complex system How a complexivist view of the world changes everything? Clicker question: If you were an ADP molecule inside a bacterial cell. How would you manage to find an ATP synthase so that you could become an ATP molecule A. I wwould follow the hydrogen ion flow B. The ATP synthase would grab me C. My electronegativity would attract me to the ATP synthase D. I would be actively pumped to the right area E. Random movement would bring me to the ATP synthase Our minds tend to explain patterns by “direct casual schemata”  Our world is very directional  This way of understanding is a schemata o causal schemas However some patterns require us to develop “emergent causal schemta”  Like a flock of birds flying there is no direction Diffusion is emergent rather than causal….  There is a room full of people: if you put red hats on a few on the left….it will spread out throughout the whle room  How does that happen? o We would come with the idea that the red hatted people would just stream from one side of the room to another. And there would be an even distribution of red hatted people. Many people would believe that the people would just stop. There is gradient and once it is dissipated it stops. o THIS IS NOT TRUE: sure the red headed people will be distributed throughout the club. Non random pattern: they were in this room and now they are in that room. They never stop moving. What would stop ADP from moving: heat. o ADP moves because it has thermal energy. Molecules do not stop moving once the gradient is dissipated. o Patterns and behaviour emerge out of interactions. o just emerged out of their local interactions with each other Direct Schema vs. Emergent schema Emergence…  Characteristics of the whole are not predictable by knowledge of the parts  emergence is an explanatory schema Simple systems  few parts  defined relationships  high predictability Example: building a simple table Complicated systems  many parts  defined relationships  highly controlled  sequential  high predictability Example: building a robot Complex system  many parts  changing relationships  no ventral control  self organized  emergent patterns (1/f)  Low predictability EXAMPLE: Termites. No central engineer. Control is distributed among members of the colony. Cannot predict how the next termite mound is going to look or where it is going to be. “1/f” patterns (power laws) arise in complex systems  white noise – no relationships in white noise (random) o no relationship  pink noise – made up of sound where the frequencies are present proportionally. Short wavelengths high proportion. Long wavelen
More Less

Related notes for Biology 1002B

Log In


Don't have an account?

Join OneClass

Access over 10 million pages of study
documents for 1.3 million courses.

Sign up

Join to view


By registering, I agree to the Terms and Privacy Policies
Already have an account?
Just a few more details

So we can recommend you notes for your school.

Reset Password

Please enter below the email address you registered with and we will send you a link to reset your password.

Add your courses

Get notes from the top students in your class.