E62 BME 140 Lecture Notes - Lecture 5: Emergence, Exponential Decay, Time Constant
25 Sep 2015
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Goals of lecture: define a network, ask about properties of network, measures, generates, use networks to probe emergent behaviors, size, effects of failure. 21,000 choose 2 64 bit number becomes 170! Protein-interaction: re-engineer a network, non-overlapping networks, how does an eye become something different than a heart when they begin from the same ingredients, therapeutic, how do we turn off something that is on? d. Encoding a network: use an adjacency matrix. Measuring a network: use a plot graph of probability of k vs. k. Poisson (exponential decay: emergent property of random networks, most nodes will have roughly the same number of edges, extremely unlikely to see a highly connected node, real world networks don"t behave like this. Identify a recent technological advance solving a problem in one these areas. Standard form of a first-order differential equation: dz dt z z.
