22 October 2010
Ran Kafri
Kirschner and Lahav Labs, Department of Systems Biology
Harvard Medical School
Jason Levy
Department of Mathematics
University of Ottawa
An inherent flaw in mathematical models of signal transduction is that they typically consist of differential equations that describe our pre-existing narratives of the signaling events, making it hard to "think outside the box". In practice, there are always numerous different possible models (narratives) that fit any given set of measurements. Typically, such models would also consist of more free parameters than measurements can actually support.
Confronting these limitations, we have developed Ergodic Rate Analysis (ERA), a method of deriving protein dynamics through basic conservation principles. From individual measurements of large populations of fixed cells, ERA retrieves both dynamics and positive/negative feedback, without requiring prior assumptions or free parameters. Direct measurements using time lapse microscopy have confirmed ERA predictions. We will describe the results of ERA on regulation of protein mass production in the cell cycle of cancer cells.