Ignoring, Accounting For, and Embracing Noise in Biology

Cell Biology;Stochasticity;Mathematical Modelling;Biophysics

Rochman, Nash DeltaReich, Daniel H. ;

Johns Hopkins University

关键词: Cell Biology;    Stochasticity;    Mathematical Modelling;    Biophysics;   

Others  :  https://jscholarship.library.jhu.edu/bitstream/handle/1774.2/59164/ROCHMAN-DISSERTATION-2018.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: JOHNS HOPKINS DSpace Repository

【 摘 要 】

The universe is a noisy place in every sense of the word. From the detection ofcosmic microwave background radiation to the formulation and applicationof the Heisenberg uncertainty principle, most corners of modern science havesome stochastic flavor. Biology, and cell biology in particular, is no exception.Cells have a very large number of ever-changing, moving parts and seem toonly rarely lend themselves to simple, deterministic characterization. Havingaccepted this, how do we move forward - how do we treat this stochasticitywhen we seek to model and ultimately understand the governing functions ofa cell? I would like to discuss three strategies to answer this question.Firstly, we may ignore the noise. While it is always important to firstacknowledge variations from mean behavior, sometimes grappling with theprediction of higher moments just distracts from the concept we wish toexpress. Second, we may ;;treat” the noise. Often, we are not writing downan elegant theory but pipetting and we just want to know if our results arestatistically significant. Slightly better, we may wish to account for some bias inthe calculation of a mean value which is unmeasurable but well approximated,like the age distribution of a population. Third, and the most interesting case,we may embrace the noise. Occasionally, the heterogeneity of a population is more revealing of underlying mechanism than even mean behavior, as isespecially true when studying adaptability.I will cover, in chronological order, five disparate applications of thesethree strategies; 1) a model of surface interactions of helical filaments - with afocused example of amyloid beta fibrils - in which noise is ignored; 2) a studyof bacterial cell cycle duration regulation - in which noise is embraced andheterogeneity is predicted to confer adaptability to environmental stressors; 3)an investigation into mammalian cell volume regulation - in which noise istreated to gauge statistical significance across ensembles of single cells andage-related heterogeneity is invoked to explain higher moments of observedvolume distributions; 4) a study of stem cell pattern formation - in whichnoise is treated to measure the predictive value of a data-driven model ofcell specification; and 5) an investigation into the impacts of ergodicity oncell cycle duration and population growth rate - in which noise is embracedand heterogeneity is predicted to imply asymmetry in division under somecommonly assumed conditions.