||<p>Understanding the mechanism behind cell-size control of bacteria such as E. coli
has been an active research topic for decades. Until about 2010, most studies were
limited to measurements at the cell population level. Recently advanced technologies
and techniques, including Mother Machine and modern microscopic imaging, as well as
new biological insights and experiment techniques have enabled measurements of cell
growth and division at individual cell level with high spatial and temporal resolution.
This unprecedented data allowed scientists to take a closer look into the patterns
of cell growth and division, to search for new answers, and to gain a better understanding
of the natural law governing cell growth. This thesis study is based on six data sets
provided by the You lab at Duke University and by the Jun lab at University of California,
San Diego. We focus on exploratory and quantitative study of inter-generation relationships
among certain cell growth parameters and variables, including the variation in each
relationship.</p><p>We report and describe three particular findings. (1) The variation
in cell size at birth between two successive generations, i.e., mother and daughter
generations, is better captured in two separate zones in the mother-daughter plane
of initial cell size. This leads to a two-phase linear model with much narrower noise
spread. The model can be used to connect or compensate for certain well-known models.
(2) The variation in doubling time between two successive generations is confined
in a finite region with non-uniform density. Specifically, the confining region is
apparently triangular in the successive-generation plot of doubling time. The highest
variation of doubling time in daughter-generation corresponds to the median for the
mother- generation. This variation structure of successive-generation is further used
to predict the variations in succeeding generations via an iterative simulation method.
(3) The relationship between cell size and doubling time is studied with Fourier analysis.
We found that the two dominant frequencies of the cell-size time series are nearly
constant for each lineage. Furthermore, the top dominant frequency location is invariant
under random re-ordering of generations. This invariance suggests that the dominant
frequency is an intra-generation property, i.e., an inherent property. These findings
are descriptive rather than explanatory. Nonetheless, they provide additional angles
to examine, re-examine and improve our understanding of cell growth control mechanism.
The findings also show, perhaps in a subtle way, the effect of computational concepts
and techniques, which we used to probe into data on the finding, artifacts and their