Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Decomposing variability in protein levels from noisy expression, genome
  duplication and partitioning errors during cell-divisions   Inside individual cells, expression of genes is inherently stochastic and
manifests as cell-to-cell variability or noise in protein copy numbers. Since
proteins half-lives can be comparable to the cell-cycle length, randomness in
cell-division times generates additional intercellular variability in protein
levels. Moreover, as many mRNA/protein species are expressed at low-copy
numbers, errors incurred in partitioning of molecules between the mother and
daughter cells are significant. We derive analytical formulas for the total
noise in protein levels for a general class of cell-division time and
partitioning error distributions. Using a novel hybrid approach the total noise
is decomposed into components arising from i) stochastic expression; ii)
partitioning errors at the time of cell-division and iii) random cell-division
events. These formulas reveal that random cell-division times not only generate
additional extrinsic noise but also critically affect the mean protein copy
numbers and intrinsic noise components. Counter intuitively, in some parameter
regimes noise in protein levels can decrease as cell-division times become more
stochastic. Computations are extended to consider genome duplication, where the
gene dosage is increased by two-fold at a random point in the cell-cycle. We
systematically investigate how the timing of genome duplication influences
different protein noise components. Intriguingly, results show that noise
contribution from stochastic expression is minimized at an optimal genome
duplication time. Our theoretical results motivate new experimental methods for
decomposing protein noise levels from single-cell expression data.
Characterizing the contributions of individual noise mechanisms will lead to
precise estimates of gene expression parameters and techniques for altering
stochasticity to change phenotype of individual cells.

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The categories of this paper are: stat
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
24
The categories of this paper are: dg-ga
23
The categories of this paper are: solv-int
15
The categories of this paper are: nucl-ex
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ