Quantifying how post-transcriptional noise and gene copy number variation bias transcriptional parameter inference from mRNA distributions
Transcriptional rates are often estimated by fitting the distribution of mature mRNA numbers
measured using smFISH (single molecule fluorescence in situ hybridization) with the …
measured using smFISH (single molecule fluorescence in situ hybridization) with the …
[HTML][HTML] Quantifying and correcting bias in transcriptional parameter inference from single-cell data
R Grima, PM Esmenjaud - Biophysical Journal, 2024 - cell.com
The snapshot distribution of mRNA counts per cell can be measured using single-molecule
fluorescence in situ hybridization or single-cell RNA sequencing. These distributions are …
fluorescence in situ hybridization or single-cell RNA sequencing. These distributions are …
[HTML][HTML] Cell-cycle dependence of transcription dominates noise in gene expression
CJ Zopf, K Quinn, J Zeidman… - PLoS computational …, 2013 - journals.plos.org
The large variability in mRNA and protein levels found from both static and dynamic
measurements in single cells has been largely attributed to random periods of transcription …
measurements in single cells has been largely attributed to random periods of transcription …
Effects of cell cycle variability on lineage and population measurements of messenger RNA abundance
R Perez-Carrasco, C Beentjes… - Journal of the Royal …, 2020 - royalsocietypublishing.org
Many models of gene expression do not explicitly incorporate a cell cycle description. Here,
we derive a theory describing how messenger RNA (mRNA) fluctuations for constitutive and …
we derive a theory describing how messenger RNA (mRNA) fluctuations for constitutive and …
[HTML][HTML] Quantifying intrinsic and extrinsic variability in stochastic gene expression models
Genetically identical cell populations exhibit considerable intercellular variation in the level
of a given protein or mRNA. Both intrinsic and extrinsic sources of noise drive this variability …
of a given protein or mRNA. Both intrinsic and extrinsic sources of noise drive this variability …
[HTML][HTML] Using a single fluorescent reporter gene to infer half-life of extrinsic noise and other parameters of gene expression
Fluorescent and luminescent proteins are often used as reporters of transcriptional activity.
Given the prevalence of noise in biochemical systems, the time-series data arising from …
Given the prevalence of noise in biochemical systems, the time-series data arising from …
[HTML][HTML] BayFish: Bayesian inference of transcription dynamics from population snapshots of single-molecule RNA FISH in single cells
Single-molecule RNA fluorescence in situ hybridization (smFISH) provides unparalleled
resolution in the measurement of the abundance and localization of nascent and mature …
resolution in the measurement of the abundance and localization of nascent and mature …
[HTML][HTML] A stochastic model of the yeast cell cycle reveals roles for feedback regulation in limiting cellular variability
The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent
protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system …
protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system …
LTMG: a novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data
A key challenge in modeling single-cell RNA-seq data is to capture the diversity of gene
expression states regulated by different transcriptional regulatory inputs across individual …
expression states regulated by different transcriptional regulatory inputs across individual …
[HTML][HTML] Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast
Cells respond to their environment by modulating protein levels through mRNA transcription
and post-transcriptional control. Modest observed correlations between global steady-state …
and post-transcriptional control. Modest observed correlations between global steady-state …
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