2022 IEEE 61st Conference on Decision and Control (CDC) 2022
DOI: 10.1109/cdc51059.2022.9992359
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Limits on inferring gene regulatory networks from single-cell measurements of unstable mRNA levels

Abstract: Inference of gene regulatory networks from singlecell expression data, such as single-cell RNA sequencing, is a popular problem in computational biology. Despite diverse methods spanning information theory, machine learning, and statistics, it is unsolved. This shortcoming can be attributed to measurement errors, lack of perturbation data, or difficulty in causal inference. Yet, it is not known if kinetic properties of gene expression also cause an issue. We show how the relative stability of mRNA and protein … Show more

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Cited by 3 publications
(16 citation statements)
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“…In this section, we briefly review and replicate results from Mahajan et al 2022 [21], which studied the feasibility of network inference from mRNA abundance data under conditions of only intrinsic noise. We consider a system with two genes: Gene 1 and Gene 2.…”
Section: Standard Activation Model No Extrinsic Noisementioning
confidence: 85%
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“…In this section, we briefly review and replicate results from Mahajan et al 2022 [21], which studied the feasibility of network inference from mRNA abundance data under conditions of only intrinsic noise. We consider a system with two genes: Gene 1 and Gene 2.…”
Section: Standard Activation Model No Extrinsic Noisementioning
confidence: 85%
“…There are some reasons to question the assumption that mRNA abundance data can be used as a reliable proxy for protein abundance. For example, Mahajan et al 2022 [21] shows though theoretical analysis and stochastic simulations that, under conditions of only intrinsic noise, the correlation between mRNA abundance and protein abundance even for the same gene becomes quite weak if there is a large difference between the mRNA stability and protein stability. Additionally, Liu et al 2016 [20] reviews the literature and reports a similar finding, that the correlation between mRNA levels and protein levels can be weak in some scenarios, and knowledge of mRNA transcript abundance alone is not always sufficient to predict protein abundance levels.…”
Section: Efficacy Of Network Inference Methodsmentioning
confidence: 99%
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