Scaling dictates the decoder structure

Shen, Jingxiang; Liu, Feng; Tang, Chao

doi:10.1016/j.scib.2022.06.014

Cited by 2 publications

(1 citation statement)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our work focuses on amplitude information (input and output levels) and neglects spatial effects. Other studies have investigated the basic networks [10][11][12] or decoders [47][48][49][50] required to form spatial patterns in embryonic development, particularly in the fruit fly Drosophila. In Drosophila, a possible connection to value antagonism may be the mutual repression often accompanying stripe formation [51][52][53][54] .…”

Section: Discussionmentioning

confidence: 99%

Deduction of signaling mechanisms from cellular responses to multiple cues

et al. 2022

View full text Add to dashboard Cite

Cell signaling networks are complex and often incompletely characterized, making it difficult to obtain a comprehensive picture of the mechanisms they encode. Mathematical modeling of these networks provides important clues, but the models themselves are often complex, and it is not always clear how to extract falsifiable predictions. Here we take an inverse approach, using experimental data at the cell level to deduce the minimal signaling network. We focus on cells’ response to multiple cues, specifically on the surprising case in which the response is antagonistic: the response to multiple cues is weaker than the response to the individual cues. We systematically build candidate signaling networks one node at a time, using the ubiquitous ingredients of (i) up- or down-regulation, (ii) molecular conversion, or (iii) reversible binding. In each case, our method reveals a minimal, interpretable signaling mechanism that explains the antagonistic response. Our work provides a systematic way to deduce molecular mechanisms from cell-level data.

show abstract

Section: Discussionmentioning

confidence: 99%

Deduction of signaling mechanisms from cellular responses to multiple cues

et al. 2022

View full text Add to dashboard Cite

show abstract

A phase diagram structure determines the optimal sensitivity-precision trade-off in signaling systems

Kong,

Luo,

Liu

2024

Commun Phys

View full text Add to dashboard Cite

Signal transduction is crucial for many biological functions. However, it is still unclear how signaling systems function accurately under noisy situations. More specifically, such systems operate in a regime of low response noise, while maintaining high sensitivity to signals. To gain further insight on this regime, here we derive a fundamental trade-off between response sensitivity and precision in biological signaling processes under the static noise condition. We find that the optimal trade-off in signaling networks can be better characterized by a phase diagram structure rather than topological structures. We confirm that the patterning network of early Drosophila embryos agrees with our derived relationship, and apply the optimal phase diagram structure to quantitatively predict the patterning position shifts of the downstream genes, including hunchback, Krüppel, giant, knirps and even-skipped, upon the dosage perturbation of the morphogen Bicoid.

show abstract

Scaling dictates the decoder structure

Cited by 2 publications

References 66 publications

Deduction of signaling mechanisms from cellular responses to multiple cues

Deduction of signaling mechanisms from cellular responses to multiple cues

A phase diagram structure determines the optimal sensitivity-precision trade-off in signaling systems

Contact Info

Product

Resources

About