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Feasibility and reliability of sequential logic with gene regulatory networks

Autor: MADEC, Morgan, Rosati, Elise, Lallement, Christophe

Publikováno v: PLoS ONE
PLoS ONE, Public Library of Science, 2021, ⟨10.1371/journal.pone.0249234⟩
PLoS ONE, 2021, ⟨10.1371/journal.pone.0249234⟩
PLoS ONE, Vol 16, Iss 3, p e0249234 (2021)

Gene regulatory networks exhibiting Boolean behaviour, e.g. AND, OR or XOR, have been routinely designed for years. However, achieving more sophisticated functions, such as control or computation, usually requires sequential circuits or so-called sta

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::e61ade78c9444060167ef15accceabbb
https://hal.archives-ouvertes.fr/hal-03243997/document

Emergence of cooperative bistability and robustness of gene regulatory networks

Autor: Macoto Kikuchi, Shintaro Nagata

Publikováno v: PLoS Computational Biology
PLoS Computational Biology, Vol 16, Iss 6, p e1007969 (2020)

Gene regulatory networks (GRNs) are complex systems in which many genes regulate mutually to adapt the cell state to environmental conditions. In addition to function, the GRNs possess several kinds of robustness. This robustness means that systems d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ddf8eac243a606821f0eed60b0e1c4e
http://europepmc.org/articles/PMC7351242

Inferring a network from dynamical signals at its nodes

Autor: Lilianne R. Mujica-Parodi, Luca Agozzino, Corey Weistuch, Ken A. Dill

Publikováno v: PLoS computational biology, vol 16, iss 11
PLoS Computational Biology, Vol 16, Iss 11, p e1008435 (2020)
PLoS Computational Biology

We give an approximate solution to the difficult inverse problem of inferring the topology of an unknown network from given time-dependent signals at the nodes. For example, we measure signals from individual neurons in the brain, and infer how they

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::361ab0eda7d7b873a1270e03b39977ca

Implications of diffusion and time-varying morphogen gradients for the dynamic positioning and precision of bistable gene expression boundaries

Autor: Melinda Liu Perkins

Publikováno v: PLoS Computational Biology, Vol 17, Iss 6, p e1008589 (2021)
PLoS Computational Biology

The earliest models for how morphogen gradients guide embryonic patterning failed to account for experimental observations of temporal refinement in gene expression domains. Following theoretical and experimental work in this area, dynamic positional

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95d3c75dff750da1c684a176c157dc72
https://doi.org/10.1371/journal.pcbi.1008589