The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Accurate information transmission through dynamic biochemical signaling networks
Open accessAbstract
Stochasticity inherent to biochemical reactions (intrinsic noise) and variability in cellular states (extrinsic noise) degrade information transmitted through signaling networks. We analyzed the ability of temporal signal modulation—that is, dynamics—to reduce noise-induced information loss. In the extracellular signal–regulated kinase (ERK), calcium (Ca 2+ ), and nuclear factor kappa-B (NF-κB) pathways, response dynamics resulted in significantly greater information transmission capacities compared to nondynamic responses. Theoretical analysis demonstrated that signaling dynamics has a key role in overcoming extrinsic noise. Experimental measurements of information transmission in the ERK network under varying signal-to-noise levels confirmed our predictions and showed that signaling dynamics mitigate, and can potentially eliminate, extrinsic noise–induced information loss. By curbing the information-degrading effects of cell-to-cell variability, dynamic responses substantially increase the accuracy of biochemical signaling networks.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Information transfer by leaky, heterogeneous, protein kinase signaling systems
Voliotis, M., Perrett, R. M., McWilliams, C., McArdle, C. A., & Bowsher, C. G. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1314446111 · Cited by 98
Cited by
Van Valen, D. A., Kudo, T., Lane, K. M., Macklin, D. N., Quach, N. T., DeFelice, M. M., Maayan, I., Tanouchi, Y., Ashley, E. A., & Covert, M. W. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005177 · Cited by 557
Robustness and Information Transfer within IL-6-induced JAK/STAT Signalling
Billing, U., Jetka, T., Nortmann, L., Wundrack, N., Komorowski, M., Waldherr, S., Schaper, F., & Dittrich, A. (2019) · Communications Biology · doi:10.1038/s42003-018-0259-4 · Cited by 64
Relaxation oscillations and hierarchy of feedbacks in MAPK signaling
Kochańczyk, M., Kocieniewski, P., Kozłowska, E., Jaruszewicz-Błońska, J., Sparta, B., Pargett, M., Albeck, J. G., Hlavacek, W. S., & Lipniacki, T. (2017) · Scientific Reports · doi:10.1038/srep38244 · Cited by 59
Self-citationFiebelkow, J., Guendel, A., Guendel, B., Mehwald, N., Jetka, T., Komorowski, M., Waldherr, S., Schaper, F., & Dittrich, A. (2021) · Cell Communication and Signaling · doi:10.1186/s12964-021-00770-7 · Cited by 53
Mathematical modeling of gonadotropin-releasing hormone signaling
Pratap, A., Garner, K. L., Voliotis, M., Tsaneva-Atanasova, K., & McArdle, C. A. (2017) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2016.08.022 · Cited by 35
Signaling pathways have an inherent need for noise to acquire information
Azpeitia, E., Balanzario, E. P., & Wagner, A. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-03778-x · Cited by 20
Modeling evolution of crosstalk in noisy signal transduction networks
Tareen, A., Wingreen, N. S., & Mukhopadhyay, R. (2018) · Physical Review E · doi:10.1103/physreve.97.020402 · Cited by 11
Nearly maximal information gain due to time integration in central dogma reactions
Sarkar, S., & Rammohan, J. (2023) · iScience · doi:10.1016/j.isci.2023.106767
Metadata
- Authors
- Selimkhanov, J., Taylor, B., Yao, J., Pilko, A., Albeck, J., Hoffmann, A., Tsimring, L., & Wollman, R.
- Venue
- Science
- Published
- 2014-12-12
- Volume
- 346
- Issue
- 6215
- Pages
- 1370-1373
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2021387539
- Cited by
- 378
- References
- 1
- FWCI
- 10.46
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
