The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Dynamics and control at feedback vertex sets. II: A faithful monitor to determine the diversity of molecular activities in regulatory networks
Open accessAbstract
Modern biology provides many networks describing regulations between many species of molecules. It is widely believed that the dynamics of molecular activities based on such regulatory networks are the origin of biological functions. However, we currently have a limited understanding of the relationship between the structure of a regulatory network and its dynamics. In this study we develop a new theory to provide an important aspect of dynamics from information of regulatory linkages alone. We show that the "feedback vertex set" (FVS) of a regulatory network is a set of "determining nodes" of the dynamics. The theory is powerful to study real biological systems in practice. It assures that (i) any long-term dynamical behavior of the whole system, such as steady states, periodic oscillations or quasi-periodic oscillations, can be identified by measurements of a subset of molecules in the network, and that (ii) the subset is determined from the regulatory linkage alone. For example, dynamical attractors possibly generated by a signal transduction network with 113 molecules can be identified by measurement of the activity of only 5 molecules, if the information on the network structure is correct. Our theory therefore provides a rational criterion to select key molecules to control a system. We also demonstrate that controlling the dynamics of the FVS is sufficient to switch the dynamics of the whole system from one attractor to others, distinct from the original.
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
A genomic regulatory network for development
Davidson, E. H., Rast, J. P., Oliveri, P., Ransick, A., Calestani, C., Yuh, C.-H., Minokawa, T., Amore, G., Hinman, V., Arenas-Mena, C., et al. (2002) · Science · doi:10.1126/science.1069883 · Cited by 1,567
The logical analysis of continuous, non-linear biochemical control networks
Glass, L., & Kauffman, S. A. (1973) · Journal of Theoretical Biology · doi:10.1016/0022-5193(73)90208-7 · Cited by 940
Research works printed but not linked: 17
- Akutsu, 1998, A system for identifying genetic networks from gene expression patterns produced by gene disruptions and overexpressions, Genome Inf., 9, 151
- Fiedler, 2013, Dynamics and control at feedback vertex sets I: informative and determining nodes in regulatory networks, J. Dyn. Differential Eqns., 10.1007/s10884-013-9312-7 · DOI
- Foias, 1984, Determination of the solutions of the Navier–Stokes equations by a set of nodal values, Math. Comput., 43, 117, 10.1090/S0025-5718-1984-0744927-9 · doi:10.1090/s0025-5718-1984-0744927-9
- Foias, 1991, Determining nodes, finite differences schemes and inertial manifolds, Nonlinearity, 4, 135, 10.1088/0951-7715/4/1/009 · doi:10.1088/0951-7715/4/1/009
- Imai, 2006, Regulatory blueprint for a chordate embryo, Science, 312, 1183, 10.1126/science.1123404 · DOI · Paper page
- Joly, 2012, Observation and inverse problems in coupled cell networks, Nonlinearity, 25, 657, 10.1088/0951-7715/25/3/657 · doi:10.1088/0951-7715/25/3/657
- Liu, 2011, Controllability of complex networks, Nature, 473, 167, 10.1038/nature10011 · DOI · Paper page
- Liu, 2013, Observability of complex systems, Proc. Natl. Acad. Sci. USA, 110, 2460, 10.1073/pnas.1215508110 · DOI · Paper page
- Mirsky, 2009, A model of the cell-autonomous mammalian circadian clock, Proc. Natl. Acad. Sci. USA, 106, 11107, 10.1073/pnas.0904837106 · DOI · Paper page
- Mochizuki, 2005, An analytical study of the number of steady states in gene regulatory networks, J. Theor. Biol, 236, 291, 10.1016/j.jtbi.2005.03.015 · DOI
- Mochizuki, 2008, Structure of regulatory networks and diversity of gene expression patterns, J. Theor. Biol, 250, 307, 10.1016/j.jtbi.2007.09.019 · DOI
- Mochizuki, 2010, Analyzing steady states of dynamics of bio-molecules from the structure of regulatory networks, J. Theor. Biol., 266, 323, 10.1016/j.jtbi.2010.06.007 · DOI
- Müller, 2011, Few inputs can reprogram biological networks, Nature, 478, E4, 10.1038/nature10543 · DOI
- Oda, 2005, A comprehensive pathway map of epidermal growth factor receptor signaling, Mol. Syst. Biol, 1, 1, 10.1038/msb4100014 · DOI · Paper page
- Shen-Orr, 2002, Network motifs in the transcriptional regulation network of Escherichia coli, Nat. Genet., 31, 64, 10.1038/ng881 · DOI · Paper page
- Takens, 2010, Reconstruction theory and nonlinear time series analysis, vol. 3, 345
- Tamura, 2010, Finding minimum reaction cuts of metabolic networks under a Boolean model using integer programming and feedback vertex sets, Int. J. Knowl. Discovery Bioinformatics, 1, 14, 10.4018/jkdb.2010100202 · DOI
Cited by
Control principles of complex systems
Liu, Y.-Y., & Barabási, A.-L. (2016) · Reviews of Modern Physics · doi:10.1103/revmodphys.88.035006 · Cited by 654
Synchronization in complex networks and its application – A survey of recent advances and challenges
Tang, Y., Qian, F., Gao, H., & Kurths, J. (2014) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2014.09.003 · Cited by 358
Structure-based control of complex networks with nonlinear dynamics
Zañudo, J. G. T., Yang, G., & Albert, R. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1617387114 · Cited by 256
Network control principles for identifying personalized driver genes in cancer
Guo, W.-F., Zhang, S.-W., Zeng, T., Akutsu, T., & Chen, L. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbz089 · Cited by 44
Ishikawa, M., Sugino, S., Masuda, Y., Tarumoto, Y., Seto, Y., Taniyama, N., Wagai, F., Yamauchi, Y., Kojima, Y., Kiryu, H., et al. (2023) · Communications Biology · doi:10.1038/s42003-023-05594-4 · Cited by 22
Self-citation
Metadata
- Authors
- Mochizuki, A., Fiedler, B., Kurosawa, G., & Saito, D.
- Venue
- Journal of Theoretical Biology
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 335
- Pages
- 130-146
- ISSN
- 0022-5193 (ISSN-L)
- OpenAlex
- W1989915587
- Cited by
- 175
- References
- 2
- FWCI
- 2.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- creativecommons.org/licenses/by-nc-nd/3.0/ (vor)
- Funders
- JST PRESTO program
- CREST program of Japan
- HFSP program grant
- Deutsche Forschungsgemeinschaft (910)
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Dynamics and control at feedback vertex sets. II: A faithful monitor to determine the diversity of molecular activities in regulatory networks. https://app.cochat.ai/papers/10.1016/j.jtbi.2013.06.009
- The paper
- Mochizuki, A., Fiedler, B., Kurosawa, G., & Saito, D. (2013). Dynamics and control at feedback vertex sets. II: A faithful monitor to determine the diversity of molecular activities in regulatory networks. Journal of Theoretical Biology. https://doi.org/10.1016/j.jtbi.2013.06.009
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.