Grip on complexity in chemical reaction networks

Albert S. Y. Wong and Wilhelm T. S. Huck
Beilstein J. Org. Chem. 2017, 13, 1486–1497. https://doi.org/10.3762/bjoc.13.147

Cite the Following Article

Grip on complexity in chemical reaction networks
Albert S. Y. Wong and Wilhelm T. S. Huck
Beilstein J. Org. Chem. 2017, 13, 1486–1497. https://doi.org/10.3762/bjoc.13.147

How to Cite

Wong, A. S. Y.; Huck, W. T. S. Beilstein J. Org. Chem. 2017, 13, 1486–1497. doi:10.3762/bjoc.13.147

Download Citation

Citation data can be downloaded as file using the "Download" button or used for copy/paste from the text window below.
Citation data in RIS format can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Zotero.

Presentation Graphic

Picture with graphical abstract, title and authors for social media postings and presentations.
Format: PNG Size: 634.2 KB Download

Citations to This Article

Up to 20 of the most recent references are displayed here.

Scholarly Works

  • Ghosh, S.; Baltussen, M. G.; Ivanov, N. M.; Haije, R.; Jakštaitė, M.; Zhou, T.; Huck, W. T. S. Exploring Emergent Properties in Enzymatic Reaction Networks: Design and Control of Dynamic Functional Systems. Chemical reviews 2024, 124, 2553–2582. doi:10.1021/acs.chemrev.3c00681
  • Shklyaev, O. E.; Balazs, A. C. Interlinking spatial dimensions and kinetic processes in dissipative materials to create synthetic systems with lifelike functionality. Nature nanotechnology 2023, 19, 146–159. doi:10.1038/s41565-023-01530-z
  • Koyuncu, A. H.; Movilli, J.; Sahin, S.; Kriukov, D. V.; Huskens, J.; Wong, A. S. Y. Polylysine‐Coated Surfaces Drive Competition in Chemical Reaction Networks to Enable Molecular Information Processing. ChemSystemsChem 2023, 6. doi:10.1002/syst.202300030
  • Krab-Hüsken, L. E.; Pei, L.; de Vries, P. G.; Lindhoud, S.; Paulusse, J. M. J.; Jonkheijm, P.; Wong, A. S. Y. Conceptual Modeling Enables Systems Thinking in Sustainable Chemistry and Chemical Engineering. Journal of Chemical Education 2023, 100, 4577–4584. doi:10.1021/acs.jchemed.3c00337
  • Chieffo, C.; Shvetsova, A.; Skorda, F.; Lopez, A.; Fiore, M. The Origin and Early Evolution of Life: Homochirality Emergence in Prebiotic Environments. Astrobiology 2023, 23, 1368–1382. doi:10.1089/ast.2023.0007
  • Ramezanpour, A.; Mashaghi, A. Learning capacity and function of stochastic reaction networks. Journal of Physics: Complexity 2023, 4, 35006–035006. doi:10.1088/2632-072x/acf264
  • Sharma, C.; Maity, I.; Walther, A. pH-feedback systems to program autonomous self-assembly and material lifecycles. Chemical communications (Cambridge, England) 2023, 59, 1125–1144. doi:10.1039/d2cc06402b
  • Wen, M.; Spotte-Smith, E. W. C.; Blau, S. M.; McDermott, M. J.; Krishnapriyan, A. S.; Persson, K. A. Chemical reaction networks and opportunities for machine learning. Nature computational science 2023, 3, 12–24. doi:10.1038/s43588-022-00369-z
  • Kumar Bandela, A.; Sadihov‐Hanoch, H.; Cohen‐Luria, R.; Gordon, C.; Blake, A.; Poppitz, G.; Lynn, D. G.; Ashkenasy, G. The Systems Chemistry of Nucleic‐acid‐Peptide Networks. Israel Journal of Chemistry 2022, 62. doi:10.1002/ijch.202200030
  • Mahato, R. R.; Priyanka; Shandilya, E.; Maiti, S. Perpetuating enzymatically induced spatiotemporal pH and catalytic heterogeneity of a hydrogel by nanoparticles. Chemical science 2022, 13, 8557–8566. doi:10.1039/d2sc02317b
  • Baltussen, M. G.; van de Wiel, J.; Fernández Regueiro, C. L.; Jakštaitė, M.; Huck, W. T. S. A Bayesian Approach to Extracting Kinetic Information from Artificial Enzymatic Networks. Analytical chemistry 2022, 94, 7311–7318. doi:10.1021/acs.analchem.2c00659
  • Kahana, A.; Lancet, D. Self-reproducing catalytic micelles as nanoscopic protocell precursors. Nature reviews. Chemistry 2021, 5, 1–9. doi:10.1038/s41570-021-00329-7
  • Lakhova, T. N.; Kazantsev, F. V.; Lashin, S. A.; Matushkin, Y. G. The finding and researching algorithm for potentially oscillating enzymatic systems. Vavilovskii zhurnal genetiki i selektsii 2021, 25, 318–330. doi:10.18699/vj21.035
  • van der Helm, M. P.; de Beun, T.; Eelkema, R. On the use of catalysis to bias reaction pathways in out-of-equilibrium systems. Chemical science 2021, 12, 4484–4493. doi:10.1039/d0sc06406h
  • Reppe, T.; Poppe, S.; Tschierske, C. Controlling Mirror Symmetry Breaking and Network Formation in Liquid Crystalline Cubic, Isotropic Liquid and Crystalline Phases of Benzil-Based Polycatenars. Chemistry (Weinheim an der Bergstrasse, Germany) 2020, 26, 16066–16079. doi:10.1002/chem.202002869
  • Solà, J.; Jimeno, C.; Alfonso, I. Exploiting complexity to implement function in chemical systems. Chemical communications (Cambridge, England) 2020, 56, 13273–13286. doi:10.1039/d0cc04170j
  • Herrera, M.; Pérez-Hernández, M.; Parlikad, A. K.; Izquierdo, J. Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering. Processes 2020, 8, 312. doi:10.3390/pr8030312
  • Fischer, P. Vision Statement: Interactive Materials-Drivers of Future Robotic Systems. Advanced materials (Deerfield Beach, Fla.) 2020, 32, 1905953. doi:10.1002/adma.201905953
  • Lerch, M. M.; Grinthal, A.; Aizenberg, J. Viewpoint: Homeostasis as Inspiration—Toward Interactive Materials. Advanced materials (Deerfield Beach, Fla.) 2020, 32, 1905554. doi:10.1002/adma.201905554
  • Martinez-Amezaga, M.; Orrillo, A. G.; Furlan, R. L. E. Engineering multilayer chemical networks. Chemical science 2019, 10, 8338–8347. doi:10.1039/c9sc02166c

Patents

  • HUCK WILHELMUS THEODORUS STEFANUS; BALTUSSEN MATHIEU GÉRARD; ROBINSON WILLIAM EDWARD; DE JONG THIJS; GHOSH SOUVIK. A METHOD OF RESERVOIR COMPUTING AND A RESERVOIR COMPUTING SYSTEM. WO 2023075601 A1, May 4, 2023.
Other Beilstein-Institut Open Science Activities