IDEAS home Printed from https://ideas.repec.org/p/wop/safiwp/00-11-061.html
   My bibliography  Save this paper

Replication and Mutation on Neutral Networks: Updated Version 2000

Author

Listed:
  • Christian Reidys
  • Christian V. Forst
  • Peter Schuster

Abstract

Folding of RNA sequences into secondary structures is viewed as a map that assigns a uniquely defined base pairing pattern to every sequence. The mapping is non-invertible since many sequences fold into the same minimum free energy (secondary) structure or shape. The preimages of this map, called neutral networks, are uniquely associated with the shapes and vice versa. Random graph theory is used to construct networks in sequence space which are suitable models for neutral networks. The theory of molecular quasispecies has been applied to replication and mutation on single-peak fitness landscapes. This concept is extended by considering evolution on degenerate multi-peak landscapes which originate from neutral networks by assuming that one particular shape is fitter than all others. On such a single-shape landscape the superior fitness value is assigned to all sequences belonging to the master shape. All other shapes are lumped together and their fitness values are averaged in a way that is reminiscent of mean field theory. Replication and mutation on neutral networks are modeled by phenomenological rate equations as well as by a stochastic birth-and-death model. In analogy to the error threshold in sequence space the phenotypic error threshold separates two scenarios: (i) a stationary (fittest) master shape surrounded by closely related shapes and (ii) populations drifting through shape space by a diffusion like process. The error classes of the quasispecies model are replaced by distance classes between the master shape and the other structures. Analytical results are derived for single-shape landscapes, in particular, simple expressions are obtained for the mean fraction of master shapes in a population and for phenotypic error thresholds. The analytical results are complemented by data obtained from computer simulation of the underlying stochastic processes. The predictions of the phenomenological approach on the single-shape landscape are very well reproduced by replication and mutation kinetics of tRNAphe. Simulation of the stochastic process at a resolution of individual distance classes yields data which are in excellent agreement with the results derived from the birth-and-death model.

Suggested Citation

  • Christian Reidys & Christian V. Forst & Peter Schuster, 2000. "Replication and Mutation on Neutral Networks: Updated Version 2000," Working Papers 00-11-061, Santa Fe Institute.
  • Handle: RePEc:wop:safiwp:00-11-061
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. Gernot Grabher & Walter W. Powell (ed.), 2004. "Networks," Books, Edward Elgar Publishing, volume 0, number 2771.
    2. W. Fontana & P. Schuster, 1998. "Shaping Space: The Possible and the Attainable in RNA Genotype-Phenotype Mapping," Working Papers ir98004, International Institute for Applied Systems Analysis.
    3. Peter Schuster, 2000. "Molecular Insights into Evolution of Phenotypes," Working Papers 00-02-013, Santa Fe Institute.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tomassini, Marco, 2016. "Lévy flights in neutral fitness landscapes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 163-171.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Christian M. Reidys & Peter F. Stadler, 1998. "Neutrality in Fitness Landscapes," Working Papers 98-10-089, Santa Fe Institute.
    2. Teppo Felin & Stuart Kauffman & Roger Koppl & Giuseppe Longo, 2014. "Economic Opportunity and Evolution: Beyond Landscapes and Bounded Rationality," Post-Print hal-01415115, HAL.
    3. Brueckner, Jan K. & Pels, Eric, 2005. "European airline mergers, alliance consolidation, and consumer welfare," Journal of Air Transport Management, Elsevier, vol. 11(1), pages 27-41.
    4. Borm, Peter & van den Brink, Rene & Levinsky, Rene & Slikker, Marco, 2004. "On two new social choice correspondences," Mathematical Social Sciences, Elsevier, vol. 47(1), pages 51-68, January.
    5. Moukarzel, Cristian F., 2005. "Effective dimensions in networks with long-range connections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 356(1), pages 157-161.
    6. René Brink & Agnieszka Rusinowska & Frank Steffen, 2013. "Measuring power and satisfaction in societies with opinion leaders: an axiomatization," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 41(3), pages 671-683, September.
    7. Petra M. Gleiss & Peter F. Stadler & Andreas Wagner & David A. Fell, 2000. "Small Cycles in Small Worlds," Working Papers 00-10-058, Santa Fe Institute.
    8. Castillo, Enrique & Hadi, Ali S. & Lacruz, Beatriz & Pruneda, Rosa E., 2008. "Semi-parametric nonlinear regression and transformation using functional networks," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2129-2157, January.
    9. Wang, Qing, 2007. "Artificial neural networks as cost engineering methods in a collaborative manufacturing environment," International Journal of Production Economics, Elsevier, vol. 109(1-2), pages 53-64, September.
    10. Andreas Lindemann & Christian Dunis & Paulo Lisboa, 2005. "Probability distributions and leveraged trading strategies: an application of Gaussian mixture models to the Morgan Stanley Technology Index Tracking Fund," Quantitative Finance, Taylor & Francis Journals, vol. 5(5), pages 459-474.
    11. Andreas Wagner, 2001. "Estimating Coarse Gene Network Structure from Large-Scale Gene Perturbation Data," Working Papers 01-09-051, Santa Fe Institute.
    12. Koen Frenken & Alessandro Nuvolari, 2004. "Entropy statistics as a framework to analyse technological evolution," Chapters, in: John Foster & Werner Hölzl (ed.), Applied Evolutionary Economics and Complex Systems, chapter 5, Edward Elgar Publishing.
    13. Graham, Carl, 2001. "Sharp estimates and a central limit theorem for the invariant law for a large star-shaped loss network," Stochastic Processes and their Applications, Elsevier, vol. 95(2), pages 177-202, October.
    14. Zhang, G. Peter & Keil, Mark & Rai, Arun & Mann, Joan, 2003. "Predicting information technology project escalation: A neural network approach," European Journal of Operational Research, Elsevier, vol. 146(1), pages 115-129, April.
    15. Daganzo, Carlos F. & Laval, Jorge & Munoz, Juan Carlos, 2002. "Ten Strategies for Freeway Congestion Mitigation with Advanced Technologies," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt4kd6v6qf, Institute of Transportation Studies, UC Berkeley.
    16. Leo Dana & Robert Hamilton & Kirsten Wick, 2009. "Deciding to export: An exploratory study of Singaporean entrepreneurs," Journal of International Entrepreneurship, Springer, vol. 7(2), pages 79-87, June.
    17. Hu, Michael Y. & Zhang, G. Peter & Chen, Haiyang, 2004. "Modeling foreign equity control in Sino-foreign joint ventures with neural networks," European Journal of Operational Research, Elsevier, vol. 159(3), pages 729-740, December.
    18. Pels, Eric & Verhoef, Erik T., 2004. "The economics of airport congestion pricing," Journal of Urban Economics, Elsevier, vol. 55(2), pages 257-277, March.
    19. Jan Cupal & Stephan Kopp & Peter F. Stadler, 1999. "RNA Space Shape Technology," Working Papers 99-03-022, Santa Fe Institute.
    20. Andreas Wagner, 2001. "The Yeast Protein Interaction Network Evolves Rapidly and Contains Few Redundant Duplicate Genes," Working Papers 01-04-022, Santa Fe Institute.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wop:safiwp:00-11-061. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thomas Krichel (email available below). General contact details of provider: https://edirc.repec.org/data/epstfus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.