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The topology of the transcription regulatory network in the yeast, Saccharomyces cerevisiae

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  • Farkas, I.
  • Jeong, H.
  • Vicsek, T.
  • Barabási, A.-L.
  • Oltvai, Z.N.

Abstract

A central goal of postgenomic biology is the elucidation of the regulatory relationships among all cellular constituents that together comprise the ‘genetic network’ of a cell or microorganism. Experimental manipulation of gene activity coupled with the assessment of perturbed transcriptome (i.e., global mRNA expression) patterns represents one approach toward this goal, and may provide a backbone into which other measurements can be later integrated.

Suggested Citation

  • Farkas, I. & Jeong, H. & Vicsek, T. & Barabási, A.-L. & Oltvai, Z.N., 2003. "The topology of the transcription regulatory network in the yeast, Saccharomyces cerevisiae," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 318(3), pages 601-612.
    • Handle: RePEc:eee:phsmap:v:318:y:2003:i:3:p:601-612
    DOI: 10.1016/S0378-4371(02)01731-4
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    References listed on IDEAS

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    1. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
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    Cited by:

    1. Marr, Carsten & Hütt, Marc-Thorsten, 2005. "Topology regulates pattern formation capacity of binary cellular automata on graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 641-662.
    2. Xu, Xiu-Lian & Shi, Jin-Xuan & Wang, Jun & Li, Wenfei, 2021. "Long-range correlation and critical fluctuations in coevolution networks of protein sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    3. Tanizawa, Toshihiro & Nakamura, Tomomichi & Taya, Fumihiko & Small, Michael, 2018. "Constructing directed networks from multivariate time series using linear modelling technique," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 437-455.
    4. Hütt, M.-Th. & Lüttge, U., 2005. "The interplay of synchronization and fluctuations reveals connectivity levels in networks of nonlinear oscillators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 207-226.
    5. Masa Tsuchiya & Vincent Piras & Sangdun Choi & Shizuo Akira & Masaru Tomita & Alessandro Giuliani & Kumar Selvarajoo, 2009. "Emergent Genome-Wide Control in Wildtype and Genetically Mutated Lipopolysaccarides-Stimulated Macrophages," PLOS ONE, Public Library of Science, vol. 4(3), pages 1-13, March.
    6. Carvunis, Anne-Ruxandra & Latapy, Matthieu & Lesne, Annick & Magnien, Clémence & Pezard, Laurent, 2006. "Dynamics of three-state excitable units on Poisson vs. power-law random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 595-612.
    7. Brot, Hilla & Muchnik, Lev & Goldenberg, Jacob & Louzoun, Yoram, 2012. "Feedback between node and network dynamics can produce real-world network properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6645-6654.
    8. Tsuchiya, Masa & Selvarajoo, Kumar & Piras, Vincent & Tomita, Masaru & Giuliani, Alessandro, 2009. "Local and global responses in complex gene regulation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1738-1746.
    9. Nagarajan, Radhakrishnan & Upreti, Meenakshi & Govindan, R.B., 2007. "Qualitative assessment of cDNA microarray gene expression data using detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 503-510.
    10. Gerhardt, Günther J.L. & Lemke, Ney & Corso, Gilberto, 2006. "Network clustering coefficient approach to DNA sequence analysis," Chaos, Solitons & Fractals, Elsevier, vol. 28(4), pages 1037-1045.

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