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Journal Abstract Search

119 related items for PubMed ID: 20866846

  • 41. A new framework for identifying combinatorial regulation of transcription factors: a case study of the yeast cell cycle.
    Wang J.
    J Biomed Inform; 2007 Dec; 40(6):707-25. PubMed ID: 17418646
    [Abstract] [Full Text] [Related]

  • 42. Boolean dynamics of genetic regulatory networks inferred from microarray time series data.
    Martin S, Zhang Z, Martino A, Faulon JL.
    Bioinformatics; 2007 Apr 01; 23(7):866-74. PubMed ID: 17267426
    [Abstract] [Full Text] [Related]

  • 43. Superstability of the yeast cell-cycle dynamics: ensuring causality in the presence of biochemical stochasticity.
    Braunewell S, Bornholdt S.
    J Theor Biol; 2007 Apr 21; 245(4):638-43. PubMed ID: 17204290
    [Abstract] [Full Text] [Related]

  • 44. Deconstruction and dynamical robustness of regulatory networks: application to the yeast cell cycle networks.
    Goles E, Montalva M, Ruz GA.
    Bull Math Biol; 2013 Jun 21; 75(6):939-66. PubMed ID: 23188157
    [Abstract] [Full Text] [Related]

  • 45. Closing mitosis: the functions of the Cdc14 phosphatase and its regulation.
    Stegmeier F, Amon A.
    Annu Rev Genet; 2004 Jun 21; 38():203-32. PubMed ID: 15568976
    [Abstract] [Full Text] [Related]

  • 46. Statistical inference of transcriptional module-based gene networks from time course gene expression profiles by using state space models.
    Hirose O, Yoshida R, Imoto S, Yamaguchi R, Higuchi T, Charnock-Jones DS, Print C, Miyano S.
    Bioinformatics; 2008 Apr 01; 24(7):932-42. PubMed ID: 18292116
    [Abstract] [Full Text] [Related]

  • 47. Modeling interactome: scale-free or geometric?
    Przulj N, Corneil DG, Jurisica I.
    Bioinformatics; 2004 Dec 12; 20(18):3508-15. PubMed ID: 15284103
    [Abstract] [Full Text] [Related]

  • 48. Mean-field Boolean network model of a signal transduction network.
    Kochi N, Matache MT.
    Biosystems; 2012 Dec 12; 108(1-3):14-27. PubMed ID: 22212351
    [Abstract] [Full Text] [Related]

  • 49. Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle.
    Gibbs DL, Shmulevich I.
    PLoS Comput Biol; 2017 Jun 12; 13(6):e1005591. PubMed ID: 28628618
    [Abstract] [Full Text] [Related]

  • 50. Random phenotypic variation of yeast (Saccharomyces cerevisiae) single-gene knockouts fits a double pareto-lognormal distribution.
    Graham JH, Robb DT, Poe AR.
    PLoS One; 2012 Jun 12; 7(11):e48964. PubMed ID: 23139826
    [Abstract] [Full Text] [Related]

  • 51. Binary threshold networks as a natural null model for biological networks.
    Rybarsch M, Bornholdt S.
    Phys Rev E Stat Nonlin Soft Matter Phys; 2012 Aug 12; 86(2 Pt 2):026114. PubMed ID: 23005832
    [Abstract] [Full Text] [Related]

  • 52. Mutual information in random Boolean models of regulatory networks.
    Ribeiro AS, Kauffman SA, Lloyd-Price J, Samuelsson B, Socolar JE.
    Phys Rev E Stat Nonlin Soft Matter Phys; 2008 Jan 12; 77(1 Pt 1):011901. PubMed ID: 18351870
    [Abstract] [Full Text] [Related]

  • 53. Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle.
    Fauré A, Naldi A, Chaouiya C, Thieffry D.
    Bioinformatics; 2006 Jul 15; 22(14):e124-31. PubMed ID: 16873462
    [Abstract] [Full Text] [Related]

  • 54. Stability of functions in Boolean models of gene regulatory networks.
    Rämö P, Kesseli J, Yli-Harja O.
    Chaos; 2005 Sep 15; 15(3):34101. PubMed ID: 16252995
    [Abstract] [Full Text] [Related]

  • 55. G1 and G2 arrests in response to osmotic shock are robust properties of the budding yeast cell cycle.
    Waltermann C, Floettmann M, Klipp E.
    Genome Inform; 2010 Sep 15; 24():204-17. PubMed ID: 22081601
    [Abstract] [Full Text] [Related]

  • 56. An Application of Invertibility of Boolean Control Networks to the Control of the Mammalian Cell Cycle.
    Zhang K, Zhang L, Mou S.
    IEEE/ACM Trans Comput Biol Bioinform; 2017 Sep 15; 14(1):225-229. PubMed ID: 26761860
    [Abstract] [Full Text] [Related]

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