Transcriptional Regulatory Networks in Saccharomyces cerevisiae

One of the main goals of systems biology is reverse engineering network structures from experimental data. Using quantitative networks measures, biological processes can be characterized and understood on a systems level. This paper reviews the scientific literature on the transcriptional regulatory networks of Saccharomyces cerevisiae to discuss what kind of structures can be identified and what this means biologically. This discussion comprises network characteristics, network dynamics in biological processes, and robustness; an inherent emergent property of networks.

[1]  P. Bourgine,et al.  Topological and causal structure of the yeast transcriptional regulatory network , 2002, Nature Genetics.

[2]  Diogo M. Camacho,et al.  Systems Biology Strikes Gold , 2009, Cell.

[3]  Rafael Sanjuán,et al.  Mechanisms of genetic robustness in RNA viruses , 2006, EMBO reports.

[4]  S. Havlin,et al.  Scale-free networks are ultrasmall. , 2002, Physical review letters.

[5]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[6]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[7]  M. Elowitz,et al.  Reconstruction of genetic circuits , 2005, Nature.

[8]  Shuji Ishihara,et al.  Cross talking of network motifs in gene regulation that generates temporal pulses and spatial stripes , 2005, Genes to cells : devoted to molecular & cellular mechanisms.

[9]  J. Stark,et al.  Network motifs: structure does not determine function , 2006, BMC Genomics.

[10]  A. Barabasi,et al.  Lethality and centrality in protein networks , 2001, Nature.

[11]  Araceli M. Huerta,et al.  From specific gene regulation to genomic networks: a global analysis of transcriptional regulation in Escherichia coli. , 1998, BioEssays : news and reviews in molecular, cellular and developmental biology.

[12]  M. Gerstein,et al.  Genomic analysis of regulatory network dynamics reveals large topological changes , 2004, Nature.

[13]  Sharon L. Milgram,et al.  The Small World Problem , 1967 .

[14]  Hiroaki Kitano,et al.  Biological robustness , 2008, Nature Reviews Genetics.

[15]  Joshua E. S. Socolar,et al.  Global control of cell-cycle transcription by coupled CDK and network oscillators , 2008, Nature.

[16]  H. Kitano.  Systems Biology: A Brief Overview , 2002, Science.

[17]  S. Shen-Orr,et al.  Network motifs in the transcriptional regulation network of Escherichia coli , 2002, Nature Genetics.

[18]  D. Fell,et al.  The small world inside large metabolic networks , 2000, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[19]  Albert-László Barabási,et al.  Scale-Free Networks: A Decade and Beyond , 2009, Science.

[20]  J. Hopfield,et al.  From molecular to modular cell biology , 1999, Nature.

[21]  Martin Suter,et al.  Small World , 2002 .

[22]  H. Kitano.  Towards a theory of biological robustness , 2007, Molecular systems biology.

[23]  Jay D. Keasling,et al.  Metabolic engineering for drug discovery and development , 2003, Nature Reviews Drug Discovery.

[24]  Jianzhi Zhang,et al.  A Big World Inside Small-World Networks , 2009, PloS one.

[25]  Andrey Rzhetsky,et al.  Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome , 2001, Bioinform..

[26]  A. Barabasi,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[27]  Albert-László Barabási,et al.  Error and attack tolerance of complex networks , 2000, Nature.

[28]  S. Teichmann,et al.  Gene regulatory network growth by duplication , 2004, Nature Genetics.