@string{AS =    {Annals of Statistics}}
@string{BI =    {Bioinformatics}}
@string{CancRes={Cancer Research}}
@string{ClinCh ={Clinical Chemistry}}
@string{PSB =   {Pacific Symposium on Biocomputing}}
@string{EMBOR = {EMBO Reports}}
@string{FEBSL=  {FEBS Letters}}
@string{GB =    {Genome Biology}}
@string{GR =    {Genome Research}}
@string{IJC =   {International Journal of Cancer}}
@string{JB =    {Journal of Biology}}
@string{JC =    {Journal of Classification}}
@string{JCB =   {Journal of Computational Biology}}
@string{JMVA =  {Journal of Multivariate Analysis}}
@string{JSPI =  {Journal of Statistical Planning and Inference}}
@string{JASA=   {Journal of the American Statistical Association}}
@string{JCGS=   {Journal of Computational and Graphical Statistics}}
@string{JRSSB=	{Journal of the Royal Statistical Society, Series B}}
@string{MBC =   {Molecular Biology of the Cell}}
@string{MC =    {Molecular Cell}}
@string{ML =    {Machine Learning}}
@string{NAR =   {Nucleic Acids Res}}
@string{NCB =   {Nature Cell Biology}}
@string{NBT =   {Nature Biotechnology}}
@string{NG  =   {Nature Genetics}}
@string{PRL =   {Physical Review Letters}}
@string{PSB =   {Pacific Symposium on Biocomputing}}
@string{PNAS =  {Proc. Natl. Acad. Sci. of the U.S.A.}}
@string{SAGMB = {Statistical Applications in Genetics and Molecular Biology}}
@string{SM =    {Statistics in Medicine}}
@string{SN =    {Social Networks}}

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@Article{Krogan2006,
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  Volume =	 "21",
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  title =	 {Towards a proteome-scale map of the human
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  title =	 {Local dynamic modeling of global interactome
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  year =	 {2005},
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  year =	 "2006",
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  title =	 "The Boost Graph Library",
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@Article{Stelzl2005,
  author =	 "Stelzl, U and others",
  title =	 {A human protein-protein interaction network: a
                  resource for annotating the proteome},
  abstract =	 {Protein-protein interaction maps provide a valuable
                  framework for a better understanding of the
                  functional organization of the proteome. To detect
                  interacting pairs of human proteins systematically,
                  a protein matrix of 4456 baits and 5632 preys was
                  screened by automated yeast two-hybrid (Y2H)
                  interaction mating. We identified 3186 mostly novel
                  interactions among 1705 proteins, resulting in a
                  large, highly connected network. Independent
                  pull-down and co-immunoprecipitation assays
                  validated the overall quality of the Y2H
                  interactions. Using topological and GO criteria, a
                  scoring system was developed to define 911
                  high-confidence interactions among 401
                  proteins. Furthermore, the network was searched for
                  interactions linking uncharacterized gene products
                  and human disease proteins to regulatory cellular
                  pathways. Two novel Axin-1 interactions were
                  validated experimentally, characterizing ANP32A and
                  CRMP1 as modulators of Wnt signaling. Systematic
                  human protein interaction screens can lead to a more
                  comprehensive understanding of protein function and
                  cellular processes.},
  journal =	 "Cell",
  year =	 "2005",
  volume =	 "122",
  number =	 "6",
  pages =	 "957-968",
  doi =		 "10.1016/j.cell.2005.08.029"
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  author =	 "John Storey",
  title =	 "A direct approach to false discovery rates",
  journal =	 JRSSB,
  year =	 2002,
  volume =	 64,
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}

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  Author =	 "Stuart, Joshua M and others",
  Title =	 "{A gene-coexpression network for global discovery of
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  Journal =	 "Science",
  Year =	 "2003",
  Volume =	 "302",
  Pages =	 "249--255"
}

@Article{StumpfPRE2005,
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  Title =	 "{{S}ampling properties of random graphs: the degree
                  distribution}",
  Journal =	 "Phys Rev E Stat Nonlin Soft Matter Phys",
  Year =	 "2005",
  Volume =	 "72",
  Pages =	 "036118"
}

@article{Tong2002,
  author =	 {Tong, Amy Hin Yan and others},
  title =	 {A combined experimental and computational strategy
                  to define protein interaction networks for peptide
                  recognition modules},
  journal =	 {Science},
  year =	 {2002},
  pages =	 {321--324}
}

@Article{TongScience2004,
  Author =	 "Tong, Amy Hin Yan and others",
  Title =	 "{Global mapping of the yeast genetic interaction
                  network}",
  Journal =	 "Science",
  Year =	 "2004",
  Volume =	 "303",
  Pages =	 "808--813"
}

@Article{Uetz2000,
  author =	 {Uetz, Peter and others},
  title =	 {A comprehensive analysis of protein-protein
                  interactions in \textit{{S}accharomyces cerevisiae}},
  journal =	 {Nature},
  year =	 {2000},
  volume =	 {403},
  pages =	 {623-627}
}

@Article{UetzReview2002,
  Author =	 "Uetz, Peter",
  Title =	 "{Two-hybrid arrays}",
  Journal =	 "Curr Opin Chem Biol",
  Year =	 "2002",
  Volume =	 "6",
  Pages =	 "57--62"
}

@Article{WiufPNAS2006,
  Author =	 "Wiuf, Carsten and others",
  Title =	 "{A likelihood approach to analysis of network data}",
  Journal =	 PNAS,
  Year =	 "2006",
  Volume =	 "103",
  Pages =	 "7566--7570",
  annote =	 "Wacko"
}

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  title =	 {A novel genetic system to detect protein-protein
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@Article{Yu:2006,
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  title =	 {Predicting interactions in protein networks by
                  completing defective cliques},
  journal =	 "Bioinformatics",
  year =	 "2006",
  volume =	 "22",
  number =	 "7",
  pages =	 "823-829",
}

@article{Zhao2005,
  title =	 {Navigating the Chaperone Network: An integrative map
                  of physical and genetic interactions mediated by the
                  {H}sp90 chaperone},
  author =	 {R. Zhao and others},
  journal =	 {Cell},
  year =	 {2005},
  volume =	 {120},
  pages =	 {715--727}
}

@Article{deSilvaStumpf2005,
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  Title =	 "{Complex networks and simple models in biology}",
  Journal =	 "J R Soc Interface",
  Year =	 "2005",
  Volume =	 "2",
  Pages =	 "419--430",
  annote =	 "Trivial"
}

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  author =	 {S. Falcon and R. Gentleman},
  title =	 {Using GOstats to test gene lists for GO term
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  journal =	 {Bioinformatics},
  year =	 {2006},
  Volume =       {2},
  pages =	 {257--258}
}

@article{hart2006,
  author =	 {"Hart, G Traver" and "Ramani, Arun K" and "Marcotte,
                  Edward M"},
  title =	 {How Complete Are Current Yeast and Human
                  Protein-Interactions Networks},
  journal =	 {Genome Biology},
  year =	 {2006},
}

@webpage{sgd,
  title =       {"Saccharomyces Genome Database"},
  url =	 {"http://www.yeastgenome.org"}
}

@Article{vonMering2002,
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  Pages =	 "399--403"
}


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   Year="2000",
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   Pages="287--292"
}

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@book{Stanley,
  author =	 "Stanley, R P",
  title =	 "Enumerative Combinatorics I",
  publisher =	 "Cambridge University Press",
  address =	 {New York},
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}