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@MISC{libsbml,
  author = {Bornstein, Ben},
  title = {libsbml},
  year = {2006},
  owner = {larman},
  timestamp = {2006.10.12},
  url = {http://sbml.org/software/libsbml/}
}

@ARTICLE{graphviz,
  author = {Emden R. Gansner and Stephen C. North},
  title = {An open graph visualization system and its applications to software
	engineering},
  journal = {Software --- Practice and Experience},
  year = {2000},
  volume = {30},
  pages = {1203--1233},
  number = {11},
  url = {citeseer.ist.psu.edu/gansner99open.html}
}

@ARTICLE{sbml-layout,
  author = {Gauges, Ralph and Rost, Ursula and Sahle, Sven and Wegner, Katja},
  title = {{A model diagram layout extension for SBML}},
  journal = {Bioinformatics},
  year = {2006},
  volume = {22},
  pages = {1879-1885},
  number = {15},
  abstract = {Motivation: Since the knowledge about processes in living cells is
	increasing, modelling and simulation techniques are used to get new
	insights into these complex processes. During the last few years,
	the SBML file format has gained in popularity and support as a means
	of exchanging model data between the different modelling and simulation
	tools. In addition to specifying the model as a set of equations,
	many modern modelling tools allow the user to create and to interact
	with the model in the form of a reaction graph. Unfortunately, the
	SBML file format does not provide for the storage of this graph data
	along with the mathematical description of the model. Results: Therefore,
	we developed an extension to the SBML file format that makes it possible
	to store such layout information which describes position and size
	of objects in the graphical representation. Availability: The complete
	specification can be found on (http://projects.villa-bosch.de/bcb/sbml/
	(SBML Layout Extension documentation, 2005). Additionally, a complete
	implementation exists as part of libSBML (2006, http://www.sbml.org/software/libsbml/).
	Contact: Ralph.Gauges@eml-r.villa-bosch.de Supplementary information:
	Supplementary data are available on Bioinformatics online.},
  doi = {10.1093/bioinformatics/btl195},
  eprint = {http://bioinformatics.oxfordjournals.org/cgi/reprint/22/15/1879.pdf},
  url = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/22/15/1879}
}

@BOOK{bioconductor,
  title = {{Bioinformatics and computational biology solutions using R and bioconductor}},
  publisher = {Springer},
  year = {2005},
  author = {Gentleman, R. and Carey, V. and Huber, W. and Irizarry, R. and Dudoit,
	S.}
}

@ARTICLE{sbml,
  author = {Hucka, M. and Finney, A. and Sauro, H. M. and Bolouri, H. and Doyle,
	J. C. and Kitano, H. and and the rest of the SBML Forum: and Arkin,
	A. P. and Bornstein, B. J. and Bray, D. and Cornish-Bowden, A. and
	Cuellar, A. A. and Dronov, S. and Gilles, E. D. and Ginkel, M. and
	Gor, V. and Goryanin, I. I. and Hedley, W. J. and Hodgman, T. C.
	and Hofmeyr, J.-H. and Hunter, P. J. and Juty, N. S. and Kasberger,
	J. L. and Kremling, A. and Kummer, U. and Le Novere, N. and Loew,
	L. M. and Lucio, D. and Mendes, P. and Minch, E. and Mjolsness, E.
	D. and Nakayama, Y. and Nelson, M. R. and Nielsen, P. F. and Sakurada,
	T. and Schaff, J. C. and Shapiro, B. E. and Shimizu, T. S. and Spence,
	H. D. and Stelling, J. and Takahashi, K. and Tomita, M. and Wagner,
	J. and Wang, J.},
  title = {{The systems biology markup language (SBML): a medium for representation
	and exchange of biochemical network models}},
  journal = {Bioinformatics},
  year = {2003},
  volume = {19},
  pages = {524-531},
  number = {4},
  abstract = {Motivation: Molecular biotechnology now makes it possible to build
	elaborate systems models, but the systems biology community needs
	information standards if models are to be shared, evaluated and developed
	cooperatively. Results: We summarize the Systems Biology Markup Language
	(SBML) Level 1, a free, open, XML-based format for representing biochemical
	reaction networks. SBML is a software-independent language for describing
	models common to research in many areas of computational biology,
	including cell signaling pathways, metabolic pathways, gene regulation,
	and others. Availability: The specification of SBML Level 1 is freely
	available from http://www.sbml.org/ Contact: sysbio-team@caltech.edu},
  doi = {10.1093/bioinformatics/btg015},
  eprint = {http://bioinformatics.oxfordjournals.org/cgi/reprint/19/4/524.pdf},
  url = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/19/4/524}
}

@MISC{mathml,
  author = {Math{ML}},
  title = {Mathematical {M}arkup {L}anguage},
  year = {2006},
  owner = {larman},
  timestamp = {2006.10.12},
  url = {http://www.w3.org/Math/}
}

@ARTICLE{sbmlr,
  author = {Radivoyevitch, Tomas},
  title = {A two-way interface between limited Systems Biology Markup Language
	and {R}},
  journal = {BMC Bioinformatics},
  year = {2004},
  volume = {5},
  pages = {190},
  number = {1},
  abstract = {BACKGROUND:Systems Biology Markup Language (SBML) is gaining broad
	usage as a standard for representing dynamical systems as data structures.
	The open source statistical programming environment R is widely used
	by biostatisticians involved in microarray analyses. An interface
	between SBML and R does not exist, though one might be useful to
	R users interested in SBML, and SBML users interested in R.RESULTS:A
	model structure that parallels SBML to a limited degree is defined
	in R. An interface between this structure and SBML is provided through
	two function definitions: write.SBML() which maps this R model structure
	to SBML level 2, and read.SBML() which maps a limited range of SBML
	level 2 files back to R. A published model of purine metabolism is
	provided in this SBML-like format and used to test the interface.
	The model reproduces published time course responses before and after
	its mapping through SBML.CONCLUSIONS:List infrastructure preexisting
	in R makes it well-suited for manipulating SBML models. Further developments
	of this SBML-R interface seem to be warranted.},
  doi = {10.1186/1471-2105-5-190},
  issn = {1471-2105},
  pubmedid = {15585059},
  url = {http://www.biomedcentral.com/1471-2105/5/190}
}

@ARTICLE{cytoscape,
  author = {Shannon, Paul and Markiel, Andrew and Ozier, Owen and Baliga, Nitin
	S. and Wang, Jonathan T. and Ramage, Daniel and Amin, Nada and Schwikowski,
	Benno and Ideker, Trey},
  title = {{Cytoscape: A Software Environment for Integrated Models of Biomolecular
	Interaction Networks}},
  journal = {Genome Res.},
  year = {2003},
  volume = {13},
  pages = {2498-2504},
  number = {11},
  abstract = {Cytoscape is an open source software project for integrating biomolecular
	interaction networks with high-throughput expression data and other
	molecular states into a unified conceptual framework. Although applicable
	to any system of molecular components and interactions, Cytoscape
	is most powerful when used in conjunction with large databases of
	protein-protein, protein-DNA, and genetic interactions that are increasingly
	available for humans and model organisms. Cytoscape's software Core
	provides basic functionality to layout and query the network; to
	visually integrate the network with expression profiles, phenotypes,
	and other molecular states; and to link the network to databases
	of functional annotations. The Core is extensible through a straightforward
	plug-in architecture, allowing rapid development of additional computational
	analyses and features. Several case studies of Cytoscape plug-ins
	are surveyed, including a search for interaction pathways correlating
	with changes in gene expression, a study of protein complexes involved
	in cellular recovery to DNA damage, inference of a combined physical/functional
	interaction network for Halobacterium, and an interface to detailed
	stochastic/kinetic gene regulatory models.},
  doi = {10.1101/gr.1239303},
  eprint = {http://www.genome.org/cgi/reprint/13/11/2498.pdf},
  url = {http://www.genome.org/cgi/content/abstract/13/11/2498}
}

@ARTICLE{gaggle,
  author = {Shannon, Paul and Reiss, David and Bonneau, Richard and Baliga, Nitin},
  title = {The Gaggle: An open-source software system for integrating bioinformatics
	software and data sources},
  journal = {BMC Bioinformatics},
  year = {2006},
  volume = {7},
  pages = {176},
  number = {1},
  abstract = {BACKGROUND:Systems biologists work with many kinds of data, from many
	different sources, using a variety of software tools. Each of these
	tools typically excels at one type of analysis, such as of microarrays,
	of metabolic networks and of predicted protein structure. A crucial
	challenge is to combine the capabilities of these (and other forthcoming)
	data resources and tools to create a data exploration and analysis
	environment that does justice to the variety and complexity of systems
	biology data sets. A solution to this problem should recognize that
	data types, formats and software in this high throughput age of biology
	are constantly changing.RESULTS:In this paper we describe the Gaggle
	-a simple, open-source Java software environment that helps to solve
	the problem of software and database integration. Guided by the classic
	software engineering strategy of separation of concerns and a policy
	of semantic flexibility, it integrates existing popular programs
	and web resources into a user-friendly, easily-extended environment.We
	demonstrate that four simple data types (names, matrices, networks,
	and associative arrays) are sufficient to bring together diverse
	databases and software. We highlight some capabilities of the Gaggle
	with an exploration of Helicobacter pylori pathogenesis genes, in
	which we identify a putative ricin-like protein -a discovery made
	possible by simultaneous data exploration using a wide range of publicly
	available data and a variety of popular bioinformatics software tools.CONCLUSION:We
	have integrated diverse databases (for example, KEGG, BioCyc, String)
	and software (Cytoscape, DataMatrixViewer, R statistical environment,
	and TIGR Microarray Expression Viewer). Through this loose coupling
	of diverse software and databases the Gaggle enables simultaneous
	exploration of experimental data (mRNA and protein abundance, protein-protein
	and protein-DNA interactions), functional associations (operon, chromosomal
	proximity, phylogenetic pattern), metabolic pathways (KEGG) and Pubmed
	abstracts (STRING web resource), creating an exploratory environment
	useful to 'web browser and spreadsheet biologists', to statistically
	savvy computational biologists, and those in between. The Gaggle
	uses Java RMI and Java Web Start technologies and can be found at
	http://gaggle.systemsbiology.net.},
  doi = {10.1186/1471-2105-7-176},
  issn = {1471-2105},
  pubmedid = {16569235},
  url = {http://www.biomedcentral.com/1471-2105/7/176}
}

@BOOK{boost,
  title = {{The boost graph library: user guide and reference manual}},
  publisher = {Addison-Wesley},
  year = {2002},
  author = {Siek, J. and Lee, L.Q. and Lumsdaine, A.}
}

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