2001), DIP ( Xenarios and Eisenberg 2001), or TRANSFAC ( Wingender et al. For molecular interactions, general-purpose graph viewers such as Pajek ( Batagelj and Mrvar 1998), Graphlet ( and daVinci ( are available to organize and display the data as a two-dimensional network specialized tools such as Osprey ( ) and PIMrider ( ) provide these capabilities and also link the network to molecular interaction and functional databases such as BIND ( Bader et al.
#CYTOSCAPE NODE LOCATIONS RELATION SOFTWARE#
Motivated by the explosion in experimental technologies for characterizing molecular interactions and states, researchers have turned to a variety of software tools to process and analyze the resulting large-scale data. High-throughput data pertaining to molecular interactions and states are well matched, in that both data types are global (providing information for all components or interactions in an organism) high-level (outlining relationships among pathway components without detailed information on reaction rates, binding constants, or diffusion coefficients) and coarse-grained (yielding qualitative data, such as the presence or absence of an interaction or the direction of an expression change, more readily than precise quantitative readouts). 2001) may be quantified with mass spectrometry, NMR, and other advanced techniques. 2001), and metabolite concentrations ( Griffin et al. 1999), protein phosphorylation state ( Zhou et al. 1997), whereas changes in protein abundance ( Gygi et al. For instance, global changes in gene expression are measured with DNA microarrays ( DeRisi et al. To complement these data, a second set of high-throughput methods are available to characterize the molecular and cellular states induced by pathway interactions under different experimental conditions. 2002), and genetic interactions ( Tong et al. First, recent technological developments have made it feasible to measure pathway structure systematically, using high-throughput screens for protein-protein ( Ito et al. However, pathway-specific models are now being supplemented with global data gathered for an entire cell or organism, by use of two complementary approaches. Typically, models are directed toward a cellular process or disease pathway of interest ( Gilman and Arkin 2002) and are built by formulating existing literature as a system of differential and/or stochastic equations. Such models promise to transform biological research by providing a framework to (1) systematically interrogate and experimentally verify knowledge of a pathway (2) manage the immense complexity of hundreds or potentially thousands of cellular components and interactions and (3) reveal emergent properties and unanticipated consequences of different pathway configurations. A variety of modeling environments have been developed to simulate biochemical reactions and gene transcription kinetics ( Endy and Brent 2001), cellular physiology ( Loew and Schaff 2001), and metabolic control ( Mendes 1997).
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.Ĭomputer-aided models of biological networks are a cornerstone of systems biology. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. 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. 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 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.
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