Cerebral: a Cytoscape plugin for layout of and interaction with biological networks using subcellular localization annotation

Barsky, Aaron; Gardy, Jennifer L.; Hancock, Robert E. W.; Munzner, Tamara

doi:10.1093/bioinformatics/btm057

Cited by 160 publications

(148 citation statements)

References 10 publications

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“…The network consists of 309 genes, 162 TFs and 82 proteins, in which 2836 protein-DNA regulations and 301 protein-protein interactions are presented. The drawing is created using Cytoscape plugin Cerebral [86,87] and the subcellular compartment data is from the GO database. The directions of the regulations are omitted for simplicity.…”

Section: Resultsmentioning

confidence: 99%

Integrated cellular network of transcription regulations and protein-protein interactions

Wang

Chen

2010

BMC Syst Biol

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BackgroundWith the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway.ResultsIn this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated.ConclusionsWe successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology.

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Section: Resultsmentioning

confidence: 99%

Integrated cellular network of transcription regulations and protein-protein interactions

Wang

Chen

2010

BMC Syst Biol

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“…In the talk, I will analyze three more systems within this framework: Cerebral [3,4], Constellation [12,15], and Noack's LinLog energy model [16]. All three are examples of design motivated by explicit prior analysis of the use of space.…”

Section: Further Analysis Examplesmentioning

confidence: 99%

“…All three are examples of design motivated by explicit prior analysis of the use of space. The Cerebral system [3,4] features both multiple side by side views, and superimposed layers within each view. The network layout is designed to mimic the semantics of hand-drawn diagrams of biological networks.…”

Section: Further Analysis Examplesmentioning

confidence: 99%

Graph Drawing through the Lens of a Framework for Analyzing Visualization Methods

Munzner

2013

Graph Drawing

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Abstract. The visualization community has drawn heavily on the algorithmic and systems-building work that has appeared with the graph drawing literature, and in turn has been a fertile source of applications. In the spirit of further promoting the effective transfer of ideas between our two communities, I will discuss a framework for analyzing the design of visualization systems. I will then analyze a range of graph drawing techniques through this lens. In the early stages of a project, this sort of analysis may benefit algorithm developers who seek to identify open problems to attack. In later project stages, it could guide algorithm developers in characterizing how newly developed layout methods connect with the tasks and goals of target users in different application domains.

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“…The next step needed is the development of tools that incorporate graphical representations of the interactions with the wealth of annotation available from the protein interaction databases, NCBI, and others. Many plug-ins to Cytoscape have been reported to solve these issues [72][73][74][75][76][77][78]. We can also foresee that the "balls and edges" approach for displaying interactions is insufficient because it does not represent the dynamic and the structural aspect of the protein interactions.…”

Section: How Will the Protein Interaction Be Accessed?mentioning

confidence: 99%

Mapping the human protein interactome

Figeys

2008

Cell Res

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Interactions are the essence of all biomolecules because they cannot fulfill their roles without interacting with other molecules. Hence, mapping the interactions of biomolecules can be useful for understanding their roles and functions. Furthermore, the development of molecular based systems biology requires an understanding of the biomolecular interactions. In recent years, the mapping of protein-protein interactions in different species has been reported, but few reports have focused on the large-scale mapping of protein-protein interactions in human. Here, we review the developments in protein interaction mapping and we discuss issues and strategies for the mapping of the human protein interactome. The latest craze in science is systems biology. Scientists in different scientific fields, however, define and view "systems biology" in different ways. Systems biology, for example, can mean mathematical modeling of a system for accurate predictions of the behavior of the system. It can also mean the systematic application of different highthroughput approaches to gather information on the system and to combine different information spaces for a more comprehensible view of the biology at hand. To date, the best modeling and predictions have been on systems for which good biological information is available [1]. Hence, gathering information on the system is required to develop predictive models. Genomics has been the primary source of large-scale information on systems through genome sequencing, large-scale SNPs analyses, and gene expression studies. KeywordsThe success of genomics has snow-balled into other areas, such as the large-scale data gathering at the protein level (proteomics). One of the achievements of proteomics is the mapping of protein interactions (interactome; the ensemble of the protein interactions related to a proteome or a genome). We have seen a growing number of large-scale studies of the interactome (or part of) for different species including yeast [2][3][4][5][6][7] Should the human protein interactome be mapped?The first question can be easily answered and is reminiscent of early discussions about sequencing the human genome. Many scientists were doubtful that sequencing the human genome would be worth the effort. It is now clear that today's research in human diseases and biological processes benefits from the human genome project. We already have a glimpse of the potential outcomes of mapping the human interactome by looking at the yeast interactome. The importance of mapping the yeast interactome can be measured in different ways; however, the number of references to the original papers by Fields [22] (over 3 000 citations) for interaction mapping by Y2H; and Ho [4] (over 1 300 citations) and Gavin [6] (over 1 400 citations) for protein interaction mapping by mass spectrometry clearly npg Cell Research (2008) 18:716-724.

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Cerebral: a Cytoscape plugin for layout of and interaction with biological networks using subcellular localization annotation

Abstract: http://www.pathogenomics.ca/cerebral

Cited by 160 publications

References 10 publications

Integrated cellular network of transcription regulations and protein-protein interactions

Integrated cellular network of transcription regulations and protein-protein interactions

Graph Drawing through the Lens of a Framework for Analyzing Visualization Methods

Mapping the human protein interactome

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