ArticleAnnals of the New York Academy of Sciences2009
Specification of spatial relationships in directed graphs of cell signaling networks.
Article in Annals of the New York Academy of Sciences, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Regulation of ERK-MAPK signaling in human epidermis.BMC systems biology · 2015Article
- Network reconstruction based on proteomic data and prior knowledge of protein connectivity using graph theory.PloS one · 2015Article
- Perinatal asphyxia: current status and approaches towards neuroprotective strategies, with focus on sentinel proteins.Neurotoxicity research · 2011Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Graph theory provides a useful and powerful tool for the analysis of cellular signaling networks. Intracellular components such as cytoplasmic signaling proteins, transcription factors, and genes are connected by links, representing various types of chemical interactions that result in functional consequences. However, these graphs lack important information regarding the spatial distribution of cellular components. The ability of two cellular components to interact depends not only on their mutual chemical affinity but also on colocalization to the same subcellular region. Localization of components is often used as a regulatory mechanism to achieve specific effects in response to different receptor signals. Here we describe an approach for incorporating spatial distribution into graphs and for the development of mixed graphs where links are specified by mutual chemical affinity as well as colocalization. We suggest that such mixed graphs will provide more accurate descriptions of functional cellular networks and their regulatory capabilities and aid in the development of large-scale predictive models of cellular behavior.
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Registered trials
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