Temporal Phosphorylation in Response to Insulin Reveals Signaling Network Topology (from Sean Humphrey et al., Cell Metab. 2013 Jun 4; 17(6): 1009–1020.)
Data from the literature were used to construct a cell signaling network. Proteins identified in this study were annotated with their respective insulin-dependent phosphorylation sites. They are color coded according to the temporal patterns derived from unsupervised clustering (fuzzy c-means), shown at the right.
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In the field of proteomics and transcriptomics, 3 types of visualisation techniques are generally employed: one, where data is being explored (such as heat maps); second, where data is being explored with regards to available knowledge (such as Cerebral [47] — a tool which allows gene expression data to be overlaid on a network within a cellular morphology); finally, just exploring the available knowledge (as allowed by Cytoscape). Such tools are often integrated with pathway databases, or allow the input of models or networks in common formats, such as SBML or tab separated list of the connected nodes. Gehlenborg et al. (2010) [48] provide an extensive review of the available tools and techniques for visualisation in this domain.
Effective visualisations of models and datasets depicting post-translational modifications over time, present a challenge due to the increase in dimensionality. To address these challenges, we proposed a novel layout strategy termed ‘Minardo’ [49], drawing inspiration from the famous visualisation by Charles Joseph Minard, depicting Napoleon’s march through Russia in 1812–1813 [50]. Minard’s visualisation encodes 6 dimensions, including time, in a single graph.