Transcriptional Characterization of Glioma Neural Stem Cells Diva ...

5.10 Glioblastoma Pathway Construction Methods
Figure 5.7: Schematisation of a typical Cytoscape network look, with nodes and
edges representing proteins and the type of interaction between them, respectively.
The colour and shape of the nodes can be attributed to different characteristics of the
proteins, such as their family, enzymatic activity, post-translational modifications,
etc. The colour and shape of the edges can be attributed to the type of interactions
between proteins, such as activating, inhibiting, coenzymatic, etc. In this example
protein A and B interact to form a complex that activates protein D, also repressed
by protein C, that once active can go ahead and activate protein E.
A series of pre-defined "layouts" available in Cytoscape, i.e. algorithms that
automatically lay a network out by generating arrangements of nodes and
edges that either make it look a specific way, such as the circular, grid and
hierarchical layouts, or use the attribute information as a guide, such as the
attribute circle, degree sorted circle, force-directed, group attributes layouts.
For our purposes we used the edge-weighed force-directed layout, also known
as "biolayout" that, once generated, was manually re-adapted to obtain a best
fit for image generation. In order to graph the network, the edge-weighed
force-directed layout, or biolayout, uses an algorithm that minimises the en-
ergy of the model by starting with an initial layout, where the positions of the
nodes are randomly assigned. Then, in every iteration, the algorithm tries to
improve the layout according to the energy model using the first derivation of
the energy function to compute a direction and a distance for the movement
of each node. Since the graphs generated are large, the minimising algorithms
do not carry a high complexity per iteration value. The algorithm of Barnes
and Hut [42] is used in Cytoscape’s biolayout for this purpose.
The glioblastoma pathway was constructed manually by integrating the infor-
mation on nodes (genes) and edges (types of interactions between genes) from
a variety of glioblastoma pathways found in the literature with the purpose of
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