biological network visualisation, including generating and parsing a user input form, calling the
relevant API to retrieve the interaction network for the genes provided in user input, and finally
using a graph visualisation framework to produce an SVG representation of the biological network.
An example of the type of graphs that can be produced by this library is displayed below.
Why gene interaction networks?
The bulk of the work in our cells is performed by proteins. These proteins work with each other in
dense interaction networks to carry out various biological functions. Major efforts have been made
over the last decade to map the interactions between all human proteins, resulting in databases
containing large protein interaction networks ( 20,000 proteins, 300,000 interactions). These
networks act as a useful scaffold for interpreting the results of large-scale biological experiments.
Often biologists perform experiments that test thousands of candidate proteins for their involvement in some process (e.g. proteins whose mutation is associated with drug resistance in cancer,
proteins that are associated with a particular disease). The end result of these experiments is
typically a small (10-500) list of ’hit’ proteins. Mapping these hits onto a protein interaction network can help biologists make sense of their experiments by revealing which of the hits interact
with each other.
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