Figure 2.

Visualization of the most significant "down-regulated neighborhood" identified by GiGA using a GeneOntology-based network. The expression data are taken from the 20.5 h timepoint of the yeast diauxic shift (DeRisi et al., 1997). The layout was generated from the output of GiGA by the free software aiSee webcite using a force-directed algorithm with default parameters. The same software can also be used for the versatile real-time navigation of the network. Colored boxes show the regulated genes (darker shading indicates stronger regulation), white boxes show the evidence linking the genes (in this case GeneOntology numbers and terms). Several important components of this regulatory neighborhood are indicated (small and large ribosomal subunit proteins, rRNA processing/snRNP, nucleolar proteins, translation elongation factors). These components were also identified in the original publication after manual analysis. GiGA finds them automatically, and also detects the – biologically obvious – connections between them. As all the evidence is included in the same picture, the biologist can then use her expertise to assess the relevance of each link, without having to make the connections ad hoc by tedious literature studies.

Breitling et al. BMC Bioinformatics 2004 5:100   doi:10.1186/1471-2105-5-100
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