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Jrg Bernhardt; Henry Mehlan; Julia Schler; Michael Hecker (E.M.A.-University Greifswald, Institute for Microbiology; Jahnstrasse15;17487 Greifswald; Germany)
Established expression data analyses use clustering methods to find sets of similarly behaving mRNA or protein molecules. Subsequently these sets of co-expressed genes are matched with available information about their interactions and functions. This usually occurs manually by extensive literature studies or (semi-)automatically using tools for overrepresentation analyses within (quasi-)hierarchically structured gene functional classification systems. Current visualization methods are based on tree graphs or other directed acyclic graphs. However, hierarchically structured classification systems of bio-entities are ideal candidates for a space filling representation based on treemaps. We established and applied Voronoi treemaps to a variety of biologically related classification systems like Gene Ontology, EC Codes, KEGG Brite, and FunCat. In addition, we visualized peptide data from MassSpec analyses and phylogenetic trees. We present how OntologyMaps visualized relations between genes and regulators of Bacillus subtilis in a glucose starvation experiment and how OntologyMaps helped us getting an impression of the interplay of distinguished regulators in starving bacterial cells.http://www.nature.com/ncomms/journal/v1/n9/full/ncomms1137.html