- Article -
| In Silico Biology 7, 0014 (2007); ©2007, Bioinformation Systems e.V. |
DomainDraw: A macromolecular feature drawing program
J. Lynn Fink1, 2 and Nicholas Hamilton1, 2, 3*
1 ARC Centre in Bioinformatics, University of Queensland, St Lucia, Queensland, Australia 4072
2 Institute for Molecular Bioscience, University of Queensland St Lucia, Queensland, Australia 4072
3 Advanced Computational Modelling Centre, Department of Mathematics, University of Queensland St Lucia, Queensland, Australia 4072
* Corresponding author
Email: l.fink@imb.uq.edu.au, n.hamilton@imb.uq.edu.au
Edited by E. Wingender; received October 17, 2006; revised January 31, 2007; accepted February 01, 2007; published February 13, 2007
Abstract
Visualization of functional and structural features of biological macromolecules is an important aspect of communicating and analyzing biological data, for example the presence of a transmembrane domain in relation to a nucleotide binding site or the organization of transcription factor binding sites in a promoter. However, this is not necessarily a trivial task especially when the feature information is complex or lengthy. While there are some tools available that can create these images, none have been implemented for the specific purpose of automating the generation of presentation-quality graphics for displaying feature information. We have implemented DomainDraw, a visualization tool that can be used to generate schematic diagrams of biological macromolecules for the purpose of representing the relative position and range of user-specified domains or motifs. The user specifies the name, position, and range of the domains of interest and DomainDraw generates the image based on these parameters. Optional parameters include domain color and shape, image size, and whether to align multiple proteins using a particular domain. DomainDraw is publicly available as a web server and can be accessed at http://domaindraw.imb.uq.edu.au. The executable may be obtained by contacting the authors.
Keywords: visualization, functional genomics, high-throughput methods