Large-scale multiple sequence alignment visualization through gradient vector flow
By applying gradient vector flow analysis to the MSA data, it is possible to extract and visually emphasize conservations and other patterns that are relevant during the MSA exploration process. In contrast to the traditional visual representation of MSAs, which exploits color-coded tables, the proposed visual metaphor allows us to provide an overview of large MSAs as well as to highlight global patterns, outliers, and data distributions.
| Release Date: |
May, 2012 |
| Status: | |
| Availability: | |
| Data type: | |
| Techniques: | 2D |
| Software: | Installed |
| Technology: | C++, Python, Voreen |
| Platform: | Linux, Mac OSX, Windows |
| Requirements: | Windows, Linux, Mac OS X |
Project development
This work was supported through grants from the Excellence Center at Linkoping and Lund in Information Technology (ELLIIT), the Swedish Research Council (VR, grant 2011–4113), and the Swedish e-Science Research Centre (SeRC). The presented technique has been integrated into the Voreen volume rendering engine (www.voreen.org), which is an open source visualization framework.
Last updated on 9th November, 2016
