The Computational Biology Core at the Stowers Institute assists investigators with the analysis of biological data. The group combines software development and technical skills with biological insights to help find answers in complex and massive data-sets. The bioinformatics experts in the core primarily work with high-throughput sequence data, ChIP data, and other expression-based datasets. In addition, they provide general statistical and numerical analysis as well as support for scientific software and databases.
The Computational Biology group uses a variety of software packages, both open-source and commercial. Below is a small sampling of the tools currently being used to process NGS data:
- Bowtie, Cufflinks, and Tophat are used for basic alignment and analysis.
- Trinity and Trans-ABySS are used for assembly of model organisms.
- R is used heavily for statistical analysis of our datasets.
- Matlab is used for statistical analysis.
Over the years, members of the Computational Biology group have developed a number of tools in-house that are useful to other researchers. For more information please visit the website of the Computational Biology group or contact:
Computational Biology Core