To provide tools for computational science that are
- easy to use, that is, well documented, have intuitive user interfaces with small learning curve.
- open access, that is, open source, open xml format, facilitating reproducibility of results, runs on many platforms.
- easy to extend, by having extensibility in design and small learning curve on the basic API.
Efficient testing of probabilistic hypotheses for sequence data analysis involving tree models.
To achieve the above, the following needs to be implemented:
- Data Format Standardisation & Validation Framework
- Class/Object to Data I/O mapping framework
- Common input language definition
- Document code/internals to enable auto-generation of API
- Implement auto-citation generator, methods section
- Refactor Core – sub/coa, related Junit test. One substitution model hierarchy, One coalescent likelihood et cetera
- multicoring/parallelisation – Investigate best approach (research)
- migrate to java 1.6
- general datatypes/sub models in BEAUTi
- implement plugin framework, associated doc for developer, and related test
- Implement “general” datatype in BEAST
- new datatypes – Microsatellites, SNPS
- better prior selection
- templates for standard analyses
- visualisations – geographical
- visualisations – posterior-prior
- visualisations – species-tree.
- BEAST book
- Unified IO Review
- Beauti and Beast common XML format, Simple XML format for end user,
- Unified Logic Layer – parameter object