Overview
Topic status: We're looking for students to study this topic.
Bioinformatics computing demands huge computing and memory resources, and becomes one of the main problems in computational bioinformatics. Investigating traditional sequential computing, parallel computing, cluster/distributed/cooperative computing and/or other computing approaches, the projects to be undertaken on this topic aim to develop architecture/frameworks, algorithms and scheduling strategies, dynamic memory management policies, implementation methods and/or web tools for complicated bioinformatics problems.
They would make the best use of the computing resources including memory and CPUs for improved computation efficiency and/or more complicated bioinformatics computing. In particular, the projects will consider the scenarios of building Composition Vector (CV) Trees for phylogenetic analysis using complete genenomes without sequence alignment. Preliminary studies have been carried out in our group and working c++ code is already available for stand-alone sequential computation of CV tree building.
- Study level
- PhD, Masters, Honours
- Supervisors
- QUT
- Organisational unit
Science and Engineering Faculty
- Research area
- Contact
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Please contact the supervisor.
Professor Glen Tian
