Algorithm Development

This research theme is concerned with developing innovative algorithms for analysing and integrating a variety of biochemical data as well as modelling relevant biological systems and networks to address challenging issues in systems and synthetic biology. We bring together ideas from diverse disciplines including computing, mathematics, and engineering to develop novel solutions to problems for which each individual discipline may have difficulties in dealing with. Examples of these algorithms include the analysis of high-throughput biological data such as DNA microarray and deep-sequencing and the construction of genetic, regulatory or biochemical networks.

Projects

  • The Integration of Multiple Data Sources for Building Robust Gene Regulatory Networks. PhD student: Valeria Bo, supervisor: Allan Tucker 
  • The Identification and Modelling of Key Stages in a Temporal Process.  PhD student: Stefano Ceccon, supervisor: Allan Tucker
  • The Exploitation of Cross-Sectional Studies to Infer Disease Processes. PhD student: Yuanxi Li, supervisor: Allan Tucker
  • Converging models for interspecies transcriptome studies of human diseases. PhD student Yahya Anvar, supervisor: Allan Tucker  (Co-Promoter with Leiden University Medical Centre, Netherlands)
  • Data Integrity and Intelligent Data Analysis Techniques Applied to a Glaucoma Progression Datase.  Research Fellow: Lucia Sacchi, supervisors: Allan Tucker and Stephen Swift 

Page last updated: Friday 24 January 2014