Research

Computational biology

Understanding biology using computational simulation and analysis

 

Our research groups address fundamental and applied questions in biology using big data approaches, and methods and tools from mathematics, statistics and computer science. Our research seeks to answer problems in a range of biological fields and applications, including:

  • crop genomics
  • environmental and evolutionary genomics
  • theoretical biology and ecology
  • animal and plant microbiomes
  • big data management, integration and interrogation

We use a range of computational methods and modelling to explore:

  • the evolution of resistance to biocides in weeds, pathogens and insects
  • genome structure and diversity
  • new approaches for breeding climate resilient and disease resistant crops
  • the maintenance of diversity in ecological communities
  • the design of biosecurity systems to help manage invasive species
  • coral and seagrass growth patterns and evolution
  • optimality and evolution of plant structure and function

Our methods include:

  • computational simulation modelling
  • genome sequencing, assembly and comparison
  • statistical modelling
  • applied bioinformatics
  • graph database development and application
  • applied deep learning

Courses

Key staff

For more information about our work and current projects, contact our key researchers:

 

Contact the School of Biological Sciences

CRICOS Code: 00126G
Updated
Friday, 9 November 2018 10:34 AM (this date excludes nested assets)
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Content ID
b7e400e5-0641-40cb-ac74-c48e71d2a74b