A deep understanding of modern biology requires skills in the quantitative sciences

Advances in data acquisition, such as DNA sequencing, have changed how we address and investigate fundamental and applied biological questions.

We are now able to generate and analyse huge and complex datasets to tackle the challenges of the 21st century, including a growing and ageing population, biodiversity, biosecurity, food security, control of infectious agents, including new and emerging diseases, and the engineering of novel enzymes to be used industrially.

The ability to effectively analyse these datasets is of critical importance in understanding these complex processes and the mechanisms that underlie them.

Using bioinformatics to underpin research

Mathematics, statistics, and computational science provide the foundations for methods and bioinformatics tools that can be used to extract valuable knowledge from the data generated in modern bioscience.

Bioinformatics helps us improve our understanding of mechanistic and predictive biological processes and phenomena at the organism and systems level through the harnessing of data from transformative technologies in genomics, epigenomics, metagenomics, metabolomics/metabonomics, and proteomics. Bioinformatics also helps us to link  these types of data with important phenotypic traits such as crop yield and resistance to pathogens or pesticides.

We are developing and using bioinformatics tools to gain a better understanding of biological systems at the genomic and whole system level. When working with largely uncharacterised genomes and systems, informatics challenges are often encountered. This means we must develop new methods for analysing, managing, and visualising data.

Our bioinformatics teams work on these problems:

  • Genomics and genome assembly
  • Transcriptomics
  • Metagenomics and metatranscriptomics
  • Epigenomics
  • Comparative genomics
  • Sequence variant analysis
  • Phenomics
  • Proteomics
  • Statistical genetics
  • Biostatistics
  • Visualising biological data
  • Phylogenomics
  • Linking genomic data with remotely mapped environmental data
  • Linking genotypic traits to important phenotypic traits

Some of our bioinformatics software tools available for download include:

Case studies

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