The CIBM is active in two broad areas of computational biology

  • Computer Aided Design methods for synthetic genome engineering
    We are developing algorithms that will allow in-silico design of complex organisms, ranging from human cells to plants.
    Dr Stracquadanio is a leading computational scientist in the field, and he has led the development of algorithms to engineer the first synthetic eukaryotic genome: the synthetic yeast.
  • Biological Network Analysis
    We are interested in developing algorithms to identify networks of genes that are associated with a disease phenotype. We are using our expertise in optimisation and statistical learning to develop algorithms that analyse high-throughput omic data and identify gene clusters associated with cancer.

Our research interests include but are not limited to:

  • Machine learning
  • Graph theory
  • Graph clustering
  • Computer Aided Design (CAD) methods
  • Statistical learning
  • High-throughput big data analysis
  • Evolutionary optimisation
  • Fuzzy logic
  • Synthetic biology software development
  • Efficient data structures for genomics


  • Network Analysis of the effect of hypoxia and nutrient deprivation on motility and metabolic switching of cancer cells.
    Wellcome Trust Seed Award in Science. PI: G. Stracquadanio (£99,776).

The Computational Intelligence Centre
University of Essex, Wivenhoe Park, Colchester CO4 3SQ, United Kingdom
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