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).