Dr Nick Furnham
in Computational Biology of Infectious Disease
Nicholas has expertise in computational biology, machine learning / AI, genomics and structural biology.
He joined the School as an independent investigator supported by a MRC Strategic Skill Fellowship in Methodology Research. Prior to this he was a staff scientist / post-doctoral research in the group of Prof. Dame Janet Thornton at the European Bioinformatics Institute (an outstation of the European Molecular Biology Laboratory). He completed his PhD under the supervision of Prof. Sir Tom Blundell in the Biochemistry Department at Cambridge University after a MSc. in Bioinformatics at Exeter University. His original undergraduate training in Biological Science, where he specialised in parasitology, was at King’s College London.
Nicholas runs the antimicrobial chemotherapy module that is open to several of the ITD faculty MSc programs. He also co-organises the Programming module (Python and R), one of the core modules of the Health Data Science MSc. run in the EPH faculty. Nicholas also contributes lectures and practical classes to several other MSc. modules including Pathogen Genomics, Molecular Biology and Recombinant DNA Techniques and Advanced Training in Molecular Biology.
In addition, he supervises research students and those interested in undertaking a PhD or MSc project should contact him directly.
Dr. Furnham’s research interest focus on the development and application of computational methods to important questions in infectious disease biology. Using an interdisciplinary approach combining biology and chemistry with computer science his group develops new algorithms and bioinformatics tools through large-scale integrative data processing. His research group is exploiting the latest developments in machine learning and artificial intelligence in projects addressing questions in antimicrobial resistance and the development of novel therapeutics.
The Furnham group leads several projects including:
- understand the molecular consequences of genomic variance through GWAS studies in surveillance and tracking of antimicrobial resistance;
- the development of novel therapeutics using a combination of structure led high-throughput fragment based screening with pharmacogenomics and high-content screening. This has been applied to developing new anti-schistosomal agents and was nominated for a Newton Prize;
- the development of a resource, FunTree (www.funtree.info), which brings together on a large-scale from thousands of genomes protein sequences, structures, taxonomy, phylogenetic analysis and comparisons of protein function.
Prior projects have included putting allergy into its evolutionary context by establishing molecular similarities between known allergens and proteins in multicellular parasites. We verified these predictions experimentally to show new proteins in parasitic worms that cause allergy like immune responses, demonstrating that allergy is the price we pay for evolving immunity to these parasites. This work has received interest in the wider media with reports in Science and the Smithsonian (amongst others).