Computational Biology and Bioinformatics

Our groups in Computational Biology and Bioinformatics focus on developing computational strategies to study a variety of biological phenomena and data ranging from molecules and cells all the way to behaviour.

Most of our computational tools are based on machine learning with applications in neuroscience, biomedicine and synthetic biology

Faculty

Member Research interests
Douglas Armstrong Molecular neuroinformatics, network models, behavioural models.
Ian Simpson Computational Biology, Statistics and Machine-learning. Molecular control of neural development and function especially in cortical structures and in relation to cognition, learning and memory. Evolution and conservation of molecular regulatory processes. Analysis of high-throughput data-sets (genomic, meta-genomic, transcriptomic and proteomic).
Diego Oyarzun Control theory, systems and synthetic biology, machine learning, metabolic modelling
Ava Khamseh

Semi-parametric probabilistic modelling, targeted learning, causal inference and its applications to population biomedicine, cancer modelling, experimental molecular biology (genomics and transcriptomics)

Ajitha Rajan

My research is in the field of computational immunology and aims to comprehensively characterise T-Cell antigen presentation landscapes and deliver predictive models that will allow for comparative immunology within homosapiens and across species. Our computational models will open the door to answer questions about immunotherapy efficacy. We also use machine learning techniques to  predict overall survival and recurrence in cancer datasets, currently for Glioma, Renal and Oesophageal cancer. 

Andrea Weisse

Computational biology, systems and synthetic biology, antimicrobial resistance, infectious diseases, dynamic systems and network models, molecular and patient data.

Events

We have a very informal reading group and publications monitoring system. We meet every two-three weeks in the coffee area on level 1 at 10am, discuss recently published papers over coffee, and then move on to read in more detail one/ two selected papers (we work on a rota informally).

Joining the group

If you would like to join as a PhD student, please see information here:

Prospective Postgraduates

We also have a large MSc programme in bioinformatics.  For this, you should apply directly to the School for information: 

Information about the MSc programme

Occasionally we have openings for postdoctoral researchers. Please contact the individual lecturers directly about this.

Classes

As part of our MSc programme, we teach two classes in bioinformatics, namely:

Bioinformatics 1

Bioinformatics 2

Related research at the University of Edinburgh

Edinburgh has a very active research landscape in computational biology and bioinformatics, both within the School of Informatics and outside. Within Informatics, we have strong links with the Institute for Perception, Action and Behaviour (IPAB)  and the Laboratory for the Foundations of Computer Science (LFCS) .  We have very strong links with the School of Biological Sciences, the College of Medicine and Veterinary Medicine (particularly Neuroscience) and BioSS (bioinformatics, statistics). 

IPAB (Institute for Perception, Action and Behaviour)

LFCS (Laboratory for the Foundations of Computer Science)

Centre for Systems Biology at Edinburgh

School of Biological Sciences

Neuroscience

BioSS (Bioinformatics, Statistics)

Funding

We receive funding for our research from many sources, including:

Engineering and Physical Sciences Research Council

Microsoft Research 

European Commission FP7

Biotechnology and Biological Sciences Research Council

UCB Pharma