Georgios Baskozos

My main research interest lies in the bioinformatics of neuropathic pain including genetics, transcriptomics, functional genomics and predictive modelling. I have a particular interest in the transcriptional analysis of peripheral nerve injury both in humans and animal models of pain and I have developed a customised computational pipeline for the identification of novel long non-coding RNAs and gene model reconstruction using RNA-sequencing.

In addition, I have extensive experience in designing and implementing computational workflows for the analysis of Whole Genome and Exome Sequencing data working closely with experimental biologists and medical doctors.

I have also a keen interest in data analysis of large scale clinical datasets with heterogenous variables using exploratory data analysis, statistical learning and predictive modelling techniques. I am currently applying machine learning methods and developing computational workflows as the only directly appointed researcher for the Diabetes UK Project Grant 19/0005984 “Using machine learning to predict painful diabetic neuropathy”. I am also funded as a researcher co-investigator at the "Partnership for Assessment and Investigation of Neuropathic Pain: Studies Tracking Outcomes, Risks and Mechanisms (PAINSTORM)" UKRI - Versus Arthritis APDP grant.

Finally, I support my colleagues, being part of David Bennett’s group, with statistics, hypothesis testing and advice on experimental design.