Bionow BioAI Summit

I am a Professor of bioinformatics, with particular interest in the development of new approaches and software for interpreting omics data. Broadly, the group is working in the following main areas at present.

Proteomics: My research group has built several packages for proteomics data analysis, many of which are released as open source, free software, and one of which is now sold commercially. I also have an interest in mechanisms for analysis and integration of multi-omics data (genomics, proteomics and metabolomics) - in particularly understanding the evolution and function of post-translational modifications (PTMs). My group has expertise around databases, data curation, knowledge management and data standards - for example I have a leading role in the Proteomics Standards Initiative. 

Analysis of multi-omics data for crops: We are developing approaches for integrating and analysing large-scale publicly available data on crops, particularly rice - including the use of proteogenomics, analysis of PTMs, and performing genome annotation.

Genomic databases and annotation: Our team contributes to genome annotation and data sharing for infectious disease resarch, via VEuPathDB and AFND

Application of machine learning: my research group is increasingly using machine learning (ML) for analysis of data from biological systems including humans/animals, eukaryotic pathogens and plants; we are also applying ML approaches for analysis of clinical data sets, in immunogenetics and cancer diagnosis.

As joint Director of the Computational Biology Facility, we are involved in a wide range of data science and software engineering projects with collaborators at the University of Liverpool, other research institutions and industry.

I am also interested in the development of teaching and training mechanism for coding and data science for students and staff.

Prof Frangi is the Bicentennial Turing Chair in Computational Medicine at the University of Manchester, Manchester, UK, with joint appointments at the Computer Science and Health Sciences Schools. He is a member of the Christabel Pankhurst Institute (www.pankhurst.manchester.ac.uk) on health technologies research and innovation. He is also the Royal Academy of Engineering Chair in Emerging Technologies, with a focus on Precision Computational Medicine for in silico trials of medical devices. He is an Alan Turing Institute Fellow. His research vision was recently awarded an ERC Advanced Grant from the European Research Council. He also leads the InSilicoUK Pro-Innovation Regulations Network (www.insilicouk.org).

Professor Frangi's primary research interests lie at the crossroads of medical image analysis and modelling, emphasising machine learning (phenomenological models) and computational physiology (mechanistic models). He is particularly interested in statistical methods applied to population imaging and in silico clinical trials. His highly interdisciplinary work has been translated into cardiovascular, musculoskeletal and neurosciences.