Simon is an AI data scientist at NHS National Services Scotland, and also
a honorary lecturer in Computer Science, University of
His research interest involves the development of Machine Learning and Statistical techniques to
help with the analysis of complex datasets, particularly within the field of Metabolomics but also
other -omics fields, Human-Computer Interaction and Information Retrieval.
After his studies and PhD in Wageningen, the Netherlands, Justin moved to Glasgow
Polyomics to work with Dr. Karl Burgess and Prof. Mike Barrett and different partners from Glasgow
Polyomics. In 2015, Justin obtained an ISSF Fellowship from the Wellcome Trust to work on method
development and implementation of fragmentation approaches to enhance the metabolite annotation
capacities of the high-resolution LC-MS systems. He then focused on small polar metabolites in
urine, beer, and bacterial extracts thereby exploiting the information-rich fragmentation data that
modern mass spectrometers generate to alleviate the bottleneck of metabolite annotation and
identification in untargeted metabolomics approaches. He teamed up with Dr Simon Rogers and Dr Joe
Wandy to start the MS2LDA project in which he provides valuable biological data interpretations and
insights that is crucial to the development of the system. After taking up a shared Postdoc position
between the group of Dr Marnix Medema at WUR and the group of Prof. Pieter Dorrestein at the UCSD,
USA, in 2017, a year later, Justin obtained an eScience grant to develop tools that combine
workflows developed for genome and metabolome mining to aid in functional annotations of genes and
structural annotations of metabolites. Since January 2020, Justin obtained a position as an
Assistant Professor in Computational Metabolomics in the Bioinformatics Group in Wageningen. His
research vision is to close the gap between what we can see in metabolomics and what we can actually
learn from it. He will continue to implement and apply natural language processing algorithms to
perform metabolome mining and to seek the connection with genomics and genome mining. He will use
the plant root microbiome and human food metabolome as prime applications since they represent
complex metabolite mixtures full of yet unknown metabolic matter that once elucidated will boost our
insights in molecular mechanisms underpinning the regulation of growth, development, and health.
You can find his publications
Joe is a data scientist
at Glasgow Polyomics, University of Glasgow. Before
working at Glasgow Polyomics, Joe was a PhD student at the School of Computing Science, supervised by
His research interest is in natural language processing and the application of machine learning
methods to the analysis of complex biological data.
In particular, this also involves the necessary large-scale processing of data required prior to
modelling and also the effective visualisations of analysis results.
The following people have contributed codes, patches and new features to this project, and we would like to acknowledge their massive contributions. Without their help, this project would not be where it is now.