Emmanouela’s research will focus on two fields of biology that are interrelated but which have been traditionally difficult to integrate. “Both transcriptomics (which looks at the intermediate steps of gene regulation) and proteomics (which examines the cells based on specific markers) aim to understand the fundamental biological processes that govern cell function, regulation and state.” explains Emmanouela “In my project, I will integrate transcriptomics single cell RNA data with proteomics Mass Spectometry (CyTOF) data to gain a better understanding of cell heterogeneity. I will also develop a visualisation tool to help in the interpretation of these models.”
Dominic’s project will attempt to overcome some of the limitations of current microscopy methodology. Dominic explains “I will develop algorithms that can statistically quantify and describe cellular appearances utilising the latest machine learning, computer vision and signal processing techniques and technologies. I will develop approaches that allow better automation, visualisation and feedback from experiments, to better inform the researcher as they perform and automate their experiments.”
Emmanouela and Dominic (both part of the Radcliffe Department of Medicine) are no stranger to the MRC WIMM. Emmanouela joined our Institute in 2014, following an MSc in Applied Statistics and DPhil at the Ludwig Institute for Cancer Research, both at the University of Oxford. Dominic studied for a PhD in the field of molecular neuroscience at University College London. Dominic joined the MRC WIMM in 2013, after completing an MSc in Computer Science, and supported the Institute’s Wolfson Imaging Centre with image analysis and method development. Emmanouela and Dominic have been awarded a UKRI Rutherford Fund Fellowship and a UKRI Innovation Fellowship respectively, to develop their independent projects and support their career towards establishing their own groups.
They will be based at the MRC WIMM Centre for Computational Biology. The Centre brings together researchers using computational biology – from bioinformatics and mathematical modelling through to data visualisation and artificial intelligence – to understand complex biological systems and treat human disease.