Heba Sailem

King's College London, UK

Dr Sailem research is focused on understanding the interplay between genetic and phenotypic components underlying changes in tissue architecture. To achieve that she develops statistical and machine learning methodologies for analysing large biomedical datasets with a focus on cellular imaging and single cell data. In 2017, She has been awarded a Sir Henry Wellcome Research Fellowship to develop a knowledge-driven machine learning framework for characterising gene functions in different cell types. These methods revealed a potential role for olfactory receptors in epithelial colorectal cell organisation.

She did her PhD at the Institute of Cancer Research in London under the supervision of Prof Chris Bakal. While at the ICR she developed methods for integrating phenotypic data with gene expression, modelling of the relationship between cell signalling and its context, and modelling the dynamics of cell morphogenesis. In these studies, she discovered new links between cell shape and breast cancer progression.

She is also interested in data visualisation as an important tool for science communication. She devised PhenoPlot, one of the first tools that are specifically designed for visualising phenotypic data. This method facilitates the interpretation of high dimensional data by generating pictorial representations of cells based on hundreds to thousands of measurements.