Advanced Data Analysis for Image Based Spatial Proteomics
Proteins are the building blocks of human biology and targets for all pharmaceutical drugs. Proteomics is the study of proteins and how their different quantities in cells and tissues can lead to positive or negative effects in an organism. Spatial proteomics is a new and exciting method that allows scientists to build a ‘map’ of where these proteins are located and in what quantity in the tissues. Combining the techniques of microscopic imaging and mass spectrometry allows us to understand how cells interact with each other, adding a new dimension to understanding their function. New machines are generating vast quantities of data, but currently the methods for analysing and processing the data are slow and difficult to use, leading to a bottleneck.
Analysing these complex data sets quickly and accurately is critical, particularly in relation to new diseases like COVID-19, and requires an intuitive and automated analysis platform powered by advanced algorithms. In the same way that Google Maps has revolutionised how we understand and consume spatial information on earth, this test bed aims to develop an advanced platform that does the same for spatial proteomics.
PIs: Helen Byrne, Steve Taylor