New microscopy technique helps pictures tell a thousand words

A new imaging method combined with machine learning uncovers previously hidden information in micrographs of biological cells to reveal quantitative information of gene expression levels. Researchers from the University of Glasgow's James Watt School of Engineering and School of Computing Science describe in a paper published today how they have used image analysis and machine learning as a tool to directly determine the gene activity in single cells. For centuries, microscopy has been one of the most important tools to understand the structure and behaviour of biological cells. However, it has been limited to what is physically possible the see and has mostly been used to describe size, shape and structure. To understand the underlying gene expression activities, other techniques such as polymerase chain reaction required. Here the research groups used detailed image analysis to extract more than 1000 mathematical values describing each cell being analysed, generally called morphometric descriptors. Bringing these values together, it is possible to "teach" a computer the relationship between the morphometric values and the actual gene expression levels.