Dr Matloob Khushi postdoctoral researcher at Children’s Medical Research Institute has developed a new bioinformatics tool to improve the early detection of cancer.
Matcol is a bioinformatics tool which helps determine protein and DNA colocalisations visualised using fluorescence microscopy. Colocalization refers to the observation of the spatial overlap between two or more different fluorescent labels and their biological interaction.
Put simply, this process allows cancer researchers to see whether a protein of interest is in proximity to cancer marker proteins. Previously, most scientists used image analysis software to manually perform colocalization identification.
Yet the problem with manual colocalization quantification is that it’s subjective, prone to human error, and takes longer to perform.
Dr Khushi told the Daily Telegraph, “Single image analysis takes up many hours and scientists are required to study a large cohort of images.”
This pioneering development can replace manual colocalisation counting, and be applied to a wide range of biological areas including cancer detection.
"MatCol automates this quantification task and can quantify hundreds of images automatically within a few minutes,” Dr Khushi said.
With MatCol’s automation and more streamlined processing, scientists can identify cancer in its early stages—allowing for early medical intervention and the potential to save lives.