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The accuracy of a smartphone app called GelApp, designed by A*STAR scientists to help analyze biomedical samples, has been greatly enhanced by the addition of a cutting-edge image processing algorithm.
GelApp was developed in 2015 by intern Jia-Zhi Sim under the supervision of Samuel Ken-En Gan and Hwee Kuan Lee at the A*STAR Bioinformatics Institute. The app analyzes and labels outputs from 'gel electrophoresis'—a common laboratory technique that separates and identifies molecules, such as DNA and proteins, by passing a sample through a gel under electric charge. Individual molecules move through at different speeds, so they separate out and create a pattern of bands across the surface. Gel band images are traditionally analyzed by eye and labeled by hand; the size of each band indicates which precise molecules are present, and highlights where genes are truncated or proteins are altered.
Band - Size - Subtler - Details - Time
"Eyeballing band size means that subtler details might be missed, not to mention the time demanded by the task," explains Gan. "While our first GelApp went a long way to enable automated analysis, there are still improvements to be made."
The A*STAR team and their collaborators in France wanted to improve GelApp's functional accuracy when faced with variations in experimental set-ups, cameras, lighting, reflections and blurring.
"We looked to...
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