The initial step of creating effective therapeutic approaches is to understand the disease causing mechanism in detail, which involves acquiring and analyzing massive biological data. However, conventional human involved data analysis methods experience serious disadvantages when processing high-information content of biological image data, such as low throughput and potential user-introduced error and biases. The objective of this student-initiated proposal is to develop an automatic quantification algorithm to extract and analyze quantitative biological information related to endocytosis of membrane proteins to facilitate data analysis and reduce user-introduced errors. This team has been active from September 1, 2015 - current.

A presentation of this project is avaliable here.