Exocytotic vesicle fusion classification for early disease diagnosis using a mobile GPU microsystem
[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ 2 ] Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee | [ SzD ] doctoral school student
2022
scientific article
english
- GPU
- perceptron
- amperometry
- exocytosis
- vesicle fusion
- precancerous condition
EN This work addresses monitoring vesicle fusions occurring during the exocytosis process, which is the main way of intercellular communication. Certain vesicle behaviors may also indicate certain precancerous conditions in cells. For this purpose we designed a system able to detect two main types of exocytosis: a full fusion and a kiss-and-run fusion, based on data from multiple amperometric sensors at once. It uses many instances of small perceptron neural networks in a massively parallel manner and runs on Jetson TX2 platform, which uses a GPU for parallel processing. Based on performed benchmarking, approximately 140,000 sensors can be processed in real time within the sensor sampling period equal to 10 ms and an accuracy of 99%. The work includes an analysis of the system performance with varying neural network sizes, input data sizes, and sampling periods of fusion signals.
12.11.2021
4843 - 4854
CC BY (attribution alone)
czasopismo hybrydowe
final published version
in press
100
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