The development of a drug against pathogens of hemorrhagic fever, like the Marburg virus, is a great challenge. Therefore, accurate knowledge of the properties of subviral particles in the host cell must be obtained. The base for subviral particle analysis is a special fluorescence microscopy technique. In order to automate and visualize the subviral particles’ motion patterns, previously a tracking algorithm was developed. In this article a new algorithm to parameterize and visualize the achieved particle tracks is introduced. A good potential for a fast data recognition is shown, with constantly respecting a high usability for pharmaceutical researchers. This algorithm was tested on both simulated and real data and provides reproducible results.
© 2018 the author(s), published by Walter de Gruyter Berlin/Boston
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.