Quantification Platform for Touch Response of Zebrafish Larvae using Machine Learning

• Paper link: https://publikationen.bibliothek.kit.edu/1000140195

The functions of this code

• Quantification of the data collected by Touch-Response data acquisition platforms;
• Visualization of the quantification results.

This code is implemented by Python, and uses the following (parts) libraries:

• tensorflow-gpu==1.15.0
• torch=1.4.0
• scikit-learn==0.23.1
• scipy==1.6.0
• seaborn==0.12.2
• pyqt5-sip==4.19.18

How to use the repostory

• Install the environment according to environment.yml.

• Change the path of the data and the path to save the quantification results in config.py: QUANTIFY_DATA_PATH, and QUANTIFY_SAVE_PATH.

• DO the quantification by

  python quantification.py

• Visulization of the results can be done by ./QuantificationResults/FigureDraw.py

• Pattern analysis of the quantification reusults can be done by ./HTS/

In case of citing our work

@inproceedings{wang2021quantification,
  title={Quantification Platform for Touch Response of Zebrafish Larvae using Machine Learning},
  author={Wang, Yanke and Pylatiuk, Christian and Mikut, Ralf and Peravali, Ravindra and Reischl, Markus},
  booktitle={PROCEEDINGS 31. WORKSHOP COMPUTATIONAL INTELLIGENCE},
  volume={25},
  pages={37},
  year={2021}
}