The members of the Applied Computational Biology group at the Institute of Experimental Genetics (IEG) at the Helmholtz Zentrum München (HMGU) cover a wide range of scientific disciplines, all possessing deep IT knowledge and experience and a strong command of the IT toolbox. As a team, we work at the interface between biology and applied computer sciences in our institute as well as in external collaborations.
Space: Independent Teams
SEEK ID: https://workflowhub.eu/projects/67
Public web page: https://www.helmholtz-muenchen.de/ieg/research/research-groups/applied-computational-biology
Organisms: No Organisms specified
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Team created: 8th Oct 2021
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Teams: Applied Computational Biology at IEG/HMGU
Organizations: Helmholtz Zentrum München
Teams: Applied Computational Biology at IEG/HMGU
Organizations: Helmholtz Zentrum München
https://orcid.org/0000-0003-4796-1661Expertise: Software Engineering, Machine Learning, AI
Tools: Java, Jupyter notebook, Web services, Python
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Web page: Not specified
Country: Germany
City: München
Web page: https://www.helmholtz-muenchen.de/en/helmholtz-zentrum-muenchen/index.html
ABR_Threshold_Detection
What is this?
This code can be used to automatically determine hearing thresholds from ABR hearing curves.
One of the following methods can be used for this purpose:
- neural network (NN) training,
- calibration of a self-supervised sound level regression (SLR) method
on given data sets with manually determined hearing thresholds.
Installation:
Run inside the src directory:
Installation as python package
pip install -e ./src (Installation as python
...
This notebook is about pre-processing the Auditory Brainstem Response (ABR) raw data files provided by Ingham et. al to create a data set for Deep Learning models.
The unprocessed ABR data files are available at Dryad.
Since the ABR raw data are available as zip-archives, these have to be unzipped and the extracted raw data files parsed so that the time ...