Expertise: Bioinformatics, Genomics, Machine Learning
Tools: Python, R, Machine Learning
I am a Ph.D. student in Gong lab. I am interested in cancer genomics, including the mining of genetic risk determinants in cancer, functional prediction of genetic variants, tumor-associated molecular epidemiology, large-scale data integration, analysis, and mining, as well as the construction of bioinformatical data platforms.
Teams: EU-Openscreen
Organizations: Fraunhofer Institute for Translational Medicine and Pharmacology ITMP

Expertise: Bioinformatics, Cheminformatics, Machine Learning
Tools: Workflows
Teams: Applied Computational Biology at IEG/HMGU
Organizations: Helmholtz Zentrum München

Expertise: Software Engineering, Machine Learning, AI
Tools: Java, Jupyter notebook, Web services, Python
Expertise: Bioinformatics, Computer Science, Data Management, Genetics, Genomics, Machine Learning, Metagenomics, NGS, Scientific workflow developement, Software Engineering
Tools: Databases, Galaxy, Genomics, Jupyter notebook, Machine Learning, Nextflow, nf-core, PCR, Perl, Python, R, rtPCR, Snakemake, Transcriptomics, Virology, Web, Web services, Workflows
Dad, husband and PhD. Scientist, technologist and engineer. Bibliophile. Philomath. Passionate about science, medicine, research, computing and all things geeky!
Teams: Bioinformatics Innovation Lab
Organizations: Pondicherry University

Expertise: Bioinformatics, Systems Biology, Machine Learning
Tools: Galaxy, Cytoscape, Databases, Jupyter notebook, R, Python
Ph.D. Student at Department of Bioinformatics, Pondicherry University
Teams: MAB - ATGC
Organizations: Centre National de la Recherche Scientifique (CNRS)

Expertise: Bioinformatics, Genomics, algorithm, Machine Learning, Metagenomics, NGS, Computer Science
Tools: Transcriptomics, Genomics, Python, C/C++, Web services, Workflows
Teams: GalaxyProject SARS-CoV-2, nf-core viralrecon, EOSC-Life - Demonstrator 7: Rare Diseases, iPC: individualizedPaediatricCure, EJPRD WP13 case-studies workflows, TransBioNet, OpenEBench, ELIXIR Proteomics
Organizations: Barcelona Supercomputing Center (BSC-CNS), ELIXIR

Expertise: Bioinformatics, Computer Science, AI, Machine Learning
Computer Engineer in Barcelona Supercomputing Center (BSC)
Teams: Harkany Lab
Organizations: Medical University of Vienna

Expertise: Systems Biology, Bioengineering, Bioinformatics, Neuroscience
Tools: Workflows, Machine Learning, Transcriptomics
Research Director @ INRAe
Abstract (Expand)
Authors: Anna-Lena Lamprecht, Magnus Palmblad, Jon Ison, Veit Schwämmle, Mohammad Sadnan Al Manir, Ilkay Altintas, Christopher J. O. Baker, Ammar Ben Hadj Amor, Salvador Capella-Gutierrez, Paulos Charonyktakis, Michael R. Crusoe, Yolanda Gil, Carole Goble, Timothy J. Griffin, Paul Groth, Hans Ienasescu, Pratik Jagtap, Matúš Kalaš, Vedran Kasalica, Alireza Khanteymoori, Tobias Kuhn, Hailiang Mei, Hervé Ménager, Steffen Möller, Robin A. Richardson, Vincent Robert, Stian Soiland-Reyes, Robert Stevens, Szoke Szaniszlo, Suzan Verberne, Aswin Verhoeven, Katherine Wolstencroft
Date Published: 2021
Publication Type: Journal
DOI: 10.12688/f1000research.54159.1
Citation: F1000Res 10:897
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
...