New Results
Understanding melanopsin using bayesian generative models – an Introduction
Benedikt V. Ehinger, Dennis Eickelbeck, Katharina Spoida, Stefan Herlitze, Peter König
doi: https://doi.org/10.1101/043273
Benedikt V. Ehinger
1Institute of Cognitive Science, University of Osnabrück, Albrechtstr. 28, 49076 Osnabrück, Germany
Dennis Eickelbeck
2Department of General Zoology and Neurobiology, ND7/31, Ruhr-University Bochum, Universitätsstr. 150, D-44780 Bochum, Germany
Katharina Spoida
2Department of General Zoology and Neurobiology, ND7/31, Ruhr-University Bochum, Universitätsstr. 150, D-44780 Bochum, Germany
Stefan Herlitze
2Department of General Zoology and Neurobiology, ND7/31, Ruhr-University Bochum, Universitätsstr. 150, D-44780 Bochum, Germany
Peter König
1Institute of Cognitive Science, University of Osnabrück, Albrechtstr. 28, 49076 Osnabrück, Germany
3Dept. of Neurophysiology and Pathophysiology, University Medical Center Hamburg Eppendorf, 20246 Hamburg, Germany
Article usage
Posted March 11, 2016.
Understanding melanopsin using bayesian generative models – an Introduction
Benedikt V. Ehinger, Dennis Eickelbeck, Katharina Spoida, Stefan Herlitze, Peter König
bioRxiv 043273; doi: https://doi.org/10.1101/043273
Subject Area
Subject Areas
- Biochemistry (11569)
- Bioengineering (8622)
- Bioinformatics (28866)
- Biophysics (14803)
- Cancer Biology (11940)
- Cell Biology (17169)
- Clinical Trials (138)
- Developmental Biology (9302)
- Ecology (14019)
- Epidemiology (2067)
- Evolutionary Biology (18128)
- Genetics (12145)
- Genomics (16615)
- Immunology (11706)
- Microbiology (27691)
- Molecular Biology (11386)
- Neuroscience (60095)
- Paleontology (447)
- Pathology (1847)
- Pharmacology and Toxicology (3183)
- Physiology (4878)
- Plant Biology (10277)
- Synthetic Biology (2849)
- Systems Biology (7289)
- Zoology (1619)