New Results
A Bayesian framework for comparing the structure of spontaneous correlated activity recorded under different conditions
Catherine S Cutts, Stephen J Eglen
doi: https://doi.org/10.1101/037358
Catherine S Cutts
1Cambridge Computational Biology Institute Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge CB3 0WA, United Kingdom
Stephen J Eglen
1Cambridge Computational Biology Institute Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge CB3 0WA, United Kingdom
Article usage
Posted January 20, 2016.
A Bayesian framework for comparing the structure of spontaneous correlated activity recorded under different conditions
Catherine S Cutts, Stephen J Eglen
bioRxiv 037358; doi: https://doi.org/10.1101/037358
Subject Areas
- Biochemistry (11574)
- Bioengineering (8626)
- Bioinformatics (28876)
- Biophysics (14809)
- Cancer Biology (11945)
- Cell Biology (17175)
- Clinical Trials (138)
- Developmental Biology (9309)
- Ecology (14023)
- Epidemiology (2067)
- Evolutionary Biology (18130)
- Genetics (12148)
- Genomics (16621)
- Immunology (11712)
- Microbiology (27705)
- Molecular Biology (11402)
- Neuroscience (60109)
- Paleontology (448)
- Pathology (1849)
- Pharmacology and Toxicology (3185)
- Physiology (4878)
- Plant Biology (10279)
- Synthetic Biology (2850)
- Systems Biology (7291)
- Zoology (1619)