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URL: http://www.biological-networks.org/p/outliers/
Proper Citation: DONE: Detection of Outlier NEurons (RRID:SCR_005299)
Description: Software that performs a morphology-based approach for the automatic identification of outlier neurons based on neuronal tree structures. This tool was used by Zawadzki et al. (2012), who reported on and its application to the NeuroMorpho database. For the analysis, each neuron is represented by a feature vector composed of 20 measurements, which are projected into lower dimensional space with PCA. Bivariate kernel density estimation is then used to obtain a probability distribution for cells. Cells with high probabilities are understood as archetypes, while those with the small probabilities are classified as outliers. Further details about the method and its application in other domains can be found in Costa et al. (2009) and Echtermeyer et al. (2011). This version requires Matlab (Mathworks Inc, Natick, USA) and allows the user to apply the workflow using a graphical user interface.
Abbreviations: DONE
Synonyms: Detection of Outlier NEurons
Resource Type: software resource, software application
Defining Citation: PMID:22615032
Keywords: neuron, feature-space, archetype, outlier, matlab, neuromorphometry, computational neuroscience
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