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The sharing of primary data in the field of neuroscience has received considerable scrutiny from scientific societies and from science journals. Many see this as value added for science publishing that can enhance and inform secondary examination of data and results. Still others worry that data...
The computer-assisted three-dimensional reconstruction of neuronal morphology is becoming an increasingly popular technique to quantify the arborization patterns of dendrites and axons. The resulting digital files are suitable for comprehensive morphometric analyses as well as for building...
As public availability of gene expression profiling data increases, it is natural to ask how these data can be used by neuroscientists. Here we review the public availability of high-throughput expression data in neuroscience and how it has been reused, and tools that have been developed to...
We describe a method for classifying subjects based on functional magnetic-resonance (fMR) data, using a method combining a Bayesian-network classifier with inverse-tree structure (BNCIT), and ensemble learning. The central challenge is to generate a classifier from a small sample of...
This paper presents a new algorithm for extracting the centerlines of the axons from a 3D data stack collected by a confocal laser scanning microscope. Recovery of neuronal structures from such datasets is critical for quantitatively addressing a range of neurobiological questions such as the...
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