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BMC BioinformaticsNeurosciencePeer-reviewed journal article

NeuronBridge: an intuitive web application for neuronal morphology search across large data sets

Jody ClementsiD, Cristian GoinaiD, Philip M. HubbardiD, Takashi KawaseiD, Donald J. OlbrisiD, Hideo OtsunaiD, Robert SvirskasiD, Konrad RokickiiD

PDFDOIPreprint

Abstract

Neuroscience research in Drosophila is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. In order to exploit this knowledge base, researchers target individual neurons and study their function. Therefore, vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM). However, creating a fly line for driving gene expression within a single neuron found in the EM connectome remains a challenge, as it typically requires identifying a pair of fly lines where only the neuron of interest is expressed in both. This task and other emerging scientific workflows require finding similar neurons across large data sets imaged using different modalities. Here, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large datasets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly GUI, data model, serverless cloud architecture, and massively parallel image search engine. NeuronBridge is openly accessible at http://neuronbridge.janelia.org/.

Citations
80
FWCI
13.99
Field percentile
top 1%

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