ArticleNeuron2016
NBLAST: Rapid, Sensitive Comparison of Neuronal Structure and Construction of Neuron Family Databases.
Article in Neuron, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 162 papers, 1 of them a synthesis that pooled it.
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Who cites it
162 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- From neurons to novelty: Circuit mechanisms shaping courtship evolution.Current opinion in neurobiology · 2025Review
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102 more citing papers are in PubMed but not listed here.
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5 authors.
Funding
Abstract
Neural circuit mapping is generating datasets of tens of thousands of labeled neurons. New computational tools are needed to search and organize these data. We present NBLAST, a sensitive and rapid algorithm, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry, decomposing neurons into short segments; matched segments are scored using a probabilistic scoring matrix defined by statistics of matches and non-matches. We validated NBLAST on a published dataset of 16,129 single Drosophila neurons. NBLAST can distinguish neuronal types down to the finest level (single identified neurons) without a priori information. Cluster analysis of extensively studied neuronal classes identified new types and unreported topographical features. Fully automated clustering organized the validation dataset into 1,052 clusters, many of which map onto previously described neuronal types. NBLAST supports additional query types, including searching neurons against transgene expression patterns. Finally, we show that NBLAST is effective with data from other invertebrates and zebrafish. VIDEO ABSTRACT.
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