NBLAST Fast, sensitive neuron similarity search

Neural circuit mapping efforts in model organisms are generating multi-terabyte datasets of 10,000s of labelled neurons. Such data demand new computational tools to search and organize neurons. We present a general, sensitive and rapid algorithm, NBLAST, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry and works by decomposing a query and target neuron into short segments; matched segment pairs are scored using a log-likelihood ratio scoring matrix empirically defined by the statistics of real matches and non-matches.

Find out more …

• Please use this website to explore why NBLAST might be helpful in your research and how it works.
• With NBLAST online you can query single neurons or fragments against large databases of single neurons (FlyCircuit) or Gal4 expression patterns (FlyLight).
• Power users can run NBLAST on their desktop using arbitrary data.
• We have used NBLAST to organise over 16,000 Drosophila neurons into structural clusters.
• Finally, watch some demo videos, read all out about in the paper, or contact us for help.