@article{10.3389/fphys.2023.1076533,
  author = {Robert Court and Marta Costa and Clare Pilgrim and Gillian Millburn and Alex Holmes and Alex McLachlan and Aoife Larkin and Nicolas Matentzoglu and Huseyin Kir and Helen Parkinson and Nicolas H. Brown and Cahir J. O'Kane and J. Douglas Armstrong and Gregory S. X. E. Jefferis and David Osumi-Sutherland},
  title = "{Virtual Fly Brain—An interactive atlas of the Drosophila nervous system}",
  journal = {Frontiers in Physiology},
  volume = {14},
  publisher = {Frontiers Media {SA}},
  year = {2023},
  month = {jan},
  abstract = "{As a model organism, Drosophila is uniquely placed to contribute to our understanding of how brains control complex behavior. Not only does it have complex adaptive behaviors, but also a uniquely powerful genetic toolkit, increasingly complete dense connectomic maps of the central nervous system and a rapidly growing set of transcriptomic profiles of cell types. But this also poses a challenge: Given the massive amounts of available data, how are researchers to Find, Access, Integrate and Reuse (FAIR) relevant data in order to develop an integrated anatomical and molecular picture of circuits, inform hypothesis generation, and find reagents for experiments to test these hypotheses? The Virtual Fly Brain (virtualflybrain.org) web application & API provide a solution to this problem, using FAIR principles to integrate 3D images of neurons and brain regions, connectomics, transcriptomics and reagent expression data covering the whole CNS in both larva and adult. Users can search for neurons, neuroanatomy and reagents by name, location, or connectivity, via text search, clicking on 3D images, search-by-image, and queries by type (e.g., dopaminergic neuron) or properties (e.g., synaptic input in the antennal lobe). Returned results include cross-registered 3D images that can be explored in linked 2D and 3D browsers or downloaded under open licenses, and extensive descriptions of cell types and regions curated from the literature. These solutions are potentially extensible to cover similar atlasing and data integration challenges in vertebrates.}",
  issn = {1664-042X},
  doi = {https://doi.org/10.3389/fphys.2023.1076533},
  url = {https://doi.org/10.3389/fphys.2023.1076533},
}