We are proud to announce the release of VFB 2.0_beta1 designed in collaboration with MetaCell using the Geppetto open source platform. This release, available at https://v2.virtualflybrain.org, features:
VFB 2.0_beta1 does not have the full functionality of VFB 1.5. In particular queries of FlyBase annotations of expression and phenotypes are not yet integrated. We are currently working on tuning queries for these and plan to incorporate them into the next release, scheduled for the end of April.
We’re also very busy adding new data including:
- a new template for the larval CNS with painted domains and registered neurons
- re-imaged VT lines from Janelia
- split-GAL4 line images from FlyLight (Janelia)
- neuron reconstructions from EM data
We are very keen to get community feedback on this release – including bug reports, features requests or just general suggestions. Please use the feedback link on the new site or email us on email@example.com.
Please note that although new development is focussed on VFB 2.0, we will continue to maintain VFB 1.5 in parallel.
We are proud to announce a major new VFB release. This sees some very significant enhancements to the data we serve: we have now mapped ~50% of the >16,000 single neurons from FlyCircuit to published neuron classes; we now host almost 18,000 images of VT lines along with curation of where they are expressed.
An example of the detailed image data available for neuron classes can be see by querying for neurons with synaptic terminals in the protocerebral bridge and sorting on available images. 111 of the 137 neuron classes returned are illustrated by one or more single neuron images:
This particular data comes from combining NBLAST clusters (described in a recent paper from VFB’s Marta Costa and Greg Jefferis) and detailed curation of the paper from Ann-Shyn Chiang’s group ‘A comprehensive wiring diagram of the protocerebral bridge for visual information processing in the Drosophila brain.’
Any of these neuron images can be used to search for predicted GAL4 driver lines using NBLAST on the fly (video tutorial).
We are working on integrating NBLAST queries directly into VFB, so soon you’ll be able obtain lists of predicted driver lines directly from neuron classes.
We now have ~18,000 images of VT expression patterns. Registered data kindly donated by Barry Dickson (Janelia/IMP), Katja Buhler (VRVis) and colleagues was bridged from the original T1 template space to the JFRC2 template used on the VFB site.
The VT lines are indexed to gross neuropils (data from BrainBase), e.g.
They are also indexed to individual neurons (curated from the literature):
This release also includes many more minor enhancements and extensions to data via curation by VFB and FlyBase of anatomy, expression and phenotypes.
We are delighted to announce the official release of VFB 1.5. This
has already been available in beta for some time. It will become the
official version of VFB on Monday 15th Feb.
The new site features a new look and feel, a much improved image
browser and better integration of images into search results. Please
let us know what you think. Your feedback is essential to our
The main focus of development is now our new 3D browser (watch this
space for demos) and improvements to our data architecture to speed
up the site, extend queries and support new visualisation tools.
Data from http://virtualflybrain.org
Something we’re working on with geppettoengine for next year.
We’re looking for a web developer to help us build VFB 2.0. Please share with anyone you think may be interested. Details:
Are you interested in the challenge of designing web tools to provide accurate answers to biologically important questions couched in the language of biology? Are you interested in the challenges of communicating and interacting with 3D image data? Do you have an eye for web design?
Virtual Fly Brain are looking for a front end web developer to help redesign our site.
Virtual Fly Brain is a data integration hub for Drosophila neurobiology. We already integrate thousands of descriptions of neuroanatomy along with 10s of thousands of annotations of expression and 3D images of neuroanatomy. We have a clear semantic schema that provides the functionality our users need, and that runs from curation, through our OWL-based data models. Our new site must communicate these semantics clearly and elegantly whilst integrating an interactive 3D browser for images of neuroanatomy.
Details of the position, which is a combined post working with both VFB and The European Bank for induced pluripotent stem cells, are available on the EBI site.
We are proud to announce the addition of a triple stained adult Brain stack to VFB.
Earlier this year, Kei Ito and colleagues on the BrainName consortium published their long awaited new nomenclature for the insect Brain. VFB has followed the evolving BrainName nomenclature since its inception. We are now fully compliant with the published version and have added the gorgeous triple stained half brain shown in this paper to our hosted stacks. (The raw data for this stack is openly available on FlyBase (details and link here).
The detailed, painted mask on this stack includes major tracts such as the great commissure (blue, centre in the above image). We are working on adding a second mask with many more tracts marked. We are also planning to add linked thumbnails from term info to painted domains on both adult brain stacks.
In other news – usage of VFB continues to climb dramatically. We now get over 18,000 hits a month, with all of our many features getting significant usage.
We’re collecting user stories to assess dev priorities. Please contact us via our blog, or our community group firstname.lastname@example.org to let us know.
Feel free to include anything you’d like to use VFB for, not matter how technically difficult it may seem. Please let us know any frustrations you have with current functionality.
We are excited to announce a new release of VFB, featuring a full set of adult central brain lineage clone images and mapping data from Ito et al., 2013 & Yu et al., 2003 + fruitless expressing clones from Cachero and Ostrovsky et al., 2010. The mapping data we’ve added includes mapping to brain regions and mapping of single neurons and fru expressing lineage clones to complete central brain lineage clones. We’ve also added functionality for display of multiple images on our stack browser. In combination with new functionality allowing multiple registered images. The combination of these functionalities provides opportunities for querying and exploring lineage data that are unavailable from any other resource.
To search textually for clones, simply type ‘clone’ into the text search box on the front page or :
To query by region:
All clones from the Ito and Yu papers and most from Cachero come with linked thumbnail images.
Any of these thumbnails can be added to the stack browser:
You can layer up to 3 image stacks in a single browser view:
Images that can be added to the stack browser include > 16000 neurons from the FlyCircuit dataset. We plan to add downloads for many of our registered stacks in the near future.
Many thanks to Kei Ito & Tzumin Lee for providing us with data and mapping tables to make this release possible.
We hope you enjoy the new content and features. Please let us know what you think,
The VFB team.
We are happy to announce the integration of GAL4 line expression patterns from HHMI Janelia farm into VFB. Query results for transgene expression in any major neuropil now include results from the Rubin lab collection at Janelia farm.
Each result includes a thumbnail image linked to the appropriate page on the Janelia Farm FlyLight site and a link to the relevant transgene page on FlyBase where you can find molecular details, phenotypes and links to stocks.
For example, from the VFB page for nodulus, choose the transgene expression query from the menu, as shown below.
The results include 56 Janelia GAL4 lines.
In the near future, we plan to host full size, registered image stacks for most or all of these GAL4 lines as extra layers in our stack browser. This will allow users to compare multiple registered images on the same stack to look for regions of overlap.