ArticleFrontiers in neural circuits2019
DVID: Distributed Versioned Image-Oriented Dataservice.
Article in Frontiers in neural circuits, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A connectome and analysis of the adulteLife · 2020Pooled it
- Connectome quality converges predictably to reveal optimal stopping points during proofreading.bioRxiv : the preprint server for biology · 2026Article
- Article
- Sexual dimorphism in the complete connectome of thebioRxiv : the preprint server for biology · 2025Article
- PyReconstruct: A fully open-source, collaborative successor to Reconstruct.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- WASPSYN: A Challenge for Domain Adaptive Synapse Detection in Microwasp Brain Connectomes.IEEE transactions on medical imaging · 2024Article
- Connectome-driven neural inventory of a complete visual system.bioRxiv : the preprint server for biology · 2024Article
- Ten recommendations for organising bioimaging data for archival.F1000Research · 2023Article
- How innovations in methodology offer new prospects for volume electron microscopy.Journal of microscopy · 2022Review
- Article
- The Brain Observatory Storage Service and Database (BossDB): A Cloud-Native Approach for Petascale Neuroscience Discovery.Frontiers in neuroinformatics · 2022Article
- Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling.Frontiers in neural circuits · 2022Article
- An Integrated Toolkit for Extensible and Reproducible Neuroscience.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021Article
- Massive Data Management and Sharing Module for Connectome Reconstruction.Brain sciences · 2020Article
- Article
- Convolutional nets for reconstructing neural circuits from brain images acquired by serial section electron microscopy.Current opinion in neurobiology · 2019Review
- Analyzing Image Segmentation for Connectomics.Frontiers in neural circuits · 2018Article
- TDat: An Efficient Platform for Processing Petabyte-Scale Whole-Brain Volumetric Images.Frontiers in neural circuits · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Open-source software development has skyrocketed in part due to community tools like github.com, which allows publication of code as well as the ability to create branches and push accepted modifications back to the original repository. As the number and size of EM-based datasets increases, the connectomics community faces similar issues when we publish snapshot data corresponding to a publication. Ideally, there would be a mechanism where remote collaborators could modify branches of the data and then flexibly reintegrate results via moderated acceptance of changes. The DVID system provides a web-based connectomics API and the first steps toward such a distributed versioning approach to EM-based connectomics datasets. Through its use as the central data resource for Janelia's FlyEM team, we have integrated the concepts of distributed versioning into reconstruction workflows, allowing support for proofreader training and segmentation experiments through branched, versioned data. DVID also supports persistence to a variety of storage systems from high-speed local SSDs to cloud-based object stores, which allows its deployment on laptops as well as large servers. The tailoring of the backend storage to each type of connectomics data leads to efficient storage and fast queries. DVID is freely available as open-source software with an increasing number of supported storage options.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.