ArticleBrain informatics2020
An open-source framework for neuroscience metadata management applied to digital reconstructions of neuronal morphology.
Article in Brain informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed, 21 citations in OpenAlex.
- Connectivity of single neurons classifies cell subtypes in mouse brains.Nature methods · 2025Article
- Accelerating the continuous community sharing of digital neuromorphology data.FASEB bioAdvances · 2024Article
- Online conversion of reconstructed neural morphologies into standardized SWC format.Nature communications · 2023Article
- Automatic identification of scientific publications describing digital reconstructions of neural morphology.Brain informatics · 2023Article
- Neuronal Connectivity as a Determinant of Cell Types and Subtypes.Research square · 2023Article
- Automatic identification of scientific publications describing digital reconstructions of neural morphology.bioRxiv : the preprint server for biology · 2023Article
- Machine learning classification reveals robust morphometric biomarker of glial and neuronal arbors.Journal of neuroscience research · 2023Article
- Assisted neuroscience knowledge extraction via machine learning applied to neural reconstruction metadata on NeuroMorpho.Org.Brain informatics · 2022Article
- Petabyte-Scale Multi-Morphometry of Single Neurons for Whole Brains.Neuroinformatics · 2022Article
- Efficient metadata mining of web-accessible neural morphologies.Progress in biophysics and molecular biology · 2022Article
- Exploring highly reliable substructures in auto-reconstructions of a neuron.Brain informatics · 2021Article
- Highlights from the Era of Open Source Web-Based Tools.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Research advancements in neuroscience entail the production of a substantial amount of data requiring interpretation, analysis, and integration. The complexity and diversity of neuroscience data necessitate the development of specialized databases and associated standards and protocols. NeuroMorpho.Org is an online repository of over one hundred thousand digitally reconstructed neurons and glia shared by hundreds of laboratories worldwide. Every entry of this public resource is associated with essential metadata describing animal species, anatomical region, cell type, experimental condition, and additional information relevant to contextualize the morphological content. Until recently, the lack of a user-friendly, structured metadata annotation system relying on standardized terminologies constituted a major hindrance in this effort, limiting the data release pace. Over the past 2 years, we have transitioned the original spreadsheet-based metadata annotation system of NeuroMorpho.Org to a custom-developed, robust, web-based framework for extracting, structuring, and managing neuroscience information. Here we release the metadata portal publicly and explain its functionality to enable usage by data contributors. This framework facilitates metadata annotation, improves terminology management, and accelerates data sharing. Moreover, its open-source development provides the opportunity of adapting and extending the code base to other related research projects with similar requirements. This metadata portal is a beneficial web companion to NeuroMorpho.Org which saves time, reduces errors, and aims to minimize the barrier for direct knowledge sharing by domain experts. The underlying framework can be progressively augmented with the integration of increasingly autonomous machine intelligence components.
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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.