ArticleNeuron2022
Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis.
Article in Neuron, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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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.
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Who cites it
21 citing papers in PubMed.
- Rapid robust high-fidelity 3D neuronal extraction from multiview calcium imaging datasets.Nature methods · 2026Article
- Efficient and reproducible pipelines for spike sorting large-scale electrophysiology data.eLife · 2026Article
- Mouse sensorimotor cortex reflects complex kinematic details during reaching and grasping.eLife · 2026Article
- Bridging the neuro-AI chasm: a framework for scalable, contextually adaptive training resources in large-scale brain data science.Frontiers in psychology · 2026Article
- Spyglass: a framework for reproducible and shareable neuroscience research.bioRxiv : the preprint server for biology · 2025Article
- Optical Neuroimage Studio (OptiNiSt): Intuitive, scalable, extendable framework for optical neuroimage data analysis.PLoS computational biology · 2025Article
- Multiscale Cloud-Based Pipeline for Neuronal Electrophysiology Analysis and Visualization.bioRxiv : the preprint server for biology · 2024Article
- Review
- Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling and cloud-native open-source tools.Nature methods · 2024Article
- Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging.Nature methods · 2024Article
- Exploration biases forelimb reaching strategies.Cell reports · 2024Article
- Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools.bioRxiv : the preprint server for biology · 2024Article
- Editorial: On the Economics of Neuroscientific Data Sharing.Neuroinformatics · 2024Article
- Reproducible brain PET data analysis: easier said than done.Frontiers in neuroinformatics · 2024Article
- Article
- Face mask recognition system using CNN model.Neuroscience informatics · 2022Review
- Neuroscience data analysis in the cloud.Nature methods · 2022Article
- Light-weight electrophysiology hardware and software platform for cloud-based neural recording experiments.Journal of neural engineering · 2021Article
- Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders.PLoS computational biology · 2021Article
- Chronic, cortex-wide imaging of specific cell populations during behavior.Nature protocols · 2021Article
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Authors and funding
11 authors.
Funding
Abstract
A key aspect of neuroscience research is the development of powerful, general-purpose data analyses that process large datasets. Unfortunately, modern data analyses have a hidden dependence upon complex computing infrastructure (e.g., software and hardware), which acts as an unaddressed deterrent to analysis users. Although existing analyses are increasingly shared as open-source software, the infrastructure and knowledge needed to deploy these analyses efficiently still pose significant barriers to use. In this work, we develop Neuroscience Cloud Analysis As a Service (NeuroCAAS): a fully automated open-source analysis platform offering automatic infrastructure reproducibility for any data analysis. We show how NeuroCAAS supports the design of simpler, more powerful data analyses and that many popular data analysis tools offered through NeuroCAAS outperform counterparts on typical infrastructure. Pairing rigorous infrastructure management with cloud resources, NeuroCAAS dramatically accelerates the dissemination and use of new data analyses for neuroscientific discovery.
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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.