ReviewFrontiers in bioinformatics2021
Singularity Containers Improve Reproducibility and Ease of Use in Computational Image Analysis Workflows.
Review in Frontiers in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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
6 citing papers in PubMed.
- Artificial intelligence for antimicrobial resistance: advancing reproducibility, interpretability, and clinical deployment.Briefings in bioinformatics · 2026Review
- Article
- Recommendations for the collection and annotation of biosamples for analysis of biomarkers in neurofibromatosis and schwannomatosis clinical trials.Clinical trials (London, England) · 2024Review
- Federated Analysis for Privacy-Preserving Data Sharing: A Technical and Legal Primer.Annual review of genomics and human genetics · 2023Review
- Light-sheets and smart microscopy, an exciting future is dawning.Communications biology · 2023Review
- Web-based processing of physiological noise in fMRI: addition of the PhysIO toolbox to CBRAIN.Frontiers in neuroinformatics · 2023Article
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.
Funding
Abstract
Reproducing computational workflows in image analysis and microscopy can be a daunting task due to different software versions and dependencies. This is especially true for users with little specific knowledge of scientific computation. To overcome these challenges, we introduce Singularity containers as a useful tool to run and share image analysis workflows among many users, even years later after establishing them. Unfortunately, containers are rarely used so far in the image analysis field. To address this lack of use, we provide a detailed step-by-step protocol to package a state-of-the-art segmentation algorithm into a container on a local Windows machine to run the container on a high-performance cluster computer.
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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.