ArticleF1000Research2021
Developing open-source software for bioimage analysis: opportunities and challenges.
Article in F1000Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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.
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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
15 citing papers in PubMed.
- AI-based hardware and software tools in microscopy to boost research in immunology and virology.Frontiers in immunology · 2025Review
- Systematic data analysis pipeline for quantitative morphological cell phenotyping.Computational and structural biotechnology journal · 2024Review
- Deep learning-based image analysis identifies a DAT-negative subpopulation of dopaminergic neurons in the lateral Substantia nigra.Communications biology · 2023Article
- A biologist's guide to planning and performing quantitative bioimaging experiments.PLoS biology · 2023Article
- Article
- Predicting peritoneal recurrence in gastric cancer with serosal invasion using a pathomics nomogram.iScience · 2023Article
- Performant web-based interactive visualization tool for spatially-resolved transcriptomics experiments.Biological imaging · 2023Article
- Moving beyond the desktop: prospects for practical bioimage analysis via the web.Frontiers in bioinformatics · 2023Article
- Better research software tools to elevate the rate of scientific discovery or why we need to invest in research software engineering.Frontiers in bioinformatics · 2023Article
- Developing image analysis methods for digital pathology.The Journal of pathology · 2022Review
- Meeting in the Middle: Towards Successful Multidisciplinary Bioimage Analysis Collaboration.Frontiers in bioinformatics · 2022Article
- Estimation of Covid-19 lungs damage based on computer tomography images analysis.F1000Research · 2022Article
- A field guide to cultivating computational biology.PLoS biology · 2021Article
- The "Neuro-Glial-Vascular" Unit: The Role of Glia in Neurovascular Unit Formation and Dysfunction.Frontiers in cell and developmental biology · 2021Review
- Bioimage analysis workflows: community resources to navigate through a complex ecosystem.F1000Research · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Fast-paced innovations in imaging have resulted in single systems producing exponential amounts of data to be analyzed. Computational methods developed in computer science labs have proven to be crucial for analyzing these data in an unbiased and efficient manner, reaching a prominent role in most microscopy studies. Still, their use usually requires expertise in bioimage analysis, and their accessibility for life scientists has therefore become a bottleneck. Open-source software for bioimage analysis has developed to disseminate these computational methods to a wider audience, and to life scientists in particular. In recent years, the influence of many open-source tools has grown tremendously, helping tens of thousands of life scientists in the process. As creators of successful open-source bioimage analysis software, we here discuss the motivations that can initiate development of a new tool, the common challenges faced, and the characteristics required for achieving success.
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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.