Developing open-source software for bioimage analysis: opportunities and challenges [version 1; peer review: 2 approved]
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 m...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2021-04-01
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| Series: | F1000Research |
| Online Access: | https://f1000research.com/articles/10-302/v1 |
| _version_ | 1818742625500397568 |
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| author | Florian Levet Anne E. Carpenter Kevin W. Eliceiri Anna Kreshuk Peter Bankhead Robert Haase |
| author_facet | Florian Levet Anne E. Carpenter Kevin W. Eliceiri Anna Kreshuk Peter Bankhead Robert Haase |
| author_sort | Florian Levet |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-18T02:15:30Z |
| format | Article |
| id | doaj.art-20d7a60b0c774f80a4faa2418554647a |
| institution | Directory Open Access Journal |
| issn | 2046-1402 |
| language | English |
| last_indexed | 2024-12-18T02:15:30Z |
| publishDate | 2021-04-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | F1000Research |
| spelling | doaj.art-20d7a60b0c774f80a4faa2418554647a2022-12-21T21:24:23ZengF1000 Research LtdF1000Research2046-14022021-04-011010.12688/f1000research.52531.155826Developing open-source software for bioimage analysis: opportunities and challenges [version 1; peer review: 2 approved]Florian Levet0Anne E. Carpenter1Kevin W. Eliceiri2Anna Kreshuk3Peter Bankhead4Robert Haase5Univ. Bordeaux, CNRS, Interdisciplinary Institute for Neuroscience, IINS, UMR 5297, Bordeaux, 33000, FranceImaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USAMedical Physics and Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USAEuropean Molecular Biology Laboratory, Heidelberg, GermanyPathology, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UKDFG Cluster of Excellence “Physics of Life”, TU Dresden, Dresden, GermanyFast-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.https://f1000research.com/articles/10-302/v1 |
| spellingShingle | Florian Levet Anne E. Carpenter Kevin W. Eliceiri Anna Kreshuk Peter Bankhead Robert Haase Developing open-source software for bioimage analysis: opportunities and challenges [version 1; peer review: 2 approved] F1000Research |
| title | Developing open-source software for bioimage analysis: opportunities and challenges [version 1; peer review: 2 approved] |
| title_full | Developing open-source software for bioimage analysis: opportunities and challenges [version 1; peer review: 2 approved] |
| title_fullStr | Developing open-source software for bioimage analysis: opportunities and challenges [version 1; peer review: 2 approved] |
| title_full_unstemmed | Developing open-source software for bioimage analysis: opportunities and challenges [version 1; peer review: 2 approved] |
| title_short | Developing open-source software for bioimage analysis: opportunities and challenges [version 1; peer review: 2 approved] |
| title_sort | developing open source software for bioimage analysis opportunities and challenges version 1 peer review 2 approved |
| url | https://f1000research.com/articles/10-302/v1 |
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