2021
DOI: 10.12688/f1000research.52531.1
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Developing open-source software for bioimage analysis: opportunities and challenges

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 deve… Show more

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Cited by 28 publications
(28 citation statements)
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“…With the vast amount of experimental data, data analysis and computational expertise has become a limiting factor for many laboratories. Trained specialists and specialized data analysis training are needed to extract meaningful data in a high-throughput, standardized, and objective manner ( Levet et al, 2021 ). Dedicated specialized computational approaches can address this analytical bottleneck to analyze data, and push scientific boundaries by computationally modeling what is experimentally impossible.…”
Section: Future Directions and Areas Of Scientific Interestmentioning
confidence: 99%
“…With the vast amount of experimental data, data analysis and computational expertise has become a limiting factor for many laboratories. Trained specialists and specialized data analysis training are needed to extract meaningful data in a high-throughput, standardized, and objective manner ( Levet et al, 2021 ). Dedicated specialized computational approaches can address this analytical bottleneck to analyze data, and push scientific boundaries by computationally modeling what is experimentally impossible.…”
Section: Future Directions and Areas Of Scientific Interestmentioning
confidence: 99%
“…Bugs are inevitable in any sophisticated software, and researchers who share their code expose themselves to criticism-even retraction-if their software is shown not to do what is described in the paper [68]. But even if it works as described, making software open involves taking on a lot of additional work and responsibility [69,70]. Code intended for public consumption typically needs to be of a higher standard than in-house code; one cannot make simplifying assumptions (e.g.…”
Section: Complications Of Sharingmentioning
confidence: 99%
“…Appropriate software licenses should be chosen [71], which can involve securing agreement from a range of stakeholders with different priorities (including principal investigators, funders, innovation departments). Then, if the software has sufficient appeal and the authors desire to maximise its usefulness, the work is really only beginning: users require documentation and ongoing support, perhaps lasting far beyond the grant that originally funded the work [69].…”
Section: Complications Of Sharingmentioning
confidence: 99%
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“…Quality software development and maintenance is crucial for efficient and reproducible data analysis and is a key ingredient for successful computational biology projects [16]. Community-level software ecosystems and pipeline-building tools have outsized impact because Everyone receives bad reviews; most are unavoidable.…”
Section: Value Software As An Academic Productmentioning
confidence: 99%