
doi: 10.5281/zenodo.12187829 , 10.5281/zenodo.14268318 , 10.5281/zenodo.15096668 , 10.5281/zenodo.11185906 , 10.5281/zenodo.12191581 , 10.5281/zenodo.11264394 , 10.5281/zenodo.12190275 , 10.5281/zenodo.15050551 , 10.5281/zenodo.11243963 , 10.5281/zenodo.17456109 , 10.5281/zenodo.12760603 , 10.5281/zenodo.14514106 , 10.5281/zenodo.8108214 , 10.5281/zenodo.14761274 , 10.5281/zenodo.12191646 , 10.5281/zenodo.10700825 , 10.5281/zenodo.17192954 , 10.5281/zenodo.17776991 , 10.5281/zenodo.12804877 , 10.5281/zenodo.10927638 , 10.5281/zenodo.11640926 , 10.5281/zenodo.14763316 , 10.5281/zenodo.11243811 , 10.5281/zenodo.12188447 , 10.5281/zenodo.12745204 , 10.5281/zenodo.17250260 , 10.5281/zenodo.10727259 , 10.5281/zenodo.10926948 , 10.5281/zenodo.11387366 , 10.5281/zenodo.17815626 , 10.5281/zenodo.10908333 , 10.5281/zenodo.11264275 , 10.5281/zenodo.10680375 , 10.5281/zenodo.18174210 , 10.5281/zenodo.15095944 , 10.5281/zenodo.15096745 , 10.5281/zenodo.10688783 , 10.5281/zenodo.17194765 , 10.5281/zenodo.18403460
doi: 10.5281/zenodo.12187829 , 10.5281/zenodo.14268318 , 10.5281/zenodo.15096668 , 10.5281/zenodo.11185906 , 10.5281/zenodo.12191581 , 10.5281/zenodo.11264394 , 10.5281/zenodo.12190275 , 10.5281/zenodo.15050551 , 10.5281/zenodo.11243963 , 10.5281/zenodo.17456109 , 10.5281/zenodo.12760603 , 10.5281/zenodo.14514106 , 10.5281/zenodo.8108214 , 10.5281/zenodo.14761274 , 10.5281/zenodo.12191646 , 10.5281/zenodo.10700825 , 10.5281/zenodo.17192954 , 10.5281/zenodo.17776991 , 10.5281/zenodo.12804877 , 10.5281/zenodo.10927638 , 10.5281/zenodo.11640926 , 10.5281/zenodo.14763316 , 10.5281/zenodo.11243811 , 10.5281/zenodo.12188447 , 10.5281/zenodo.12745204 , 10.5281/zenodo.17250260 , 10.5281/zenodo.10727259 , 10.5281/zenodo.10926948 , 10.5281/zenodo.11387366 , 10.5281/zenodo.17815626 , 10.5281/zenodo.10908333 , 10.5281/zenodo.11264275 , 10.5281/zenodo.10680375 , 10.5281/zenodo.18174210 , 10.5281/zenodo.15095944 , 10.5281/zenodo.15096745 , 10.5281/zenodo.10688783 , 10.5281/zenodo.17194765 , 10.5281/zenodo.18403460
In the rapidly evolving field of bioimaging, the integration and orchestration of Findable, Accessible, Interoperable, and Reusable (FAIR) image analysis workflows remains a challenge. We introduce BIOMERO, a bridge connecting OMERO, a renowned bioimaging data management platform, FAIR workflows and high-performance computing (HPC) environments. BIOMERO, featuring our opensource Python library "OMERO Slurm Client", facilitates seamless execution of FAIR workflows, particularly for large datasets from High Content or High Throughput Screening. BIOMERO empowers researchers by eliminating the need for specialized knowledge, enabling scalable image processing directly from OMERO. BIOMERO notably supports the sharing and utilization of FAIR workflows between OMERO, Cytomine/BIAFLOWS, and other bioimaging communities. BIOMERO will promote the widespread adoption of FAIR workflows, emphasizing reusability, across the realm of bioimaging research. Its user-friendly interface will empower users, including those without technical expertise, to seamlessly apply these workflows to their datasets, democratizing the utilization of AI by the broader research community.
If you use this software, please cite it using the metadata from this file.
python, high-performance-computing, biomero, cytomine, omero, slurm, bioimaging, fair, biaflows, high-throughput-screening, high-content-screening, image-analysis
python, high-performance-computing, biomero, cytomine, omero, slurm, bioimaging, fair, biaflows, high-throughput-screening, high-content-screening, image-analysis
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
