Year: 2023
Type: article
Abstract: As biological imaging continues to rapidly advance, it results in increasingly complex image data, necessitating a reevaluation of conventional bioimage analysis methods and their accessibility. This perspective underscores our belief that a transition from desktop-based tools to web-based bioimage analysis could unlock immense opportunities for improved accessibility, enhanced collaboration, and streamlined workflows. We outline the potential benefits, such as reduced local computational demands and solutions to common challenges, including software installation issues and limited reproducibility. Furthermore, we explore the present state of web-based tools, hurdles in implementation, and the significance of collective involvement from the scientific community in driving this transition. In acknowledging the potential roadblocks and complexity of data management, we suggest a combined approach of selective prototyping and large-scale workflow application for optimal usage. Embracing web-based bioimage analysis could pave the way for the life sciences community to accelerate biological research, offering a robust platform for a more collaborative, efficient, and democratized science.
Source: Frontiers in Bioinformatics
Authors: Wei Ouyang, Kevin W. Eliceiri, Beth A. Cimini
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,125
Funders: Silicon Valley Community Foundation, Chan Zuckerberg Initiative, European Commission, Knut och Alice Wallenbergs Stiftelse, Science for Life Laboratory, National Institutes of Health, HORIZON EUROPE Framework Programme, National Institute of General Medical Sciences, HORIZON EUROPE Research Infrastructures
OpenAlex ID: W4385246338