Bioimage analysis workflows: community resources to navigate through a complex ecosystem

Area of Science:

• Bioimage analysis
• Scientific workflows
• Computational biology

Background:

• Bioimage analysis workflows are crucial but face challenges with big data and remote work.
• The NEUBIAS community aims to organize information and actors in bioimage analysis.
• Sharing and reproducibility are key concerns in modern scientific research.

Purpose of the Study:

• To provide recommendations for finding, handling, and developing bioimage analysis workflows.
• To address challenges in running workflows in remote and cloud environments.
• To promote the adoption of FAIR principles for bioimage analysis workflows.

Main Methods:

• Opinion paper based on community experience and emerging trends.
• Discussion of challenges related to data storage, computing, and remote execution.
• Exploration of tools for cloud and High Performance Computing (HPC) execution.

Main Results:

• Local solutions are limiting due to big data and complex algorithms.
• Reproducibility and documentation are critical for workflow sharing.
• FAIR principles (Findable, Accessible, Interoperable, Reusable) are essential for open science.

Conclusions:

• Navigating the bioimage analysis workflow ecosystem requires strategic approaches.
• Cloud and HPC resources offer solutions for intensive analysis.
• Implementing FAIR principles enhances workflow usability and scientific reproducibility.