openBEB: open biological experiment browser for correlative measurements

Area of Science:

• Systems biology
• Bioinformatics
• Computational biology

Background:

• Developing new experimental methods is crucial for studying complex biological interaction networks.
• High-throughput approaches analyzing individual subjects, like single cells, are needed to minimize biological noise.
• Correlating multiple physical properties enhances data consistency in biological experiments.

Purpose of the Study:

• To present openBEB (open Biological Experiment Browser), a novel software framework designed for biological data management.
• To facilitate data acquisition, coordination, annotation, and synchronization with database solutions.
• To enable seamless integration of diverse experimental techniques for comprehensive biological analysis.

Main Methods:

• OpenBEB features a core program for data management and a plug-in manager for data-specific tasks.
• An open architecture allows rapid integration of plug-ins for various functions like data acquisition and visualization.
• A macro-interpreter facilitates automation and coordination of different software modules.

Main Results:

• OpenBEB provides a unified platform for managing raw data and metadata.
• The framework supports synchronization with database solutions like openBIS.
• An update and deployment mechanism ensures synchronization across the core program, plug-ins, and metadata.

Conclusions:

• OpenBEB offers versatility, easy deployment, and scalability, making it valuable for the scientific community.
• The software supports engineers, experimental biologists, and data analysts, fostering collaboration.
• OpenBEB successfully integrated live cell microscopy, microfluidic control, and visual proteomics, demonstrating its capability to correlate diverse measurements.