UBioLab: a web-laboratory for ubiquitous in-silico experiments

Area of Science:

• Bioinformatics
• Computational Biology
• Semantic Web Technologies

Background:

• The proliferation of internet-based bioinformatic resources presents challenges in data management, visualization, and in-silico experiment execution for biologists and bioinformaticians.
• Integrating diverse resources with varying computational paradigms and interfaces (e.g., OGSA, SOAP, Java RMI) requires a unified framework.

Purpose of the Study:

• To design and develop a prototype framework, UBioLab, addressing the integration and management of distributed bioinformatic resources.
• To provide a transparent and uniform approach for handling resource distribution, semantic heterogeneity, and diverse computational interfaces.

Main Methods:

• UBioLab employs a fully Web-based architecture combining domain ontologies, Semantic Web, and workflow techniques.
• Key components include a semantic knowledge management system for distributed resources, a semantic-driven graphic environment for workflow definition/monitoring, and intelligent agent-based technology for distributed execution.

Main Results:

• UBioLab facilitates flexible visualization, organization, and inference of domain knowledge (resources, activities).
• It provides a powerful engine for defining and storing semantic-driven, ubiquitous in-silico experiments.
• The framework enables transparent, automatic, and distributed execution of these experiments.

Conclusions:

• UBioLab acts as a semantic guide, simplifying the use of distributed bioinformatic resources for both biologists and bioinformaticians.
• The framework's architecture effectively tackles challenges in resource integration, semantic heterogeneity, and experiment execution in a distributed environment.