From the desktop to the grid: scalable bioinformatics via workflow conversion

Area of Science:

• Computational Biology
• Bioinformatics
• Scientific Computing

Background:

• Scientific experiments involve complex data flows and parameter selection, impacting reproducibility.
• Breaking down experiments into manageable tasks aids in identifying bottlenecks and parallelization opportunities.
• Existing workflow engines have limitations, including cost and community-specific designs.

Purpose of the Study:

• To develop a platform-free tool for scientific workflow interoperability.
• To combine features of royalty-free workflow engines for broader accessibility.
• To simplify the design and execution of scientific workflows on high-performance computing resources.

Main Methods:

• Developed a structured representation for command-line tool parameters, inputs, and outputs (Common Tool Descriptor documents).
• Integrated Konstanz Information Miner (workflow editor) and Grid and User Support Environment (high-performance computing interaction).
• Created a free and accessible system for designing workflows on desktops and executing them on remote high-performance computing resources.

Main Results:

• Achieved platform-free structured representation of tool parameters and workflows.
• Successfully combined functionalities of two prominent royalty-free workflow engines.
• Enabled users to design workflows on local machines and execute them on high-performance computing infrastructure.

Conclusions:

• The developed tool reduces time spent on scientific workflow design.
• Increases accessibility of high-performance computing for technically inexperienced users.
• Enhances scientific reproducibility and the quality of research outcomes.