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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

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GASOLINE: a Greedy And Stochastic algorithm for optimal Local multiple alignment of Interaction NEtworks.

Giovanni Micale¹, Alfredo Pulvirenti², Rosalba Giugno²

¹Department of Computer Science, University of Pisa, Pisa, Italy.

|June 10, 2014

Summary

GASOLINE, a new algorithm for multiple local network alignment, efficiently produces biologically significant alignments. It outperforms existing methods in reliability and speed for real biological networks.

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Area of Science:

Computational Biology
Bioinformatics
Systems Biology

Background:

Biological networks are crucial for understanding complex biological systems.
Network analysis aids evolutionary and comparative biology.
Current alignment methods face limitations with large datasets.

Purpose of the Study:

To introduce GASOLINE, an algorithm for multiple local network alignment.
To address limitations of existing network alignment approaches.
To provide a computationally feasible solution for large biological networks.

Main Methods:

GASOLINE employs statistical iterative sampling combined with a greedy strategy.
The algorithm performs multiple local network alignment.
It was tested on real and synthetic biological network databases.

Main Results:

GASOLINE achieves biologically significant alignments.
It demonstrates feasible running times, even for large networks.
Outperforms state-of-the-art algorithms in reliability and speed on real networks.
Shows comparable alignment quality on synthetic networks.

Conclusions:

GASOLINE offers a reliable and efficient solution for multiple local network alignment.
The algorithm is suitable for analyzing large and complex biological networks.
GASOLINE is available as a Java implementation with computed alignments.