A New Method for Comparing Biological Networks
Author Information
Author(s): Klau Gunnar W, Michael Q Zhang, Michael S Waterman, Xuegong Zhang
Primary Institution: CWI, P.O. Box 94079, 1090 GB Amsterdam, The Netherlands
Hypothesis
Can a new graph-based method improve the alignment of biological networks?
Conclusion
The new method for network alignment is fast and offers advantages over traditional heuristic methods.
Supporting Evidence
- The new method is based on a maximum structural matching formulation.
- Computational experiments show that the method is reasonably fast.
- The software tool is freely available as part of the LISA library.
Takeaway
This study introduces a new way to compare biological networks, which helps scientists understand how different proteins interact.
Methodology
The study uses a graph-based maximum structural matching formulation and a Lagrangian relaxation approach to compute optimal network alignments.
Limitations
The paper does not provide a detailed comparison to other methods, which will be addressed in future work.
Digital Object Identifier (DOI)
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