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Biological Network Alignment

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Functional Coherence of Molecular Networks in Bioinformatics

Abstract

Recent experimental approaches to high-throughput screening, combined with effective computational techniques have resulted in large, high-quality databases of biochemical interactions. These databases hold the potential for fundamentally enhancing our understanding of cellular processes and for controlling them. Recent work on analyses of these databases has focused on computational approaches for aligning networks, identifying modules, extracting discriminating and descriptive components, and inferring networks. In this chapter, we focus on the problem of aligning a given set of networks with a view to identifying conserved subnetworks, finding orthologies, and elucidating higher level organization and evolution of interactions. Network alignment, in general, poses significant computational challenges, since it is related to the subgraph isomorphism problem (which is known to be computationally expensive). For this reason, effective computational techniques focus on exploiting structure of networks (and their constituent elements), alternate formulations in terms of underlying optimization, and on the use of additional data for simplifying the alignment process. We present a comprehensive survey of these approaches, along with important algorithms for various formulations of the network alignment problem.

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Acknowledgements

The authors thank Ron Pinter (Technion) and Mehmet Koyutürk (Case Western Reserve) for many useful suggestions.

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Authors and Affiliations

  1. Purdue University, Lafayette, IN, 47906, USA

    Shahin Mohammadi

  2. Department of Computer Science, Purdue University, 305 N. University Street, West Lafayette, IN, 47907-2107, USA

    Ananth Grama

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Correspondence to Ananth Grama .

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Editors and Affiliations

  1. Department of Electrical Engineering & C, Case Western Reserve University, Euclid Ave. 10900, Cleveland, 44106, Ohio, USA

    Mehmet Koyutürk

  2. Department of Bioengineering, University of California, San Diego, 9500 Gilman Dr., La Jolla, 92093-0412, California, USA

    Shankar Subramaniam

  3. Department of Computer Science, Purdue University, 305 North University Street, West Lafayette, 47907-2107, Indiana, USA

    Ananth Grama

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Mohammadi, S., Grama, A. (2012). Biological Network Alignment. In: Koyutürk, M., Subramaniam, S., Grama, A. (eds) Functional Coherence of Molecular Networks in Bioinformatics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0320-3_5

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