article

A matrix-based multilevel approach to identify functional protein modules

Authors:

Suely Oliveira,

Sang-Cheol SeokAuthors Info & Claims

International Journal of Bioinformatics Research and Applications, Volume 4, Issue 1

Pages 11 - 27

https://doi.org/10.1504/IJBRA.2008.017161

Published: 01 February 2008 Publication History

Abstract

Identifying functional modules is believed to reveal most cellular processes. There have been many computational approaches to investigate the underlying biological structures (Bader and Hogue, 2003; Dhillon et al., 2005; Krogan et al., 2006; Ramadan et al., 2005; Xiong et al., 2005; Zhang et al., 2004). A spectral clustering method plays a critical role identifying functional modules in a yeast protein-protein network (Ramadan et al., 2005). We present an unweighted-graph version of a multilevel spectral algorithm which more accurately identifies protein complexes with less computational time.

References

[1]

Abou-Rjeili, A. and Karypis, G. (2005) Multilevel Algorithms for Partitioning Power-Law Graphs, Technical Report TR 05-034, University of Minnesota, Minneapolis, MN, http://glaros.dtc. umn.edu/gkhome/fetch/papers/powerlawgraphs.pdf

[2]

Bader, G.D. and Hogue, C.W. (2003) 'An automated method for finding molecular complexes in large protein interaction networks', BMC Bioinformatics, Vol. 57, No. 1, Available via http://www.biomedcentral.com/bmcbioinformatics/archive/

[3]

Batagelj, V. and Zaversnik, M. (2002) Generalized Cores, Computing Research Repository (CoRR), Vol. cs.DS/0202039, Available via http://arxiv.org/abs/cs.DS/0202039

[4]

Bornholdt, S. and Schuster, H.G. (Eds.) (2003) Handbook of Graphs and Networks, Wiley VCH, Berlin.

[5]

Deane, C.M., Salwinski, L., Xenarios, I. and Eisenberg, D. (2002) 'Protein interactions: two methods for assessment of the reliability of high throughput observations', Mol. Cell Proteomics, Vol. 1, No. 5, pp. 349-356.

[6]

Dhillon, I., Guan, Y. and Kulis, B. (2005) 'A fast kernel-based multilevel algorithm for graph clustering', Proc. Eleventh ACM SIGKDD International Conference on Knowledge Discovery in Data Mining, Chicago, IL, pp. 629-634, http://doi.acm.org/10.1145/1081870.1081948

Digital Library

[7]

Ding, C., He, X., Zha, H., Gu, M. and Simon, H. (2003) A MinMaxCut Spectral Method for Data Clustering and Graph Partitioning, Technical Report TR 54111, Lawrence-Berkeley National Laboratory, Berkeley, CA, http://www.nersc.gov/~simon/Papers/long3.ps

[8]

Ding, C., He, X., Meraz, R. and Holbrook, S. (2004) 'A Unified representation for multiprotein complex data for modeling protein interaction networks', Proteins: Structure, Function and Bioinformatics, Vol. 57, pp. 99-108.

[9]

Fiduccia, C.M. and Mattheyses, R.M. (1982) 'A linear time heuristic for improving network partitions', Proc. 19th IEEE Design Automation Conference, pp. 175-181, http://portal.acm. org/citation.cfm?id=800263.809204

Digital Library

[10]

Gabow, H.N. (1990) 'Data structures for weighted matching and nearest common ancestors with linking', Proc. SIAM/ACM Symposium on Discrete Algorithms (SODA), San Francisco, CA, pp. 434-443, http://portal.acm.org/citation.cfm?id=320229

Digital Library

[11]

Hagen, L. and Kahng, A. (1991) 'Fast spectral methods for ratio cut partitioning and clustering', Proc. IEEE Internat. Conf. Computer Aided Design, pp. 10-13, http://ieeexplore.ieee.org/ xpls/abs_all.jsp?arnumber=185177

[12]

Karypis, G. and Kumar, V. (1995) MeTis: Unstructured Graph Partitioning and Sparse Matrix Ordering System and Version 2.0, http://citeseer.ist.psu.edu/karypis95metis.html

[13]

Karypis, G. and Kumar, V. (1998) 'A fast and high quality multilevel scheme for partitioning irregular graphs', SIAM J. Sci. Comput., Vol. 20, No. 1, pp. 359-392.

Digital Library

[14]

Kernighan, B.W. and Lin, S. (1970) 'An efficient heuristic procedure for partitioning graphs', The Bell System Technical Journal, Vol. 49, No. 2, pp. 291-308.

[15]

Krogan, N. et al. (2006) 'Global landscape of protein complexes in the yeast Saccharomyces cerevisiae', Nature, Vol. 440, No. 7084, pp. 637-643, http://www.ncbi.nlm.nih.gov/sites/ entrez?cmd=Retrieve&db=

[16]

Monien, B., Preis, R. and Diekmann, R. (2000) 'Quality matching and local improvement for multilevel graph-partitioning', Parallel Comput., Vol. 26, pp. 1609-1634.

Digital Library

[17]

Newman, M.E.J. (2003) 'Properties of highly clustered networks', Physics Review, Vol. 57, pp. 99-108.

[18]

Oliveira, S. and Seok, S.C. (2005) 'A multi-level approach for document clustering', Proc. ICCS 2005, Lecture Notes in Computer Science, Springer, Atlanta, GA, Vol. 3514, pp. 204-211.

Digital Library

[19]

Ramadan, E., Osgood, C. and Pothen, A. (2005) 'The architecture of a proteomic network in the yeast', Proceedings of CompLife 2005, Lecture Notes in Bioinformatics, Springer, Konstanz, Germany, Vol. 3695, pp. 265-276.

Digital Library

[20]

Shi, J. and Malik, J. (2000) 'Normalized cuts and image segmentation', IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 22, No. 8, pp. 888-905.

Digital Library

[21]

Vazirani, V. (1994) 'A theory of alternating paths and blossoms for proving correctness of the ¿(E) general graph maximum matching algorithm', Combinatorica, Vol. 14, pp. 71-109.

[22]

Xiong, H., He, X., Ding, C., Zhang, Y., Kumar, V. and Holbrook, S. (2005) 'Identification of functional modules in protein complexes via hyperclique pattern discovery', Proc. Pacific Symposium on Biocomputing (PSB), Big Island, Hawaii, Vol. 10, pp. 221-232, http://eproceedings.worldscinet.com/9789812702456/9789812702456_0021.html

[23]

Zhang, L., Wong, S., King, O. and Roth, R. (2004) 'Predicting co-complexed protein pairs using genomic and proteomic data integration', BMC Bioinformatics, Vol. 5, No. 38, Available via http://www.biomedcentral.com/bmcbioinformatics/archive/

Cited By

Valejo AFerreira VFabbri ROliveira MLopes A(2020)A Critical Survey of the Multilevel Method in Complex NetworksACM Computing Surveys10.1145/337934753:2(1-35)Online publication date: 17-Apr-2020
https://dl.acm.org/doi/10.1145/3379347
(2018)High quality multi-core multi-level algorithm for community detectionInternational Journal of Computational Science and Engineering10.5555/3160607.316062115:3-4(311-321)Online publication date: 20-Dec-2018
https://dl.acm.org/doi/10.5555/3160607.3160621
Oliveira SSharma R(2016)Identification and prediction of functional protein modules using a bi-level community detection algorithmInternational Journal of Bioinformatics Research and Applications10.1504/IJBRA.2016.07712412:2(129-148)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1504/IJBRA.2016.077124
Show More Cited By

Index Terms

A matrix-based multilevel approach to identify functional protein modules
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
        Cluster analysis
2. Mathematics of computing
  1. Mathematical analysis
    1. Numerical analysis
      1. Computations on matrices

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cover image International Journal of Bioinformatics Research and Applications

International Journal of Bioinformatics Research and Applications Volume 4, Issue 1

February 2008

121 pages

ISSN:1744-5485

EISSN:1744-5493

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Publisher

Inderscience Publishers

Geneva 15, Switzerland

Publication History

Published: 01 February 2008

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Cited By

Valejo AFerreira VFabbri ROliveira MLopes A(2020)A Critical Survey of the Multilevel Method in Complex NetworksACM Computing Surveys10.1145/337934753:2(1-35)Online publication date: 17-Apr-2020
https://dl.acm.org/doi/10.1145/3379347
(2018)High quality multi-core multi-level algorithm for community detectionInternational Journal of Computational Science and Engineering10.5555/3160607.316062115:3-4(311-321)Online publication date: 20-Dec-2018
https://dl.acm.org/doi/10.5555/3160607.3160621
Oliveira SSharma R(2016)Identification and prediction of functional protein modules using a bi-level community detection algorithmInternational Journal of Bioinformatics Research and Applications10.1504/IJBRA.2016.07712412:2(129-148)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1504/IJBRA.2016.077124
Ji JLv JYang CZhang A(2016)Detecting Functional Modules Based on a Multiple-Grain Model in Large-Scale Protein-Protein Interaction NetworksIEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)10.1109/TCBB.2015.248006613:4(610-622)Online publication date: 1-Jul-2016
https://dl.acm.org/doi/10.1109/TCBB.2015.2480066

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