The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.05 - Sept.-Oct. (2013 vol.10)
pp: 1113-1124
Ahsanur Rahman , Dept. of Comput. Sci., Virginia Tech, Blacksburg, VA, USA
Christopher L. Poirel , Dept. of Comput. Sci., Virginia Tech, Blacksburg, VA, USA
David J. Badger , Dept. of Comput. Sci., Virginia Tech, Blacksburg, VA, USA
Craig Estep , Dept. of Comput. Sci., Virginia Tech, Blacksburg, VA, USA
T. M. Murali , Dept. of Comput. Sci., Virginia Tech, Blacksburg, VA, USA
ABSTRACT
Analysis of molecular interaction networks is pervasive in systems biology. This research relies almost entirely on graphs for modeling interactions. However, edges in graphs cannot represent multiway interactions among molecules, which occur very often within cells. Hypergraphs may be better representations for networks having such interactions, since hyperedges can naturally represent relationships among multiple molecules. Here, we propose using hypergraphs to capture the uncertainty inherent in reverse engineering gene-gene networks. Some subsets of nodes may induce highly varying subgraphs across an ensemble of networks inferred by a reverse engineering algorithm. We provide a novel formulation of hyperedges to capture this uncertainty in network topology. We propose a clustering-based approach to discover hyperedges. We show that our approach can recover hyperedges planted in synthetic data sets with high precision and recall, even for moderate amount of noise. We apply our techniques to a data set of pathways inferred from genetic interaction data in S. cerevisiae related to the unfolded protein response. Our approach discovers several hyperedges that capture the uncertain connectivity of genes in relevant protein complexes, suggesting that further experiments may be required to precisely discern their interaction patterns. We also show that these complexes are not discovered by an algorithm that computes frequent and dense subgraphs.
INDEX TERMS
Clustering algorithms, Proteins, Upper bound, Reverse engineering, Systems biology, Bioinformatics, Molecular computing,graphs and networks, Biology and genetics, hypergraphs
CITATION
Ahsanur Rahman, Christopher L. Poirel, David J. Badger, Craig Estep, T. M. Murali, "Reverse Engineering Molecular Hypergraphs", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.10, no. 5, pp. 1113-1124, Sept.-Oct. 2013, doi:10.1109/TCBB.2013.71
REFERENCES
[1] B. Alberts, A. Johnson, J. Lewis, M. Raff, K. Roberts, and P. Walter, "The Endoplasmic Reticulum," Molecular Biology of the Cell, fourth ed., Garland Science, 2002.
[2] J. Arroyo, J. Hutzler, C. Bermejo, E. Ragni, J. García-Cantalejo, P. Botías, H. Piberger, A. Schott, A.B. Sanz, and S. Strahl, "Functional and Genomic Analyses of Blocked Protein O-Mannosylation in Baker's Yeast," Molecular Microbiology, vol. 79, no. 6, pp. 1529-1546, 2011.
[3] A. Battle, M.C. Jonikas, P. Walter, J.S. Weissman, and D. Koller, "Automated Identification of Pathways from Quantitative Genetic Interaction Data," Molecular Systems Biology, vol. 6, no. 1, p. 379, 2010.
[4] S. Bauer, J. Gagneur, and P.N. Robinson, "GOing Bayesian: Model-Based Gene Set Analysis of Genome-Scale Data," Nucleic Acids Research, vol. 38, no. 11, pp. 3523-3532, 2010.
[5] G.F. Berriz, J.E. Beaver, C. Cenik, M. Tasan, and F.P. Roth, "Next Generation Software for Functional Trend Analysis," Bioinformatics, vol. 25, no. 22, pp. 3043-3044, 2009.
[6] T. Christensen, A. Oliveira, and J. Nielsen, "Reconstruction and Logical Modeling of Glucose Repression Signaling Pathways in Saccharomyces cerevisiae," BMC Systems Biology, vol. 3, no. 1,article 7, 2009.
[7] E. Demir et al., "The BioPAX Community Standard for Pathway Data Sharing," Nature Biotechnology, vol. 28, no. 9, pp. 935-942, 2010.
[8] J. Dutkowski and T. Ideker, "Protein Networks as Logic Functions in Development and Cancer," PLoS Computational Biology, vol. 7, no. 9,article e1002180, 2011.
[9] N. Friedman and D. Koller, "Being Bayesian about Network Structure: A Bayesian Approach to Structure Discovery in Bayesian Networks," Machine Learning, vol. 50, no. 1, pp. 95-125, 2003.
[10] X. He and J. Zhang, "Why Do Hubs Tend to Be Essential in Protein Networks?" PLoS Genetics, vol. 2, no. 6,article e88, 2006.
[11] L.S. Heath and A.A. Sioson, "Semantics of Multimodal Network Models," IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 6, no. 2, pp. 271-280, Apr. 2009.
[12] Z. Hu, J. Mellor, J. Wu, M. Kanehisa, J.M. Stuart, and C. DeLisi, "Towards Zoomable Multidimensional Maps of the Cell," Nature Biotechnology, vol. 25, no. 5, pp. 547-554, May 2007.
[13] C. Huttenhower, E.M. Haley, M.A. Hibbs, V. Dumeaux, D.R. Barrett, H.A. Coller, and O.G. Troyanskaya, "Exploring the Human Genome with Functional Maps," Genome Research, vol. 19, no. 6, pp. 1093-1106, 2009.
[14] M.C. Jonikas, S.R. Collins, V. Denic, E. Oh, E.M. Quan, V. Schmid, J. Weibezahn, B. Schwappach, P. Walter, J.S. Weissman, and M. Schuldiner, "Comprehensive Characterization of Genes Required for Protein Folding in the Endoplasmic Reticulum," Science, vol. 323, no. 5922, pp. 1693-1697, 2009.
[15] S. Klamt, U.-U. Haus, and F. Theis, "Hypergraphs and Cellular Networks," PLoS Computational Biology, vol. 5, no. 5,article e1000385, 2009.
[16] W. Li, C. Liu, T. Zhang, H. Li, M. Waterman, and X. Zhou, "Integrative Analysis of Many Weighted Co-Expression Networks Using Tensor Computation," PLoS Computational Biology, vol. 7, no. 6,article e1001106, 2011.
[17] J. Long and C. Hartman, "ODES: An Overlapping Dense Sub-Graph Algorithm," Bioinformatics, vol. 26, no. 21, pp. 2788-2789, 2010.
[18] F. Markowetz and R. Spang, "Inferring Cellular Networks—A Review," BMC Bioinformatics, vol. 8, no. Suppl 6, article S5, 2007.
[19] A. Mithani, G.M. Preston, and J. Hein, "Rahnuma: Hypergraph-Based Tool for Metabolic Pathway Prediction and Network Comparison," Bioinformatics, vol. 25, no. 14, pp. 1831-1832, 2009.
[20] M. Newman, "Modularity and Community Structure in Networks," Proc. Nat'l Academy of Sciences USA, vol. 103, no. 23, pp. 8577-8582, 2006.
[21] D. Pe'er, "Bayesian Network Analysis of Signaling Networks: A Primer," Science Signaling, vol. 2005, no. 281, p. pl4, 2005.
[22] J. Rachlin, D.D. Cohen, C. Cantor, and S. Kasif, "Biological Context Networks: A Mosaic View of the Interactome," Molecular Systems Biology, vol. 2, no. 1, Nov. 2006.
[23] E. Ramadan, A. Tarafdar, and A. Pothen, "A Hypergraph Model for the Yeast Protein Complex Network," Proc. 18th Int'l Parallel and Distributed Processing Symp., pp. 189-196, 2004.
[24] J. Rini, J. Esko, and A. Varki, "Glycosyltransferases and Glycan-Processing Enzymes," Essentials of Glycobiology, second ed., Cold Spring Harbor Laboratory Press, 2009.
[25] C.F. Schaefer, K. Anthony, S. Krupa, J. Buchoff, M. Day, T. Hannay, and K.H. Buetow, "PID: The Pathway Interaction Database," Nucleic Acids Research, vol. 37, pp. D674-D679, 2009.
[26] S.-E. Schelhorn, J. Mestre, M. Albrecht, and E. Zotenko, "Inferring Physical Protein Contacts from Large-Scale Purification Data of Protein Complexes," Molecular and Cellular Proteomics, vol. 10, no. 6, article M110.004929, 2011.
[27] M. Schuldiner, J. Metz, V. Schmid, V. Denic, M. Rakwalska, H. Schmitt, B. Schwappach, and J. Weissman, "The GET Complex Mediates Insertion of Tail-Anchored Proteins into the ER Membrane," Cell, vol. 134, no. 4, pp. 634-645, 2008.
[28] R. Sharan and T. Ideker, "Modeling Cellular Machinery through Biological Network Comparison," Nature Biotechnology, vol. 24, no. 4, pp. 427-433, 2006.
[29] C. Stark, B.-J.J. Breitkreutz, A. Chatr-Aryamontri, L. Boucher, R. Oughtred, M.S. Livstone, J. Nixon, K.V. Auken, X. Wang, X. Shi, T. Reguly, J.M. Rust, A. Winter, K. Dolinski, and M. Tyers, "The BioGRID Interaction Database: 2011 Update," Nucleic Acids Research, vol. 39, pp. D698-D704, 2011.
[30] I. Ulitsky, A. Krishnamurthy, R.M. Karp, and R. Shamir, "DEGAS: De Novo Discovery of Dysregulated Pathways in Human Diseases," PLoS ONE, vol. 5, no. 10,article e13367, 2010.
[31] K. Wang, M. Saito, B.C. Bisikirska, M.J. Alvarez, W.K. Lim, P. Rajbhandari, Q. Shen, I. Nemenman, K. Basso, A.A. Margolin, U. Klein, R. Dalla-Favera, and A. Califano, "Genome-Wide Identification of Post-Translational Modulators of Transcription Factor Activity in Human B Cells," Nature Biotechnology, vol. 27, no. 9, pp. 829-837, 2009.
[32] W. Zhou and L. Nakhleh, "Properties of Metabolic Graphs: Biological Organization or Representation Artifacts?," BMC Bioinformatics, vol. 12, no. 1,article 132, 2011.
68 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool