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A Systems Bioinformatics Approach to Interconnect Biological Pathways

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Computational Methods in Synthetic Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2189))

Abstract

Signal transduction tasks as well as other complex biological processes involve many different changes in groups of genes, proteins, and metabolites linked together in chains or networks called pathways or networks of pathways. In a classical functional analysis, the biomolecules found to play a role in the biological status under investigation are members of a group of pathways that are not necessarily interconnected. However, interconnectivity is a critical factor for functionality. Thus, it is necessary to be able to construct “connected functional stories” to understand better the complex biological processes. PathwayConnector is a recently introduced web-tool that facilitates the construction of complementary pathway-to-pathway networks, bringing to our attention missing pathways that are crucial links towards the understanding of the molecular mechanisms related to complex diseases. Current version of the web-tool draws from an expanded pathway reference network and provides information deriving from 19 different organisms and 2 different pathway repositories: the KEGG and the REACTOME. Novel genes, proteins, and pathways derived from any experimental/computational method either in large-scale (omics) or even in smaller scale (specific laboratory experiments) can potentially be projected and analyzed through PathwayConnector. This chapter describes in details the pipeline and methodologies used for the latest updated version of PathwayConnector, providing an easy way for rapidly relating human or other organism’s pathways together. Recent studies have shown that pathway networks and subnetworks, generated by PathwayConnector, are an integral part towards the individualization of disease, leading to a more precise and personalized management of the treatment.

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References

  1. Oulas A, Minadakis G, Zachariou M, Sokratous K, Bourdakou MM, Spyrou GM (2019) Systems bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches. Brief Bioinform 20(3):806–824

    Article  CAS  Google Scholar 

  2. Jin L, Zuo XY, Su WY, Zhao XL, Yuan MQ, Han LZ, Zhao X, Chen YD, Rao SQ (2014) Pathway-based analysis tools for complex diseases: a review. Genomics Proteomics Bioinformatics 12(5):210–220. https://doi.org/10.1016/j.gpb.2014.10.002

    Article  PubMed  PubMed Central  Google Scholar 

  3. Kuleshov MV, Jones MR, Rouillard AD, Fernandez NF, Duan Q, Wang Z, Koplev S, Jenkins SL, Jagodnik KM, Lachmann A, McDermott MG, Monteiro CD, Gundersen GW, Ma'ayan A (2016) Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res 44(W1):W90–W97. https://doi.org/10.1093/nar/gkw377

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Chen EY, Tan CM, Kou Y, Duan Q, Wang Z, Meirelles GV, Clark NR, Ma’ayan A (2013) Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14(1):128

    Article  Google Scholar 

  5. Minadakis G, Zachariou M, Oulas A, Spyrou GM (2019) PathwayConnector: finding complementary pathways to enhance functional analysis. Bioinformatics 35(5):889–891

    Article  CAS  Google Scholar 

  6. Karp PD (2001) Pathway databases: a case study in computational symbolic theories. Science 293(5537):2040–2044

    Article  CAS  Google Scholar 

  7. Domingo-Fernandez D, Mubeen S, Marin-Llao J, Hoyt CT, Hofmann-Apitius M (2019) PathMe: merging and exploring mechanistic pathway knowledge. BMC Bioinformatics 20(1):243

    Article  Google Scholar 

  8. Kanehisa M (2002) The KEGG database. In: Bock G, Goode JA (eds) In silico simulation of biological processes. Wiley, New York

    Google Scholar 

  9. Croft D, O’kelly G, Wu G, Haw R, Gillespie M, Matthews L, Caudy M, Garapati P, Gopinath G, Jassal B (2010) Reactome: a database of reactions, pathways and biological processes. Nucleic Acids Res 39(suppl_1):D691–D697

    PubMed  PubMed Central  Google Scholar 

  10. Hood L, Friend SH (2011) Predictive, personalized, preventive, participatory (P4) cancer medicine. Nat Rev Clin Oncol 8(3):184–187. https://doi.org/10.1038/nrclinonc.2010.227

    Article  PubMed  Google Scholar 

  11. Tian Q, Price ND, Hood L (2012) Systems cancer medicine: towards realization of predictive, preventive, personalized and participatory (P4) medicine. J Intern Med 271(2):111–121. https://doi.org/10.1111/j.1365-2796.2011.02498.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Csardi G, Nepusz T (2006) The igraph software package for complex network research. InterJournal Complex Syst 1695:1695

    Google Scholar 

  13. Qu K, Garamszegi S, Wu F, Thorvaldsdottir H, Liefeld T, Ocana M, Borges-Rivera D, Pochet N, Robinson JT, Demchak B (2016) Integrative genomic analysis by interoperation of bioinformatics tools in GenomeSpace. Nat Methods 13(3):245

    Article  CAS  Google Scholar 

  14. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504

    Article  CAS  Google Scholar 

  15. UniProt Consortium (2014) UniProt: a hub for protein information. Nucleic Acids Res 43(D1):D204–D212

    Article  Google Scholar 

  16. Yu G, Wang LG, Han Y, He QY (2012) clusterProfiler: an R package for comparing biological themes among gene clusters. Omics 16(5):284–287. https://doi.org/10.1089/omi.2011.0118

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Yu G, He QY (2016) ReactomePA: an R/bioconductor package for reactome pathway analysis and visualization. Mol BioSyst 12(2):477–479. https://doi.org/10.1039/c5mb00663e

    Article  CAS  PubMed  Google Scholar 

  18. Newman ME, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E Stat Nonlinear Soft Matter Phys 69(2 Pt 2):026113. https://doi.org/10.1103/PhysRevE.69.026113

    Article  CAS  Google Scholar 

  19. Pons P, Latapy M (2006) Computing communities in large networks using random walks. J Graph Algorithms Applications 10(2):191–218

    Article  Google Scholar 

  20. Clauset A, Newman ME, Moore C (2004) Finding community structure in very large networks. Phys Rev E 70(6):066111

    Article  Google Scholar 

  21. Newman ME (2006) Finding community structure in networks using the eigenvectors of matrices. Phys Rev E 74(3):036104

    Article  CAS  Google Scholar 

  22. Brandes U, Delling D, Gaertler M, Gorke R, Hoefer M, Nikoloski Z, Wagner D (2008) On modularity clustering. IEEE Trans Knowl Data Eng 20(2):172–188

    Article  Google Scholar 

  23. Reichardt J, Bornholdt S (2006) Statistical mechanics of community detection. Phys Rev E Stat Nonlinear Soft Matter Phys 74(1 Pt 2):016110. https://doi.org/10.1103/PhysRevE.74.016110

    Article  CAS  Google Scholar 

  24. Barabási A-L (2003) Emergence of scaling in complex networks. In: Handbook of graphs and networks. Wiley, Berlin, pp 69–84

    Google Scholar 

  25. Liu Y-Y, Slotine J-J, Barabási A-L (2012) Control centrality and hierarchical structure in complex networks. PLoS One 7(9):e44459

    Article  CAS  Google Scholar 

  26. Daskalaki E, Spiliotis K, Siettos C, Minadakis G, Papadopoulos GA (2016) Foreshocks and short-term hazard assessment of large earthquakes using complex networks: the case of the 2009 L’Aquila earthquake. Nonlinear Process Geophys 23(4):241–256

    Article  Google Scholar 

  27. Barabási A-L, Gulbahce N, Loscalzo J (2011) Network medicine: a network-based approach to human disease. Nat Rev Genet 12(1):56

    Article  Google Scholar 

  28. Aldrich J (1995) Correlations genuine and spurious in Pearson and Yule. Stat Sci 10(4):364–376

    Article  Google Scholar 

  29. Zachariou M, Minadakis G, Oulas A, Afxenti S, Spyrou GM (2018) Integrating multi-source information on a single network to detect disease-related clusters of molecular mechanisms. J Proteome 188:15–29

    Article  CAS  Google Scholar 

  30. Najafi A, Bidkhori G, Bozorgmehr JH, Koch I, Masoudi-Nejad A (2014) Genome scale modeling in systems biology: algorithms and resources. Curr Genomics 15(2):130–159. https://doi.org/10.2174/1389202915666140319002221

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Menche J, Guney E, Sharma A, Branigan PJ, Loza MJ, Baribaud F, Dobrin R, Barabasi AL (2017) Integrating personalized gene expression profiles into predictive disease-associated gene pools. NPJ Syst Biol Appl 3:10. https://doi.org/10.1038/s41540-017-0009-0

    Article  PubMed  PubMed Central  Google Scholar 

  32. Jamal S, Goyal S, Shanker A, Grover A (2016) Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes. BMC Genomics 17(1):807. https://doi.org/10.1186/s12864-016-3108-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Ram PT, Mendelsohn J, Mills GB (2012) Bioinformatics and systems biology. Mol Oncol 6(2):147–154. https://doi.org/10.1016/j.molonc.2012.01.008

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Kakouri AC, Christodoulou CC, Zachariou M, Oulas A, Minadakis G, Demetriou CA, Votsi C, Zamba-Papanicolaou E, Christodoulou K, Spyrou GM (2018) Revealing clusters of connected pathways through multisource data integration in Huntington’s disease and spastic ataxia. IEEE J Biomed Health Inf 23(1):26–37

    Article  Google Scholar 

  35. Gkretsi V, Louca M, Stylianou A, Minadakis G, Spyrou G, Stylianopoulos T (2019) Inhibition of breast cancer cell invasion by Ras suppressor-1 (RSU-1) silencing is reversed by growth differentiation factor-15 (GDF-15). Int J Mol Sci 20(1):163

    Article  Google Scholar 

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Acknowledgments

This work is funded by the European Commission Research Executive Agency Grant BIORISE (No. 669026), under the Spreading Excellence, Widening Participation, Science with and for Society Framework.

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Authors and Affiliations

  1. Department of Bioinformatics, The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus

    George Minadakis & George M. Spyrou

Authors
  1. George Minadakis
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  2. George M. Spyrou
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Corresponding author

Correspondence to George Minadakis .

Editor information

Editors and Affiliations

  1. School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China

    Mario Andrea Marchisio

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Minadakis, G., Spyrou, G.M. (2021). A Systems Bioinformatics Approach to Interconnect Biological Pathways. In: Marchisio, M.A. (eds) Computational Methods in Synthetic Biology. Methods in Molecular Biology, vol 2189. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0822-7_17

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  • DOI: https://doi.org/10.1007/978-1-0716-0822-7_17

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0821-0

  • Online ISBN: 978-1-0716-0822-7

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