De Novo Pathway Enrichment with KeyPathwayMiner

  • Nicolas Alcaraz
  • Anne Hartebrodt
  • Markus ListEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 2074)


Biomolecular networks such as protein–protein interaction networks provide a static picture of the interplay of genes and their products, and, consequently, they fail to capture dynamic changes taking place during the development of complex diseases. KeyPathwayMiner is a software platform designed to fill this gap by integrating previous knowledge captured in molecular interaction networks with OMICS datasets (DNA microarrays, RNA sequencing, genome-wide methylation studies, etc.) to extract connected subnetworks with a high number of deregulated genes. This protocol describes how to use KeyPathwayMiner for integrated analysis of multi-omics datasets in the network analysis tool Cytoscape and in a stand-alone web application available at

Key words

De novo pathway enrichment Molecular interaction networks Cytoscape Multi-omics 


  1. 1.
    Cordell HJ (2009) Detecting gene–gene interactions that underlie human diseases. Nat Rev Genet 10:392CrossRefGoogle Scholar
  2. 2.
    Kanehisa M, Goto S (2000) KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28:27–30CrossRefGoogle Scholar
  3. 3.
    Joshi-Tope G, Gillespie M, Vastrik I et al (2005) Reactome: a knowledgebase of biological pathways. Nucleic Acids Res 33:D428–D432CrossRefGoogle Scholar
  4. 4.
    Falcon S, Gentleman R (2008) Hypergeometric testing used for gene set enrichment analysis. In: Hahne F, Huber W, Gentleman R, Falcon S (eds) Bioconductor case studies. Springer New York, New York, NY, pp 207–220CrossRefGoogle Scholar
  5. 5.
    Subramanian A, Tamayo P, Mootha VK et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102:15545–15550CrossRefGoogle Scholar
  6. 6.
    Alcaraz N, Kücük H, Weile J et al (2011) KeyPathwayMiner: detecting case-specific biological pathways using expression data. Internet Math 7:299–313CrossRefGoogle Scholar
  7. 7.
    List M, Alcaraz N, Dissing-Hansen M et al (2016) KeyPathwayMinerWeb: online multi-omics network enrichment. Nucleic Acids Res 44(W1):W98–W104CrossRefGoogle Scholar
  8. 8.
    Alcaraz N, Pauling J, Batra R et al (2014) KeyPathwayMiner 4.0: condition-specific pathway analysis by combining multiple omics studies and networks with Cytoscape. BMC Syst Biol 8:99CrossRefGoogle Scholar
  9. 9.
    Alcaraz N, List M, Dissing-Hansen M et al (2016) Robust de novo pathway enrichment with KeyPathwayMiner 5. F1000Res 5:1531CrossRefGoogle Scholar
  10. 10.
    Shannon P, Markiel A, Ozier O et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504CrossRefGoogle Scholar
  11. 11.
    Ideker T, Ozier O, Schwikowski B, Siegel AF (2002) Discovering regulatory and signalling circuits in molecular interaction networks. Bioinformatics 18(Suppl 1):S233–S240CrossRefGoogle Scholar
  12. 12.
    Chatr-aryamontri A, Breitkreutz B-J, Oughtred R et al (2015) The BioGRID interaction database: 2015 update. Nucleic Acids Res 43:D470–D478CrossRefGoogle Scholar
  13. 13.
    Zuberi K, Franz M, Rodriguez H et al (2013) GeneMANIA prediction server 2013 update. Nucleic Acids Res 41:W115–W122CrossRefGoogle Scholar
  14. 14.
    Bovolenta LA, Acencio ML, Lemke N (2012) HTRIdb: an open-access database for experimentally verified human transcriptional regulation interactions. BMC genomics, 13(1):405Google Scholar
  15. 15.
    Keshava Prasad TS, Goel R, Kandasamy K et al (2009) Human protein reference database—2009 update. Nucleic Acids Res 37:D767–D772CrossRefGoogle Scholar
  16. 16.
    Orchard S, Ammari M, Aranda B et al (2014) The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res 42:358–363CrossRefGoogle Scholar
  17. 17.
    Kotlyar M, Pastrello C, Sheahan N, Jurisica I (2016) Integrated interactions database: tissue-specific view of the human and model organism interactomes. Nucleic Acids Res 44:D536–D541CrossRefGoogle Scholar
  18. 18.
    Franceschini A, Szklarczyk D, Frankild S et al (2013) STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res 41:D808–D815. Scholar
  19. 19.
    Dorigo M, Stﺰtzle T (2004) Ant colony optimization. MIT Press, ISBN: 9780262042192Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  1. 1.Department of Biology, The Bioinformatics CentreUniversity of CopenhagenCopenhagenDenmark
  2. 2.TUM School of Life SciencesTechnical University of MunichFreisingGermany

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