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On TD-WGcluster: Theoretical Foundations and Guidelines for the User

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Protein-Protein Interaction Networks

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2074))

Abstract

We review the TD-WGcluster (time delayed weighted edge clustering) software integrating static interaction networks with time series data in order to detect modules of nodes between which the information flows at similar time delays and intensities. The software has represented an advancement of the state of the art in the software for the identification of connected components due to its peculiarity of dealing with direct and weighted graphs, where the attributes of the physical entities represented by nodes vary over time. This chapter aims to deepen those theoretical aspects of the clustering model implemented by TD-WGcluster that may be of greater interest to the user. We show the instructions necessary to run the software through some exploratory cases and comment on the results obtained.

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Author information

Author notes

  1. Paola Lecca

    Present address: Faculty of Computer Science, Free University of Bolzano-Bozen, Bolzano, Italy

Authors and Affiliations

  1. Systems and Synthetic Biology Laboratory, Centre for Sustainable Future Technologies, Fondazione Istituto Italiano di Tecnologia, Torino, Italy

    Angela Re

  2. Department of Mathematics, University of Trento, Trento, Italy

    Paola Lecca

Authors
  1. Angela Re
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  2. Paola Lecca
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Corresponding author

Correspondence to Paola Lecca .

Editor information

Editors and Affiliations

  1. Gene Center, Ludwig-Maximilians-Universität München, München, Germany

    Stefan Canzar

  2. Gene Center, Ludwig-Maximilians-Universität München, München, Germany

    Francisca Rojas Ringeling

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Re, A., Lecca, P. (2020). On TD-WGcluster: Theoretical Foundations and Guidelines for the User. In: Canzar, S., Ringeling, F. (eds) Protein-Protein Interaction Networks. Methods in Molecular Biology, vol 2074. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9873-9_17

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  • DOI: https://doi.org/10.1007/978-1-4939-9873-9_17

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9872-2

  • Online ISBN: 978-1-4939-9873-9

  • eBook Packages: Springer Protocols

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