Multipath: An R Package to Generate Integrated Reproducible Pathway Models
IT-Infrastructure for Translational Medical Research, University of Augsburg, 86159 Augsburg, Germany
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Biology 2020, 9(12), 483; https://doi.org/10.3390/biology9120483
Received: 24 October 2020
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Revised: 16 December 2020
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Accepted: 19 December 2020
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Published: 21 December 2020
(This article belongs to the Special Issue Computational Biology)
Simple Summary
In biological terms, the term "pathway" is used to describe a collection of processes within a cell that lead to one or more actions. The graphical representation of these processes enables the reader to understand complex relationships and interactions much more easily compared to free-text descriptions. While there is usually agreement on the existence and function of these high-level processes, the specific molecules and their interactions are often disputed and a matter of current research. A standardized computational representation of biological networks has become desirable, especially with the recent surge in new knowledge generation in biology and medicine. Our work is influenced by challenges emerging from previous work on biological pathways, knowledge encoding, and visualization as well as pathway databases. Our main motivation is the difficulty of reproducing pathway knowledge used within publications, even in top-tier journals. We propose a new way of integrating and modeling pathways and other influencing knowledge, such as drugs, and documenting their modifications using multilayered networks. We provide a tool that transforms encoded pathway data to multilayered graphs, with the possibility to modify them, and integrate other knowledge from external databases.
Biological pathway data integration has become a topic of interest in the past years. This interest originates essentially from the continuously increasing size of existing prior knowledge as well as from the many challenges scientists face when studying biological pathways. Multipath is a framework that aims at helping re-trace the use of specific pathway knowledge in specific publications, and easing the data integration of multiple pathway types and further influencing knowledge sources. Multipath thus helps scientists to increase the reproducibility of their code and analysis by allowing the integration of numerous data sources and documentation of their integration steps while doing so. In this paper, we present the package Multipath, and we describe how it can be used for data integration and tracking pathway modifications. We present a multilayer model built from the Wnt Pathway as a demonstration.
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Keywords:
multilayer networks; data integration; biological pathways; reproducibility; visualization
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MDPI and ACS Style
Hammoud, Z.; Kramer, F. Multipath: An R Package to Generate Integrated Reproducible Pathway Models. Biology 2020, 9, 483. https://doi.org/10.3390/biology9120483
AMA Style
Hammoud Z, Kramer F. Multipath: An R Package to Generate Integrated Reproducible Pathway Models. Biology. 2020; 9(12):483. https://doi.org/10.3390/biology9120483
Chicago/Turabian StyleHammoud, Zaynab, and Frank Kramer. 2020. "Multipath: An R Package to Generate Integrated Reproducible Pathway Models" Biology 9, no. 12: 483. https://doi.org/10.3390/biology9120483
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