Abstract
This chapter presents in detail aspects related to pathway-based analysis of time-varying biological processes. Biological processes are inherently dynamical events involving genes and their products interacting within specific conditions. Genes are modulated by systemic perturbations (e.g., genetic modifications or drug treatments). Thus, monitoring the systemic response at multiple levels, in conjunction with the temporal evolution, is crucial to understanding and modeling the underlying biological phenomena in a comprehensive manner. The increasing need for developing biological network and pathway analysis methods capable of providing fine temporal resolution is highlighted, in the context of decreasing costs of high-throughput technologies which is expected to trigger a significant raise in time course omics experimental data availability. Several important challenges involved in this type of analysis are discussed, such as the conversion of pathway databases information into graphs (or networks) in order to allow easier interpretation of information and subsequent computational modeling, the contextualization of the transformed pathway graphs using transcriptional data, the use of search methods for the identification within graphs of paths highlighting the time dependent portions of pathways, as well as the use of various network-based statistics or interacting edge level metrics.
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Bezerianos, A., Dragomir, A., Balomenos, P. (2017). Time-Varying Methods for Pathway and Sub-pathway Analysis. In: Computational Methods for Processing and Analysis of Biological Pathways. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-53868-6_3
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