Abstract
Biochemical pathways analysis is an effective tool for understanding changes in gene expression data and associating such changes with cellular phenotypes. Pathway research aims to identify associated proteins within a cell using pathways and at building new pathways from a group of molecules of interest. Using pathway-based methods we gain insight into different functions of relevant molecules and find direct and indirect relations between them. We present PathWeigh, a Python-based tool for pathway analysis and graph presentation. The tool is open-sourced, extendable and runtime efficient.
PathWeigh is available at https://github.org/zurkin1/Pathweigh and is released under MIT license. A sample Python notebook is provided with examples of running the tool.
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Livne, D., Efroni, S. (2022). PathWeigh – Quantifying the Behavior of Biochemical Pathway Cascades. In: Rojas, I., Valenzuela, O., Rojas, F., Herrera, L.J., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2022. Lecture Notes in Computer Science(), vol 13347. Springer, Cham. https://doi.org/10.1007/978-3-031-07802-6_29
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DOI: https://doi.org/10.1007/978-3-031-07802-6_29
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