Publication: Topological augmentation to infer hidden processes in biological systems
Topological augmentation to infer hidden processes in biological systems
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Sunnaker, M., Zamora-Sillero, E., de Lomana, A. L. G., Rudroff, F., Sauer, U., Stelling, J., & Wagner, A. (2014). Topological augmentation to infer hidden processes in biological systems. Bioinformatics, 30(2), 221–227. https://doi.org/10.1093/bioinformatics/btt638
Abstract
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MOTIVATION: A common problem in understanding a biochemical system is to infer its correct structure or topology. This topology consists of all relevant state variables-usually molecules and their interactions. Here we present a method called topological augmentation to infer this structure in a statistically rigorous and systematic way from prior knowledge and experimental data. RESULTS: Topological augmentation starts from a simple model that is unable to explain the experimental data and augments its topology by adding new terms th
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- Sunnaker, M
- Zamora-Sillero, E
- de Lomana, A Lopez Garcia
- Rudroff, F
- Sauer, U
- Stelling, J
- Wagner, A
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Sunnaker, M., Zamora-Sillero, E., de Lomana, A. L. G., Rudroff, F., Sauer, U., Stelling, J., & Wagner, A. (2014). Topological augmentation to infer hidden processes in biological systems. Bioinformatics, 30(2), 221–227. https://doi.org/10.1093/bioinformatics/btt638
