SQUAD
The SQUAD Method for the Qualitative Modeling of Regulatory Networks. The wealth of molecular information provided by high-throughput technologies has enhanced the efforts dedicated to the reconstruction of regulatory networks in diverse biological systems. This information, however, has proven to be insufficient for the construction of quantitative models due to the absence of sufficiently accurate measurements of kinetic constants. As a result, there have been efforts to develop methodologies that permit the use of qualitative information about patterns of expression to infer the regulatory networks that generate such patterns. One of these approaches is the SQUAD method, which approximates a Boolean network with the use of a set of ordinary differential equations. The main benefit of the SQUAD method over purely Boolean approaches is the possibility of evaluating the effect of continuous external signals, which are pervasive in biological phenomena. A brief description and code on how to implement this method can be found at the following link: https://github.com/caramirezal/SQUADBookChapter.
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References in zbMATH (referenced in 5 articles )
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Sorted by year (- von Stechow, Louise (ed.); Delgado, Alberto Santos (ed.): Computational cell biology. Methods and protocols (2018)
- Jin, Suoqin; Wu, Fang-Xian; Zou, Xiufen: Domain control of nonlinear networked systems and applications to complex disease networks (2017)
- Mendoza, Luis: A virtual culture of CD4+ T lymphocytes (2013)
- Sánchez-Corrales, Yara-Elena; Álvarez-Buylla, Elena R.; Mendoza, Luis: The \textitArabidopsisthaliana flower organ specification gene regulatory network determines a robust differentiation process (2010)
- Di Cara, Alessandro; Garg, Abhishek; De Micheli, Giovanni; Xenarios, Ioannis; Mendoza, Luis: Dynamic simulation of regulatory networks using SQUAD (2007) ioport