Abstract
Theoretical models describing complex biological phenomena have been accumulating. However, most of these models have been created with hypothetical parameter determination without seeing actual cell reactions. The parameter determination requires high-dimensional data monitoring, particularly at the protein level. It has been a difficult task to develop the standard model system because of the lack of an appropriate validation technique. Reverse-phase protein lysate microarray (RPA) is one of the most potent technologies for high-dimensional proteomic monitoring. Therefore, proteomic monitoring by RPA may contribute substantially to develop theoretical protein network models based on experimental validation.
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Acknowledgments
The author particularly thanks Kazushige Ishida, Sundhar Ramalingam, and Brett Spurrier for their contribution for the development of the experimental procedures; and Lynn Young for completing the computational part of the analysis. The support of Teppei Matsuo, Hironobu Noda, Takeshi Iwaya, Miyuki Ikeda, and Go Wakabayashi is greatly appreciated. This work was supported by KAKENHI (Grant-in-Aid for Scientific Research (C), 50316387 and 50453311).
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Nishizuka, S.S. (2011). Reverse-Phase Protein Lysate Microarray (RPA) for the Experimental Validation of Quantitative Protein Network Models. In: Korf, U. (eds) Protein Microarrays. Methods in Molecular Biology, vol 785. Humana Press. https://doi.org/10.1007/978-1-61779-286-1_6
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DOI: https://doi.org/10.1007/978-1-61779-286-1_6
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