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Issue title: Bio-Inspired Computing: Theories and Applications (BIC-TA 2017)
Guest editors: Linqiang Pan, Mario J. Pérez-Jiménez and Gexiang Zhang
Article type: Research Article
Authors: Yang, Jinga; * | Yin, Zhi-xiangb; † | Cui, Jian-zhongc | Huang, Kai-fengd
Affiliations: [a] School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, China. [email protected] | [b] School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, China. [email protected] | [c] School of Electronic and Information Engineering, Anhui University of Science and Technology, Huainan, China | [d] School of mechanical and electrical engineering, Huainan Normal University, Huainan, China
Correspondence: [†] Address for correspondence: School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, China
Note: [*] This project is supported by National Natural Science Foundation of China (No.61702008, No.61672001) and National Natural Science Foundation of Anhui (No.1808085MF193).
Abstract: Detecting the quality of drinking water is very important in researching the current status and predicting trends of variation, as well as fundamentally solving the water pollution problem. Recently, the application and development of biosensor provide a powerful analytical tool for detecting pollutants of drinking water, but high selectivity, specificity, short response time, and low cost are particularly desired in the detection process. In this paper, RNA molecules in combination with nano-gold and magnetic nano-particles were proposed as design strategies of the biosensor. The proposed designs have distinct advantages over conventional biosensor in the following aspects: the high affinity capacity, sensitivity, and practicability. Our work provided an alternative method to monitor the environment of drinking water, and may find applications in various monitoring fields.
Keywords: RNA biosensor, magnetic nano-particle, gold nano-particle, environmental monitoring
DOI: 10.3233/FI-2019-1768
Journal: Fundamenta Informaticae, vol. 164, no. 2-3, pp. 289-298, 2019
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