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International Conference of Pioneering Computer Scientists, Engineers and Educators

ICPCSEE 2018: Data Science pp 250–262Cite as

The Algorithms of Weightening Based on DNA Sticker Model

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 902))

Abstract

The algorithm of weightening serves as building blocks for the construction of more complex sticker algorithms. However, due to the previous weightening algorithms with single function, so the scope of solving problems is small. To this end, we propose three multifunctional weightening algorithms which running on the sticker machines. First, the basic operators of the algorithms consist of the pre-defined operations of the sticker model. Second, one can obtain the new algorithms by organizing these basic operations in a certain logical way. At last, running these new algorithms, we can obtain the corresponding functional results by reading the biochemical reaction products.

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Acknowledgement

This work has been supported by NSFC under grant No. U1204608 and No. 61572444.

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Authors and Affiliations

  1. Zhengzhou University, Zhengzhou, Henan Province, China

    Chunyan Zhang, Weijun Zhu & Qinglei Zhou

Authors
  1. Chunyan Zhang
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  2. Weijun Zhu
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  3. Qinglei Zhou
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Corresponding author

Correspondence to Chunyan Zhang .

Editor information

Editors and Affiliations

  1. Zhengzhou University, Zhengzhou, Henan, China

    Qinglei Zhou

  2. Xidian University, Xi’an, Shaanxi, China

    Qiguang Miao

  3. Harbin Institute of Technology, Harbin, China

    Hongzhi Wang

  4. Harbin University of Science and Technology, Harbin, China

    Wei Xie

  5. Zhengzhou Institute of Technology, Zhengzhou, China

    Yan Wang

  6. National Academy of Guo Ding Institute of Data Science, Beijing, China

    Zeguang Lu

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Cite this paper

Zhang, C., Zhu, W., Zhou, Q. (2018). The Algorithms of Weightening Based on DNA Sticker Model. In: Zhou, Q., Miao, Q., Wang, H., Xie, W., Wang, Y., Lu, Z. (eds) Data Science. ICPCSEE 2018. Communications in Computer and Information Science, vol 902. Springer, Singapore. https://doi.org/10.1007/978-981-13-2206-8_22

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  • DOI: https://doi.org/10.1007/978-981-13-2206-8_22

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2205-1

  • Online ISBN: 978-981-13-2206-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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