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RNA Sequences Similarities Analysis by Cross-Correlation Function

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Bio-inspired Computing: Theories and Applications (BIC-TA 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 952))

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Abstract

According to concept of dinucleotide, this paper proposes a graphical representation of dinucleotide. In this way, the graphical representation can not only show sequence one-to-one, but also can be easily converted into the original sequence. Then this paper extracts cross- correlation function to characterize the degree of similarity from representation of dinucleotide. After applying our approach to nine kinds of viruses, it can be found that our conclusion is almost consistent with the reported data. After the analysis with the method of inter-class, it can be found that our data can classify different viruses well. Our approach can more easily extract data and distinguish the different classes than previous results.

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Acknowledgement

This work is supported by the National Natural Science Foundation of China (Nos. 61425002, 61751203, 61772100, 61702070, 61672121, 61572093), Program for Changjiang Scholars and Innovative Research Team in University (No. IRT_15R07), the Program for Liaoning Innovative Research Team in University (No. LT2015002).

Author information

Authors and Affiliations

  1. Key Laboratory of Advanced Design and Intelligent Computing, Dalian University, Ministry of Education, Dalian, 116622, China

    Shanshan Xing, Bin Wang, Xiaopeng Wei, Changjun Zhou & Qiang Zhang

  2. School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, China

    Xiaopeng Wei & Qiang Zhang

  3. College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, 321004, China

    Zhonglong Zheng

Authors
  1. Shanshan Xing
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  2. Bin Wang
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  3. Xiaopeng Wei
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  4. Changjun Zhou
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  5. Qiang Zhang
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  6. Zhonglong Zheng
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Corresponding authors

Correspondence to Bin Wang or Qiang Zhang .

Editor information

Editors and Affiliations

  1. Beijing University of Posts and Telecommunications, Beijing, China

    Jianyong Qiao

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Xinchao Zhao

  3. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  4. Beijing University of Posts and Telecommunications, Beijing, China

    Xingquan Zuo

  5. Anhui University, Hefei, China

    Xingyi Zhang

  6. City University of Hong Kong, Kowloon, Hong Kong

    Qingfu Zhang

  7. Beijing University of Posts and Telecommunications, Beijing, China

    Shanguo Huang

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Xing, S., Wang, B., Wei, X., Zhou, C., Zhang, Q., Zheng, Z. (2018). RNA Sequences Similarities Analysis by Cross-Correlation Function. In: Qiao, J., et al. Bio-inspired Computing: Theories and Applications. BIC-TA 2018. Communications in Computer and Information Science, vol 952. Springer, Singapore. https://doi.org/10.1007/978-981-13-2829-9_9

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  • DOI: https://doi.org/10.1007/978-981-13-2829-9_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2828-2

  • Online ISBN: 978-981-13-2829-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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