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Weighted measures based on maximizing deviation for alignment-free sequence comparison

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  • Qian, Kun
  • Luan, Yihui

Abstract

Alignment-free sequence comparison is becoming fairly popular in many fields of computational biology due to less requirements for sequence itself and computational efficiency for a large scale of sequence data sets. Especially, the approaches based on k-tuple like D2, D2S and D2∗ are used widely and effectively. However, these measures treat each k-tuple equally without accounting for the potential importance differences among all k-tuples. In this paper, we take advantage of maximizing deviation method proposed in multiple attribute decision making to evaluate the weights of different k-tuples. We modify D2, D2S and D2∗ with weights and test them by similarity search and evaluation on functionally related regulatory sequences. The results demonstrate that the newly proposed measures are more efficient and robust compared to existing alignment-free methods.

Suggested Citation

  • Qian, Kun & Luan, Yihui, 2017. "Weighted measures based on maximizing deviation for alignment-free sequence comparison," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 235-242.
    • Handle: RePEc:eee:phsmap:v:481:y:2017:i:c:p:235-242
    DOI: 10.1016/j.physa.2017.04.062
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    References listed on IDEAS

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    1. Yu, Hong-Jie & Huang, De-Shuang, 2012. "Novel graphical representation of genome sequence and its applications in similarity analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6128-6136.
    2. Li, Chun & Yang, Yan & Jia, Meiduo & Zhang, Yingying & Yu, Xiaoqing & Wang, Changzhong, 2014. "Phylogenetic analysis of DNA sequences based on k-word and rough set theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 162-171.
    3. Liao, Bo & Xiang, Qilin & Cai, Lijun & Cao, Zhi, 2013. "A new graphical coding of DNA sequence and its similarity calculation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4663-4667.
    4. Tiee-Jian Wu & Ya-Ching Hsieh & Lung-An Li, 2001. "Statistical Measures of DNA Sequence Dissimilarity under Markov Chain Models of Base Composition," Biometrics, The International Biometric Society, vol. 57(2), pages 441-448, June.
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    Cited by:

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