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A novel graphical representation of proteins and its application

Author

Listed:
  • He, Ping-an
  • Wei, Jinzhou
  • Yao, Yuhua
  • Tie, Zhixin

Abstract

On the basis of three kinds of indices of physicochemical properties of twenty amino acids, a novel 3D graphical representation of protein sequences is presented. Then, the improved cumulative distance of the 3D graphical representations is defined in order to compare the proteins for similarity. Furthermore, the efficiency of our approach is illustrated by performing a comparison of similarities/dissimilarities among sequences of the ND5 proteins of nine different species. A correlation and significance analysis is provided to compare our results on similarities/dissimilarities and some other graphical representation results with the ClustalW results on similarities/dissimilarities. The comparison results show that our approach has better correlations with ClustalW for all nine species than other approaches.

Suggested Citation

  • He, Ping-an & Wei, Jinzhou & Yao, Yuhua & Tie, Zhixin, 2012. "A novel graphical representation of proteins and its application," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 93-99.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:1:p:93-99
    DOI: 10.1016/j.physa.2011.08.015
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    References listed on IDEAS

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    1. Li, Chun & Yu, Xiaoqing & Yang, Liu & Zheng, Xiaoqi & Wang, Zhifu, 2009. "3-D maps and coupling numbers for protein sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(9), pages 1967-1972.
    2. Abo el Maaty, Moheb I. & Abo-Elkhier, Mervat M. & Abd Elwahaab, Marwa A., 2010. "3D graphical representation of protein sequences and their statistical characterization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4668-4676.
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    Citations

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    Cited by:

    1. Hou, Wenbing & Pan, Qiuhui & He, Mingfeng, 2016. "A new graphical representation of protein sequences and its applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 996-1002.
    2. Jin, Xin & Nie, Rencan & Zhou, Dongming & Yao, Shaowen & Chen, Yanyan & Yu, Jiefu & Wang, Quan, 2016. "A novel DNA sequence similarity calculation based on simplified pulse-coupled neural network and Huffman coding," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 325-338.
    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. Mahmoodi-Reihani, Mehri & Abbasitabar, Fatemeh & Zare-Shahabadi, Vahid, 2018. "A novel graphical representation and similarity analysis of protein sequences based on physicochemical properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 477-485.
    5. Hou, Wenbing & Pan, Qiuhui & He, Mingfeng, 2014. "A novel representation of DNA sequence based on CMI coding," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 409(C), pages 87-96.
    6. Ma, Tingting & Liu, Yuxin & Dai, Qi & Yao, Yuhua & He, Ping-an, 2014. "A graphical representation of protein based on a novel iterated function system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 21-28.

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    2. Mahmoodi-Reihani, Mehri & Abbasitabar, Fatemeh & Zare-Shahabadi, Vahid, 2018. "A novel graphical representation and similarity analysis of protein sequences based on physicochemical properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 477-485.
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