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Automated Enzyme Function Classification Based on Pairwise Sequence Alignment Technique

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 370)


Enzymes are important in our life due to its importance in the most biological processes. Thus, classification of the enzyme’s function is vital to save efforts and time in the labs. In this paper, we propose an approach based on sequence alignment to compute the similarity between any two sequences. In the proposed approach, two different sequence alignment methods are used, namely, local and global sequence alignment. There are different score matrices such as BLOSUM and PAM are used in the local and global alignment to calculate the similarity between the unknown sequence and each sequence of the training sequences. The results which obtained were acceptable to some extent compared to previous studies that have surveyed.


  • Enzyme
  • Classification
  • Prediction
  • Global alignment
  • Local alignment
  • PAM

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Sharif, M.M., Tharwat, A., Hassanien, A.E., Hefeny, H.A. (2015). Automated Enzyme Function Classification Based on Pairwise Sequence Alignment Technique. In: Abraham, A., Jiang, X., Snášel, V., Pan, JS. (eds) Intelligent Data Analysis and Applications. Advances in Intelligent Systems and Computing, vol 370. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21205-0

  • Online ISBN: 978-3-319-21206-7

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