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Significance of Global Vectors Representation in Protein Sequences Analysis

  • Anon GeorgeEmail author
  • H. B. Barathi Ganesh
  • M. Anand Kumar
  • K. P. Soman
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 31)

Abstract

Understanding the meaning of protein sequences is tedious with human efforts alone. Through this work, we experiment an NLP technique to extract features and give appropriate representation for the protein sequences. In this paper, we have used GloVe representation for the same. A dataset named Swiss-Prot has been incorporated into this work. We were able to create a representation that has comparable ability to understand the semantics of protein sequences compared to the existing ones. We have analyzed the performance of representation by the classification of different protein families in the Swiss-Prot dataset using machine learning technique. The analysis done by us proved the significance of this representation.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Anon George
    • 1
    Email author
  • H. B. Barathi Ganesh
    • 1
    • 2
  • M. Anand Kumar
    • 1
  • K. P. Soman
    • 1
  1. 1.Amrita School of Engineering, Center for Computational Engineering and Networking (CEN), Amrita Vishwa VidyapeethamCoimbatoreIndia
  2. 2.Arnekt Solution Pvt. Ltd.PuneIndia

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