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Prediction of Protein Structural Class by Functional Link Artificial Neural Network Using Hybrid Feature Extraction Method

  • Bishnupriya Panda
  • Ambika Prasad Mishra
  • Babita Majhi
  • Minakhi Rout
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8298)

Abstract

During last few decades’ accurate prediction of protein structural class has been a challenging problem. Efficient and meaningful representation of protein molecule plays a significant role. In this paper Chou’s pseudo amino acid composition along with amphiphillic correlation factor and the spectral characteristics of the protein has been used to represent protein data. Thus a protein sample is represented by a set of discrete components which incorporate both the sequence order and the sequence length effects. On the basis of such a statistical framework a simple functionally linked artificial neural network has been used for structural class prediction.

Keywords

AAC AmPseAAC DCTAmPseAAC Functional link artificial neural network (FLANN) Protein Domain Structural Class 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Bishnupriya Panda
  • Ambika Prasad Mishra
  • Babita Majhi
  • Minakhi Rout

There are no affiliations available

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