Snake Toxin Classification using Neural Networks

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-40 Number-2
Year of Publication : 2016
Authors : Akash Nag, Sunil Karforma
  10.14445/22312803/IJCTT-V40P114

MLA

Akash Nag, Sunil Karforma "Snake Toxin Classification using Neural Networks". International Journal of Computer Trends and Technology (IJCTT) V40(2):78-83, October 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
In this paper, a method is presented for classifying snake toxins into neurotoxins, cytotoxins or cardiotoxins, using a four-stage neural network. A training phase was used to teach the network to recognize the type of toxin based on the number of amino acid residues between the disulphide bridges, on a sample set of 139 snake toxins. When the trained network was used to classify a set of 239 toxins, the system achieved an accuracy of 74%.

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Keywords
snake toxins, snake venom, neurotoxin, cytotoxin, cardiotoxin, artificial neural networks, classification, bioinformatics.