Determining the Secondary Structure of Elapid Toxins using Multi-Layer Perceptrons and Kohonen Networks

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Akash Nag, Sunil Karforma

Abstract

In this paper, a two-stage neural network consisting of a feed-forward neural network and a Kohonen self-organizing map, has been used to predict secondary structure. We have applied our methods to determine the structure of 245 proteins containing neurotoxins, cytotoxins, cardiotoxins and three-finger toxins, derived from venoms of Elapid snakes. In doing so, the system achieved a Q3 score of 70%, which is quite remarkable.

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How to Cite
, A. N. S. K. (2018). Determining the Secondary Structure of Elapid Toxins using Multi-Layer Perceptrons and Kohonen Networks. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 4(4), 345–348. Retrieved from https://ijfrcsce.org/index.php/ijfrcsce/article/view/1525
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