Nair, Smitha Sunil Kumaran and Subbareddy , NV and Hareesha , K S (2012) AmylPepPred: Amyloidogenic Peptide Prediction tool. Bioinformation, 8 (20). pp. 994-995. ISSN 0973-8894

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Abstract

We present an efficient computational architecture designed using supervised machine learning model to predict amyloid fibril forming protein segments, named AmylPepPred. The proposed prediction model is based on bio-physio-chemical properties of primary sequences and auto-correlation function of their amino acid indices. AmylPepPred provides a user friendly web interface for the researchers to easily observe the fibril forming and non-fibril forming hexmers in a given protein sequence. We expect that this stratagem will be highly encouraging in discovering fibril forming regions in proteins thereby benefit in finding therapeutic agents that specifically aim these sequences for the inhibition and cure of amyloid illnesses.

Item Type:	Article
Additional Information:	© 2012 Biomedical Informatics
Uncontrolled Keywords:	Amyloid fibrils, Bio-physio-chemical properties, Auto-correlation function, Support Vector Machine, AmylPepPred
Subjects:	Engineering > MIT Manipal > Computer Science and Engineering Engineering > MIT Manipal > MCA
Depositing User:	MIT Library
Date Deposited:	09 Feb 2013 10:05
Last Modified:	09 Feb 2013 10:05
URI:	http://eprints.manipal.edu/id/eprint/78325

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