By Topic

Classification of proteins in intracellular and secretory pathway using global descriptors of amino acid sequence

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Geetha Govindan ; State Inter-University Centre for Excellence in Bioinformatics, University of Kerala, Thiruvananthapuram, India ; Achuthsankar S. Nair

It is widely recognized that the information from the amino acid sequence can serve as crucial pointers in predicting subcellular location of proteins. We introduce a new feature vector for predicting proteins targeted to various compartments in the intracellular and secretory pathway from protein sequence. Features are based on the global Composition, Transition and Distribution (CTD) of amino acid attributes such as hydrophobicity, normalized van der Waals volume, polarity, polarizability, charge, secondary structure and solvent accessibility. Sequences are considered in three equal parts and the features are extracted separately for all the three parts. Based on the feature vectors, we have trained a Support Vector Machine to classify intracellular and secretory proteins. Our method gives an accuracy of 92% in human, 88% in plant and 95% in fungi with independent dataset at root level of the protein sorting pathway.

Published in:

Information and Communication Technologies (WICT), 2011 World Congress on

Date of Conference:

11-14 Dec. 2011