By Topic

Composition, Transition and Distribution (CTD) — A dynamic feature for predictions based on hierarchical structure of cellular sorting

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 ; Research Scholar, State Inter-University Centre, for Excellence in Bioinformatics, University of Kerala, Thiruvananthapuram ; Achuthsankar S. Nair

Subcellular location of protein is crucial for the dynamic life of cells as it is an important step towards elucidating its function. It is widely recognized that the information from the amino acid sequence can serve as vital pointers in predicting location of proteins. We introduce a new feature vector for predicting proteins targeted to various compartments in the hierarchical structure of cellular sorting pathway from protein sequence. Features are based on the overall 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 of the protein sequences. Classification of protein locations in cellular sorting pathway is achieved through Support Vector Machine. Our method gives an accuracy of 92% in human and 95% in fungi with non redundant test set at root level.

Published in:

2011 Annual IEEE India Conference

Date of Conference:

16-18 Dec. 2011