N-Glycosylation plays a very important role in various processes like quality control of proteins produced in ER, transport of proteins and in disease control.The experimental elucidation of N-Glycosylation sites is expensive and laborious process. In this work we build models for identification of potential N-Glycosylation sites in proteins based on sequence and structural features.The best model has cross validation accuracy rate of 72.81%. © 2009 Springer-Verlag Berlin Heidelberg.

Valadi Krishnamoorthy Jayaraman

Center for Informatics

S. Karnik

J. Mitra

A. Singh

B.D. Kulkarni

V. Sundarajan

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Identification of N-Glycosylation Sites with Sequence and Structural Features Employing Random Forests

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Identification of N-glycosylation sites with sequence and structural features employing random forests