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

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Abstract

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.

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APA

Karnik, S., Mitra, J., Singh, A., Kulkarni, B. D., Sundarajan, V., & Jayaraman, V. K. (2009). Identification of N-glycosylation sites with sequence and structural features employing random forests. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5909 LNCS, pp. 146–151). https://doi.org/10.1007/978-3-642-11164-8_24

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