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All Journal Journal of Data Science and Software Engineering
Rudy Herteno
Ilmu Komputer FMIPA ULM
Computer Science & IT

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IMPLEMENTATION OF AAC AND DC FEATURE EXTRACTION FOR CLASSIFICATION OF LYSINE PROTEIN ACETYLATION USING THE SUPPORT VECTOR MACHINE METHOD Annisa Rizqiana; Mohammad Reza Faisal; Favorisen Rosyking Lumbanraja; Muliadi; Rudy Herteno
Journal of Data Science and Software Engineering Vol 2 No 01 (2021)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Abstract

Post-Translational Modification (PTM) is a change that occurs in the chemical structure of a protein. One type of PTM is acetylation which commonly occurs in lysine proteins where this type of PTM plays an important role in biological processes. Existing research has identified lysine acetylation using computational methods, which is classification. Methods for protein classification have been developed, but much remains to be explored to identify lysine acetylation. Protein classification begins with extracting protein sequences into numerical features with protein descriptors which in this study used Amino Acid Composition (AAC) and Dipeptide Composition (DC). Furthermore, protein classification is carried out using the Support Vector Machine method. Support Vector Machine is a classification method that can be used for protein identification. This study provides the best performance results on the use of the combination of AAC and DC descriptors, which is 76.20%.
Co-Authors Annisa Rizqiana Favorisen R. Lumbanraja Muhammad Reza Faisal, Muhammad Reza Muliadi