Journal of Data Science and Software Engineering
Vol 2 No 01 (2021)

IMPLEMENTATION OF AAC AND DC FEATURE EXTRACTION FOR CLASSIFICATION OF LYSINE PROTEIN ACETYLATION USING THE SUPPORT VECTOR MACHINE METHOD

Annisa Rizqiana (Universitas Lambung Mangkurat)
Mohammad Reza Faisal (Ilmu Komputer FMIPA ULM)
Favorisen Rosyking Lumbanraja (Ilmu Komputer FMIPA Unila)
Muliadi (Ilmu Komputer FMIPA ULM)
Rudy Herteno (Ilmu Komputer FMIPA ULM)



Article Info

Publish Date
03 Mar 2021

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%.

Copyrights © 2021






Journal Info

Abbrev

integer

Publisher

Subject

Computer Science & IT

Description

Journal of Data Science and Software Engineering adalah jurnal yang dikelola oleh program studi Ilmu Komputer Universitas Lambung Mangkurat untuk mempublikasikan artikel ilmiah mahasiswa tugas akhir. Terbit tiga kali dalam ...