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Susanto, Gregorius Nugroho
Jurusan Biologi Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Lampung
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Materials Science & Nanotechnology Medicine & Pharmacology Physics Public Health Social Sciences Veterinary Other

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Journal : JOIV : International Journal on Informatics Visualization

 1 
A New Feature Extraction Approach in Classification for Improving the Accuracy of Proteins Damayanti, -; Lumbanraja, Favorisen Rosyking; Junaidi, Akmal; Sutyarso, -; Susanto, Gregorius Nugroho; Megawaty, Dyah Ayu
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2589

Abstract

Proteins play a vital role in life as essential macromolecules, consisting of linear heteromeric biopolymers formed by amino acids covalently bonded through peptide bonds. They contribute to cell development and bolster the body's defense mechanisms. Post-translational modification processes, such as glycosylation, are necessary for proteins to function optimally. Glycosylation involves adding sugar groups to proteins, playing a critical role in various protein folding processes. Dysregulation of protein glycosylation can lead to diseases like Alzheimer's and cancer. Manual classification of glycosylated proteins is time-consuming, necessitating a faster approach. This study aims to expedite glycosylated protein classification using novel methods like AAindex, CTD, SABLE, hydrophobicity, and PseAAC for increased accuracy, comparing them with existing approaches. The dataset comprises protein sequences sourced from the openly accessible UniProt database. Results demonstrate that glycosylated protein prediction achieved 100% accuracy, surpassing previous approaches. Several features contributed to this improvement, with Hydrophobicity making a significant contribution at 24%, and PseAAC making the most significant contribution at 40% among the five extraction methods developed.
Co-Authors - Damayanti Abdullah Aman Damai Agus Setiawan Agus Setyawan Akmal Junaidi Akmalia Rahmani Alqoriani A, Ostarica Andriyani, Agista Arlanda, Revilarita Arofah, Nur Lailatul Ayu Tiara Fitri Ayuandira, Niken Ayuni, Ubaid Jan Azizah Azizah Banowati, Nurmaya Tri Choirun Nisa Elfa Verda Puspita Endah Setyaningrum Endah Setyaningrum Endang L. Widiastuti Endang Linirin Widiastuti Endang Linirin Widiastuti Endang Linirin Widiastuti Farisi, Salman Favorisen R. Lumbanraja Gurum Ahmad Pauzi Hendri Busman Hendri Busman Indra Gumay Febryano Irawan, Tazranisa Indy Isni Uswatun Khasanah Juliasih, Ni Luh Gede Ratna Junaidi Junaidi Juriani Juriani Kanedi, Kanedi Kusuma Handayani, Kusuma Lestari, Sepnina Like M Husien Ferdiansyah M. Kanedi Madi Hartono Maya Riantini, Maya Mayaguezz, Henky Megawaty, Dyah Ayu Mohammad Kanedi Muhammad Zulhafid Munti Sarida Nababan, Yolanda Nazma, Anya Khalisza Putri Nuning Nurcahyani Nur Lailatul Arofah Nurul Khasanah, Nurul Okta Ferli Suryadi Ostarica Alqoriani A. Pribadie, Aldi Indra Prihadhi, Eka Primasari Pertiwi Priyambodo Priyambodo Puspitaningsih N.W., Rr. Etty Qadar Hasani Ramadhina, Melati Rizki Rani Setiana Revanza, M. Zidan Romaskila, Ulfanida Rr. Etty Puspitaningsih N.W. Sa'diah, Annisa Nurul Salman Alfarisi Sari, Mutiara Pradita Sibarani , Marsya Christyanti Slamet Mulyono Sri Murwani Sumardi . Sumardi, Sumardi Supono Supono Supono Supono Suratman Suratman Suratman Suratman Suratman Umar Sutyarso Sutyarso Sutyarso Sutyarso Sutyarso, - Teguh Ismail Tintin Kurtini Tintin Kurtini Tugiyono Tugiyono Tugiyono Tugiyono Tugiyono Tugiyono Tugiyono Tugiyono Utoyo , Laji Wahid Giantara Widiastuti, Endang Linirin Yolanda Nababan Yudha Trinoegraha Adiputra Yuni Astuti Yuni Astuti Zainal Abidin