Pendekatan Teori Graf untuk Analisis Jaringan Interaksi Protein-Protein
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Abstract
Jaringan interaksi protein-protein merupakan hal penting pada setiap proses yang terjadi dalam sel biologis karena dapat digunakan untuk mempelajari kondisi fisiologis sel ketika berada dalam keadaan normal atau tidak normal. Di sisi lain, infrastruktur komputasi telah berada di era yang cukup memadai untuk menyimpan data hasil eksperimen dari berbagai tempat dan waktu. Namun data yang terkumpul perlu diolah dan dianalisis dengan cara yang tepat agar menghasilkan pengetahuan atau wawasan baru yang bermanfaat. Penelitian ini bertujuan melakukan pendekatan agar data jaringan interaksi protein-protein yang terkumpul di database menjadi informasi yang bermakna. Pendekatan dilakukan menggunakan teori graf dengan studi kasus data protein virus SARS-Cov-2. Metode yang digunakan adalah metode in-silico dengan data sekunder berasal dari database bereputasi yang dapat diakses publik. Hasil penelitian berupa daftar protein-protein paling berpengaruh pada virus SARS-Cov-2 berdasarkan parameter-parameter umum yang digunakan dalam ilmu jaringan.
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