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Journal : KLIK: Kajian Ilmiah Informatika dan Komputer

Integrasi data Protein-Protein Interactions dan Pathway untuk Menentukan Score pada pathway Menggunakan Analisis Graf Lailan Sahrina Hasibuan; Ahmad Fariqi; Lilik Prayitno; Melly Br Bangun
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.932

Abstract

The development of molecular biology technology produces large amounts of omics data. Integration of omics data is useful for the analysis of biological processes at the molecular level, such as protein expression, drug mechanisms against diseases, and mechanisms of inheritance. This study aims to integrate protein molecular biology data through protein-protein interactions (PPIs), pathways, modules and orthology, to calculate pathway scores. The score calculation uses the degree calculation on the graph concept. Proteins, pathways, modules and orthologs act as nodes, while the interactions between them act as edges. Furthermore, according to the concept of a graph, nodes with a high degree represent nodes that have an important role in a graph. Based on this concept, the most important pathway related to a protein is the pathway with the highest degree in a multipartite graph formed by PPIs, modules, orthologs and pathways. The output of this study is a package in the R language to integrate data on molecular biology of proteins, pathways, modules and orthology, then displays the pathways that have the most role in protein based on the order of the highest score. This package was tested using protein Insulin (INS) and Xanthine dehydrogenase (XDH) inputs. The results of calculating the score on the pathway for INS produced the pathway with the highest score, namely MAPK signaling pathway (0.18) lane 1, Pathways in cancer (0.137) lane 2, Ubiquitin mediated proteolysis (0.28) lane 3. XDH protein input produces Purine metabolism pathway (0.67) lane 1, Metabolic pathways (0.48) lane 2 and Purine metabolism (0.23) lane 3. These results can be used for enrichment analysis regarding the relationship between proteins and pathways.
Co-Authors Adelina Irmayani Lubis Agustin, Angelica Ahmad Fariqi Amenobelia Sitepu Ayuning, Vista Cindy Nadya Damayanti, Nina Afria Dian Septiana Dita, Disa Martia Egner Bernard Pribadi Elis Nina Herliyana Elizon Nainggolan Firdaus, Lucky Marcelino Fitria Cahaya Fuzy Yustika Manik Fuzy Yustika Manik, Fuzy Yustika Ginting, Rehia Angelica Handayani, Silvia Mariah Harahap, Nazwa Malika Hasibuan, Lailan Sahrina Hasibuan, Maria Angel Imelda Sari Ira Sefi Andini Khairani, Dewi Lestania Simatupang Lidya Natasya Lilik Prayitno Lumbangaol, Hermawan Mahfuzi Irwan Marisa Nabila Muchtar, Chairul Omar Muhammad Adib Ahsani Muhammad Takwin Machmud Muliyani Natalia Silalahi Natalia Silalahi, Natalia Ndona, Margaretha Djanius Nehe, Gian Devina Gracia Nina Afria Damayanti Noer Risky Ramadhani Nurhudayah Manjani Oriza Salsabila Padmawati, Fitri Pakpahan, Fanny Grisella Pricilia, Yolanda Purba, Atikah Aulia Purba, Della Priskila Purba, Jon Felix Ramadhani, Noer Risky Reny Furnawati Sitanggang Ridoansih, Thomas Rini Juliani Sipahutar Rista Triwani Rodhiatam Mardiah Damanik Roif Syahli, Naufal Romi Anggun Zefanya Rosdiana Rosdiana Rossikha, Faiza Rossy Nurhasanah Rumahombar, Cindy Natalie Sagala, Angel C Sagala, Annisa Azmi SANI SUSANTI Sani Susanti Santi Nurhasanah Batubara Siagian, Mouces Ferdinan Sianturi, Mian Simangunsong, Yesica Natalia Simanjuntak, Septo Sinaga, Mariana Sipahutar, Rini Juliani Siti Maisaroh Sitorus, Julia Sintya Sondang Dioranta Suci, Delli Syahputra, Dika Dona Syahrial Syahrial SYAHRIAL SYAHRIAL Tessalonika, Jelita Vivaldy, Jeremy Akbar Winda Tarihoran Wulandari, Yunita Dwi Zainuddin Muchtar