Real-world protein particle network reconstruction based on advanced hybrid features

• Autor(a) principal: Gul, Haji
• Data de Publicação: 2022
• Outros Autores: Al-Obeidat, Feras, Tahir, Muhammad, Amin, Adnan, Moreira, Fernando
• Idioma: eng
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: http://hdl.handle.net/11328/4390; https://doi.org/10.1007/978-981-16-7618-5_2
• topic: Reconstruction biological network; Protein–protein interaction; Real-world entity relationship prediction; Complex networks

Biological network proteins are key operational particles that substantially and operationally cooperate to bring out cellular progressions. Protein links with some other biological network proteins to accomplish their purposes. Physical collaborations are commonly referred to by the relationships of domain-level. The interaction among proteins and biological network reconstruction can be predicted based on various methods such as social theory, similarity, and topological features. Operational particles of proteins collaboration can be indirect among proteins based on mutual fields, subsequently particles of proteins involved in an identical biological progression be likely to harbor similar fields. To reconstruct the real-world network of proteins particles, some methods need only the notations of proteins domain, and then, it can be utilized to multiple species. A novel method we have introduced will analyze and reconstruct the real-world network of protein particles. The proposed technique works based on protein closeness, algebraic connectivity, and mutual proteins. Our proposed method was practically tested over different data sets and reported the results. Experimental results clearly show that the proposed technique worked best as compared to other state-of-the-art algorithms.