International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 186 - Number 27 |
Year of Publication: 2024 |
Authors: Saima Khan, Fatema Tuj Jahura, Shiplu Hawladar |
10.5120/ijca2024923777 |
Saima Khan, Fatema Tuj Jahura, Shiplu Hawladar . Protein Function Prediction using Protein-Protein Interaction Networks Involving MCL and Majority Rule. International Journal of Computer Applications. 186, 27 ( Jul 2024), 1-7. DOI=10.5120/ijca2024923777
Protein is essential for all life processes, playing crucial roles such as providing structural integrity to the body and facilitating the transport of various substances within it. Understanding protein functions is critical for advancing biological science, as it aids in the improvement, regulation, and maintenance of numerous biological systems. Various methods exist to predict the functions of proteins with unknown roles, but many are time-consuming, complex, and costly. This study introduces a novel method that offers higher accuracy in predicting protein functions. It is easier, faster, and less expensive compared to many existing techniques. This new approach employs the Markov Clustering (MCL) Algorithm to cluster protein networks, followed by the application of the majority rule [3, 36] to predict protein functions.