A computational method using the random walk with restart algorithm for identifying novel epigenetic factors
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Epigenetic regulation has long been recognized as a significant factor in various biological processes, such as development, transcriptional regulation, spermatogenesis, and chromosome stabilization. Epigenetic alterations lead to many human diseases, including cancer, depression, autism, and immune system defects. Although efforts have been made to identify epigenetic regulators, it remains a challenge to systematically uncover all the components of the epigenetic regulation in the genome level using experimental approaches. The advances of constructing protein–protein interaction (PPI) networks provide an excellent opportunity to identify novel epigenetic factors computationally in the genome level. In this study, we identified potential epigenetic factors by using a computational method that applied the random walk with restart (RWR) algorithm on a protein–protein interaction (PPI) network using reported epigenetic factors as seed nodes. False positives were identified by their specific roles in the PPI network or by a low-confidence interaction and a weak functional relationship with epigenetic regulators. After filtering out the false positives, 26 candidate epigenetic factors were finally accessed. According to previous studies, 22 of these are thought to be involved in epigenetic regulation, suggesting the robustness of our method. Our study provides a novel computational approach which successfully identified 26 potential epigenetic factors, paving the way on deepening our understandings on the epigenetic mechanism.
KeywordsEpigenetic regulation Epigenetic factor Random walk with restart Protein–protein interaction network
The random walk with restart algorithm
Maximum function score
Maximum interaction score
Kyoto encyclopedia of genes and genomes
Compliance with ethical standards
This study was supported by the National Natural Science Foundation of China (31371335, 31701151), Natural Science Foundation of Shanghai (17ZR1412500), Shanghai Sailing Program and The Youth Innovation Promotion Association of Chinese Academy of Sciences (CAS) (2016245).
Conflict of interest
All authors declare that they have no conflict of interest.
This article does not contain any studies with human participants performed by any of the authors.
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