ArticleGenes2019
A Novel Method for Identifying Essential Genes by Fusing Dynamic Protein⁻Protein Interactive Networks.
Article in Genes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 38 citations in OpenAlex.
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- Antibacterial Drug Discovery: Deep Learning Successes and Challenges through the Structural Biology Lens.Computational and structural biotechnology journal · 2026Review
- Design of Fermentative Technology for the Valorization of Pig Bristle Keratins into Biostimulant for Agricultural Applications.ACS agricultural science & technology · 2025Article
- Untangling the Context-Specificity of Essential Genes by Means of Machine Learning: A Constructive Experience.Biomolecules · 2023Article
- A disease-related essential protein prediction model based on the transfer neural network.Frontiers in genetics · 2022Article
- An iteration model for identifying essential proteins by combining comprehensive PPI network with biological information.BMC bioinformatics · 2021Article
- A novel essential protein identification method based on PPI networks and gene expression data.BMC bioinformatics · 2021Article
- A Novel Method for Identifying Essential Proteins Based on Non-negative Matrix Tri-Factorization.Frontiers in genetics · 2021Article
- An Iterative Method for Predicting Essential Proteins Based on Multifeature Fusion and Linear Neighborhood Similarity.Frontiers in aging neuroscience · 2021Article
- Network Embedding the Protein-Protein Interaction Network for Human Essential Genes Identification.Genes · 2020Article
- A Novel Computational Approach for Identifying Essential Proteins From Multiplex Biological Networks.Frontiers in genetics · 2020Article
- Geptop 2.0: An Updated, More Precise, and Faster Geptop Server for Identification of Prokaryotic Essential Genes.Frontiers in microbiology · 2019Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Essential genes play an indispensable role in supporting the life of an organism. Identification of essential genes helps us to understand the underlying mechanism of cell life. The essential genes of bacteria are potential drug targets of some diseases genes. Recently, several computational methods have been proposed to detect essential genes based on the static protein⁻protein interactive (PPI) networks. However, these methods have ignored the fact that essential genes play essential roles under certain conditions. In this work, a novel method was proposed for the identification of essential proteins by fusing the dynamic PPI networks of different time points (called by FDP). Firstly, the active PPI networks of each time point were constructed and then they were fused into a final network according to the networks' similarities. Finally, a novel centrality method was designed to assign each gene in the final network a ranking score, whilst considering its orthologous property and its global and local topological properties in the network. This model was applied on two different yeast data sets. The results showed that the FDP achieved a better performance in essential gene prediction as compared to other existing methods that are based on the static PPI network or that are based on dynamic networks.
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