ArticleScientific reports2016
Critical controllability in proteome-wide protein interaction network integrating transcriptome.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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Who cites it
12 citing papers in PubMed.
- Controllability Analysis of Intercellular Protein-Protein Interaction Networks.Computational and structural biotechnology journal · 2026Article
- Target control of linear directed networks based on the path cover problem.Scientific reports · 2024Article
- Measuring criticality in control of complex biological networks.NPJ systems biology and applications · 2024Article
- Domination based classification algorithms for the controllability analysis of biological interaction networks.Scientific reports · 2022Article
- Probabilistic Critical Controllability Analysis of Protein Interaction Networks Integrating Normal Brain Ageing Gene Expression Profiles.International journal of molecular sciences · 2021Article
- Constraint-based models for dominating protein interaction networks.IET systems biology · 2021Article
- Protein-protein interactions of human viruses.Seminars in cell & developmental biology · 2020Review
- Network controllability analysis of intracellular signalling reveals viruses are actively controlling molecular systems.Scientific reports · 2019Article
- Proteome Data Improves Protein Function Prediction in the Interactome ofMolecular & cellular proteomics : MCP · 2018Article
- Critical controllability analysis of directed biological networks using efficient graph reduction.Scientific reports · 2017Article
- Multitype Network-Guided Target Controllability in Phenotypically Characterized Osteosarcoma: Role of Tumor Microenvironment.Frontiers in immunology · 2017Article
- Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability.PloS one · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recently, the number of essential gene entries has considerably increased. However, little is known about the relationships between essential genes and their functional roles in critical network control at both the structural (protein interaction network) and dynamic (transcriptional) levels, in part because the large size of the network prevents extensive computational analysis. Here, we present an algorithm that identifies the critical control set of nodes by reducing the computational time by 180 times and by expanding the computable network size up to 25 times, from 1,000 to 25,000 nodes. The developed algorithm allows a critical controllability analysis of large integrated systems composed of a transcriptome- and proteome-wide protein interaction network for the first time. The data-driven analysis captures a direct triad association of the structural controllability of genes, lethality and dynamic synchronization of co-expression. We believe that the identified optimized critical network control subsets may be of interest as drug targets; thus, they may be useful for drug design and development.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.