ArticleFrontiers in bioinformatics2022
Identification of Biomarker in Brain-specific Gene Regulatory Network Using Structural Controllability Analysis.
Article in Frontiers in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- How quantum computing can enhance biomarker discovery.Patterns (New York, N.Y.) · 2025Review
- A Rare Case of Large-Cell Neuroendocrine Carcinoma Metastasizing to the Brain: A Case Report.Cureus · 2024Article
- Target control of linear directed networks based on the path cover problem.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain tumor research has been stapled for human health while brain network research is crucial for us to understand brain activity. Here the structural controllability theory is applied to study three human brain-specific gene regulatory networks, including forebrain gene regulatory network, hindbrain gene regulatory network and neuron associated cells cancer related gene regulatory network, whose nodes are neural genes and the edges represent the gene expression regulation among the genes. The nodes are classified into two classes: critical nodes and ordinary nodes, based on the change of the number of driver nodes upon its removal. Eight topological properties (out-degree
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