Quantitative Biology

, Volume 6, Issue 4, pp 321–333 | Cite as

Subnetwork identification and chemical modulation for neural regeneration: A study combining network guided forest and heat diffusion model

  • Hui Wang
  • Gang Wang
  • Li-Da Zhu
  • Xuan Xu
  • Bo DiaoEmail author
  • Hong-Yu ZhangEmail author
Research Article



The induction of neural regeneration is vital to the repair of spinal cord injury (SCI). While compared with peripheral nervous system (PNS), the regenerative capacity of the central nervous system (CNS) is extremely limited. This indicates that modulating the molecular pathways underlying PNS repair may lead to the discovery of potential treatment for CNS injury.


Based on the gene expression profiles of dorsal root ganglion (DRG) after a sciatic nerve injury, we utilized network guided forest (NGF) to rank genes in terms of their capacity of distinguishing injured DRG from sham-operated controls. Gene importance scores deriving from NGF were used as initial heat in a heat diffusion model (HotNet2) to infer the subnetworks underlying neural regeneration in the DRG. After potential regulators of the subnetworks were found through Connectivity Map (cMap), candidate compounds were experimentally evaluated for their capacity to regenerate the damaged neurons.


Gene ontology analysis of the subnetworks revealed ubiquinone biosynthetic process is crucial for neural regeneration. Moreover, almost half of the genes in these subnetworks are found to be related to neural regeneration via text mining. After screening compounds that are likely to modulate gene expressions of the subnetworks, three compounds were selected for the experiment. Of them, trichostatin A, a histone deacetylase inhibitor, was validated to enhance neurite outgrowth in vivo via an optic nerve crush mouse model.


Our study identified subnetworks underlying neural regeneration, and validated a compound can promote neurite outgrowth by modulating these subnetworks. This work also suggests an alternative approach for drug repositioning that can be easily extended to other disease phenotypes.


network guided forest HotNet2 neural regeneration axon growth neurotrophic factors 



This work was supported by the Fundamental Research Funds for the Central Universities (No. 2662017PY115)

Supplementary material

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40484_2018_159_MOESM2_ESM.pdf (108 kb)
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40484_2018_159_MOESM3_ESM.pdf (931 kb)
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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Hubei Key Laboratory of Agricultural Bioinformatics, College of InformaticsHuazhong Agricultural UniversityWuhanChina
  2. 2.Department of Clinical ExperimentWuhan General Hospital of Guangzhou CommandWuhanChina
  3. 3.Hubei Key Laboratory of Central Nervous System Tumor and InterventionWuhanChina

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