ArticleBioMed research international2017
Identifying and Analyzing Novel Epilepsy-Related Genes Using Random Walk with Restart Algorithm.
Article in BioMed research international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 31 citations in OpenAlex.
- Transcriptional and neurotransmitter signatures associated with regional gray matter alterations in juvenile myoclonic epilepsy.Frontiers in molecular neuroscience · 2026Article
- Prediction of drug's anatomical therapeutic chemical (ATC) code by constructing biological profiles of ATC codes.BMC bioinformatics · 2025Article
- Interplay of epilepsy and long-term potentiation: implications for memory.Frontiers in neuroscience · 2024Review
- Kv7/KCNQ potassium channels in cortical hyperexcitability and juvenile seizure-related death in Ank2-mutant mice.Nature communications · 2023Article
- PWN: enhanced random walk on a warped network for disease target prioritization.BMC bioinformatics · 2023Article
- Mechanisms underlying the role of ankyrin-B in cardiac and neurological health and disease.Frontiers in cardiovascular medicine · 2022Review
- Absence of RNA-binding protein FXR2P prevents prolonged phase of kainate-induced seizures.EMBO reports · 2021Article
- Multiplex gene and phenotype network to characterize shared genetic pathways of epilepsy and autism.Scientific reports · 2021Article
- Cystatin B is essential for proliferation and interneuron migration in individuals with EPM1 epilepsy.EMBO molecular medicine · 2020Article
- Ankyrin B and Ankyrin B variants differentially modulate intracellular and surface Cav2.1 levels.Molecular brain · 2019Article
- INTERSPIA: a web application for exploring the dynamics of protein-protein interactions among multiple species.Nucleic acids research · 2018Article
- Novel human microbe-disease association prediction using network consistency projection.BMC bioinformatics · 2017Article
- Identifying novel fruit-related genes in Arabidopsis thaliana based on the random walk with restart algorithm.PloS one · 2017Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As a pathological condition, epilepsy is caused by abnormal neuronal discharge in brain which will temporarily disrupt the cerebral functions. Epilepsy is a chronic disease which occurs in all ages and would seriously affect patients' personal lives. Thus, it is highly required to develop effective medicines or instruments to treat the disease. Identifying epilepsy-related genes is essential in order to understand and treat the disease because the corresponding proteins encoded by the epilepsy-related genes are candidates of the potential drug targets. In this study, a pioneering computational workflow was proposed to predict novel epilepsy-related genes using the random walk with restart (RWR) algorithm. As reported in the literature RWR algorithm often produces a number of false positive genes, and in this study a permutation test and functional association tests were implemented to filter the genes identified by RWR algorithm, which greatly reduce the number of suspected genes and result in only thirty-three novel epilepsy genes. Finally, these novel genes were analyzed based upon some recently published literatures. Our findings implicate that all novel genes were closely related to epilepsy. It is believed that the proposed workflow can also be applied to identify genes related to other diseases and deepen our understanding of the mechanisms of these diseases.
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