Introduction: Over the past 10 years, epilepsy genetics has made dramatic progress. This study aimed to analyze the knowledge structure and the advancement of epilepsy genetics over the past decade based on co-word analysis of medical subject headings (MeSH) terms. Methods: Scientific publications focusing on epilepsy genetics from the PubMed database (January 2009–December 2018) were retrieved. Bibliometric information was analyzed quantitatively using Bibliographic Item Co-Occurrence Matrix Builder (BICOMB) software. A knowledge social network analysis and publication trend based on the high-frequency MeSH terms was built using VOSviewer. Results: According to the search strategy, a total of 5185 papers were included. Among all the extracted MeSH terms, 86 high-frequency MeSH terms were identified. Hot spots were clustered into 5 categories including: “ion channel diseases,” “beyond ion channel diseases,” “experimental research & epigenetics,” “single nucleotide polymorphism & pharmacogenetics,” and “genetic techniques”. “Epilepsy,” “mutation,” and “seizures,” were located at the center of the knowledge network. “Ion channel diseases” are typically in the most prominent position of epilepsy genetics research. “Beyond ion channel diseases” and “genetic techniques,” however, have gradually grown into research cores and trends, such as “intellectual disability,” “infantile spasms,” “phenotype,” “exome,” “ deoxyribonucleic acid (DNA) copy number variations,” and “application of next-generation sequencing.” While ion channel genes such as “SCN1A,” “KCNQ2,” “SCN2A,” “SCN8A” accounted for nearly half of epilepsy genes in MeSH terms, a number of additional beyond ion channel genes like “CDKL5,” “STXBP1,” “PCDH19,” “PRRT2,” “LGI1,” “ALDH7A1,” “MECP2,” “EPM2A,” “ARX,” “SLC2A1,” and more were becoming increasingly popular. In contrast, gene therapies, treatment outcome, and genotype-phenotype correlations were still in their early stages of research. Conclusion: This co-word analysis provides an overview of epilepsy genetics research over the past decade. The 5 research categories display publication hot spots and trends in epilepsy genetics research which could consequently supply some direction for geneticists and epileptologists when launching new projects.

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The aim of this study was to analyze the knowledge structure and report the evolution of hypoxic-ischemic encephalopathy research over the past decade based on co-word analysis. Scientific publications focusing on neonatal hypoxic-ischemic encephalopathy were searched from the Web of Science database (January 2005 to December 2014). The keywords from these articles were extracted, and a knowledge network based on these keywords was built using Ucinet6.212 and NetDraw2.084 software. A total of 1892 papers were included, and 39 high-frequency keywords were defined. "HIE" and "neonate" located at the center of the knowledge network. Etiology and pathogenesis, clinical manifestation, and therapy were researched more widely in the network than other aspects of hypoxic-ischemic encephalopathy. This co-word analysis provides an overview of neonatal hypoxic-ischemic encephalopathy research and suggests that the etiology, clinical manifestation, and therapy of hypoxic-ischemic encephalopathy have become research cores over the past decade.