<![CDATA[Population genetics has long relied on mathematical frameworks to interpret patterns of genetic variation and evolutionary processes within populations. Among these frameworks, the Hardy-Weinberg equilibrium is one of the most fundamental models for evaluating allele and genotype frequency distributions under theoretical population conditions. Despite its central role in population genetics, the development and research trends related to the Hardy-Weinberg equilibrium and mathematical modeling have not been systematically examined at the bibliometric level. This study aimed to analyze the evolution of scientific research on Hardy-Weinberg equilibrium and mathematical modeling within population genetics using bibliometric approaches. Bibliographic data were retrieved from the Scopus database, resulting in a final dataset of 1,899 research articles. Publication trends, leading journals, productive authors, citation impact, international collaboration networks, thematic structures, and historiographic evolution were analyzed using bibliometric techniques, VOSviewer, and Bibliometrix in R Studio. The results indicate a sustained growth in publications, particularly since the early 2000s, reflecting the increasing role of quantitative and computational approaches in population genetics. Citation and thematic analyses reveal a substantial intellectual transition from classical equilibrium-based population genetics toward molecular, computational, and genomics-oriented research. Historiographic periodization further demonstrates that Hardy-Weinberg-based mathematical frameworks have continuously evolved alongside advances in high-throughput sequencing, statistical genetics, and large-scale genomic analysis. An important insight from this study is that modern genomics research has not replaced the classical Hardy-Weinberg principles, but has instead expanded their application through the integration of computational biology, bioinformatics, and genomics technologies. These findings highlight the continuing relevance of mathematical population genetic frameworks in contemporary genetic science and provide a clearer understanding of the state of the art and future direction of population genetics research.]]>
