Fig. 1

Log-Transformed Trends in PubMed Citation Frequencies and Sequencing Costs (2000–2024). This figure illustrates trends in sequencing costs and PubMed citation frequencies for key terms (“multi-omics,” “personalized/precision medicine,” and “gene-environment (GxE) interactions”) from 2000 to 2024. Citation data were derived using a Python-based web scraping approach that sends HTTP requests to PubMed and parses the HTML response using the BeautifulSoup library. For each year, search queries targeted keywords in the title/abstract, filtering results by publication year to extract the annual citation count. Sequencing cost data were sourced from the National Human Genome Research Institute’s (NHGRI) Genome Sequencing Program (GSP) database (Wetterstrand KA, www.genome.gov/sequencingcostsdata; accessed June 17, 2024). Both the citation frequencies and sequencing costs are log-transformed for improved visibility of trends across a wide range of values. The y-axis for citations represents log10-transformed counts, where each unit increase corresponds to a tenfold increase in the number of citations. Similarly, the y-axis for sequencing costs reflects log10-transformed values, where each unit decrease corresponds to a tenfold reduction in the cost per megabase of sequencing. This transformation ensures that both very small and very large values are clearly represented, allowing for meaningful interpretation of exponential changes over time. The visualization emphasizes the rapid advancements in sequencing technology and the concurrent growth in research interest in multi-omics, personalized medicine, and GxE interactions