Zhang Leah, Garg Sameeksha, Zhang Edward, McOsker Sean, Bobak Carly, Giffin Kristine, Christensen Brock, Levy Joshua
Thomas Jefferson High School for Science & Technology, Alexandria, VA, USA,
Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA,
Pac Symp Biocomput. 2025;30:16-32. doi: 10.1142/9789819807024_0002.
Founded nearly 30 years ago, the Pacific Symposium on Biocomputing (PSB) has continually promoted collaborative research in computational biology, annually highlighting emergent themes that reflect the expanding interdisciplinary nature of the field. This study aimed to explore the collaborative and thematic dynamics at PSB using topic modeling and network analysis methods. We identified 14 central topics that have characterized the discourse at PSB over the past three decades. Our findings demonstrate significant trends in topic relevance, with a growing emphasis on machine learning and integrative analyses. We observed not only an expanding nexus of collaboration but also PSB's crucial role in fostering interdisciplinary collaborations. It remains unclear, however, whether the shift towards interdisciplinarity was driven by the conference itself, external academic trends, or broader societal shifts towards integrated research approaches. Future applications of next-generation analytical methods may offer deeper insights into these dynamics. Additionally, we have developed a web application that leverages retrieval augmented generation and large language models, enabling users to efficiently explore past PSB proceedings.
太平洋生物计算研讨会（PSB）成立于近30年前，一直在推动计算生物学领域的合作研究，每年都会突出反映该领域不断扩展的跨学科性质的新兴主题。本研究旨在运用主题建模和网络分析方法，探究PSB的合作与主题动态。我们确定了14个核心主题，这些主题在过去三十年里一直主导着PSB的讨论。我们的研究结果显示了主题相关性的显著趋势，机器学习和综合分析受到越来越多的关注。我们不仅观察到合作网络在不断扩大，还看到了PSB在促进跨学科合作方面的关键作用。然而，尚不清楚向跨学科的转变是由会议本身、外部学术趋势，还是更广泛的社会向综合研究方法的转变所驱动。下一代分析方法的未来应用可能会为这些动态提供更深入的见解。此外，我们开发了一个网络应用程序，利用检索增强生成和大语言模型，使用户能够高效地探索过去的PSB会议记录。
