通过对使用现代计算工具的协作网络和主题的30年回顾性分析,绘制太平洋生物计算研讨会的演变和变革性影响。

Q2 Computer Science
Leah Zhang, Sameeksha Garg, Edward Zhang, Sean McOsker, Carly Bobak, Kristine Giffin, Brock Christensen, Joshua Levy
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引用次数: 0

摘要

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的合作研究,每年都会突出反映该领域跨学科性质的新兴主题。本研究旨在利用主题建模和网络分析方法,探讨公共事业单位的合作和主题动态。我们确定了过去三十年来PSB论述的14个中心主题。我们的研究结果显示了主题相关性的显著趋势,越来越强调机器学习和综合分析。我们不仅观察到合作关系的扩大,而且还观察到PSB在促进跨学科合作方面的关键作用。然而,目前尚不清楚,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推动的。下一代分析方法的未来应用可能会对这些动态提供更深入的见解。此外,我们开发了一个web应用程序,利用检索增强生成和大型语言模型,使用户能够有效地探索过去的PSB会议记录。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CHARTING THE EVOLUTION AND TRANSFORMATIVE IMPACT OF THE PACIFIC SYMPOSIUM ON BIOCOMPUTING THROUGH A 30-YEAR RETROSPECTIVE ANALYSIS OF COLLABORATIVE NETWORKS AND THEMES USING MODERN COMPUTATIONAL TOOLS.

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.

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CiteScore
4.50
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