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SYMBIOmatics: Synergies in Medical Informatics and Bioinformatics – exploring current scientific literature for emerging topics

机译：SYMBIOmatics：医学信息学和生物信息学的协同作用–探索新兴主题的最新科学文献

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Background The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and dissemination activity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain to improve collaborative progress between both domains (ref. to http://www.symbiomatics.org ). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics. Results This paper presents results of a systematic analysis of the scientific literature from medical informatics research and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics and medical informatics journals have been used as indication of existing and emerging technologies and topics over the period 2000–2005 ("recent") and 1990–1990 ("past"). We identified emerging topics that were equally important to bioinformatics and medical informatics in recent years such as microarray experiments, ontologies, open source, text mining and support vector machines. Emerging topics that evolved only in bioinformatics were system biology, protein interaction networks and statistical methods for microarray analyses, whereas emerging topics in medical informatics were grid technology and tissue microarrays. Conclusion We conclude that although both fields have their own specific domains of interest, they share common technological developments that tend to be initiated by new developments in biotechnology and computer science.
机译：背景技术SYMBIOmatics特定支持行动（SSA）是一种“信息收集和传播活动”，旨在“确定生物信息学和医学信息学之间的协同作用”领域，以改善这两个领域之间的协作进展（参见http：// www。 symbiomatics.org）。作为项目的一部分，将确定两个研究领域的专家并通过调查与他们联系。为了向调查提供输入，对科学文献进行了分析，以提取与医学信息学和生物信息学相关的主题。结果本文介绍了从医学信息学研究和生物信息学研究中对科学文献进行系统分析的结果。在分析中，主要的生物信息学和医学信息学期刊中的词对（字母组合）被用作表示2000-2005年（“最近”）和1990-1990年（“过去”）期间现有和新兴技术和主题的指标。我们确定了近年来对生物信息学和医学信息学同样重要的新兴主题，例如微阵列实验，本体论，开源，文本挖掘和支持向量机。仅在生物信息学中发展的新兴主题是系统生物学，蛋白质相互作用网络和微阵列分析的统计方法，而医学信息学中的新兴主题是网格技术和组织微阵列。结论我们得出的结论是，尽管这两个领域都有其自己特定的领域，但它们共享共同的技术发展，这些发展往往是由生物技术和计算机科学的新发展所引发的。

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