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SYMBiomatics: Synergies in Medical Informatics and Bioinformatics – exploring current scientific literature for emergine topics

机译:SYMBiomatics:医学信息学和生物信息学的协同作用–探索有关新兴医学主题的最新科学文献

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摘要

Background: The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and disseminationactivity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain toimprove collaborative progress between both domains (ref. to http://www.symbiomatics.org). As part of theproject experts in both research fields will be identified and approached through a survey. To provide input tothe survey, the scientific literature was analysed to extract topics relevant to both medical informatics andbioinformatics.Results: This paper presents results of a systematic analysis of the scientific literature from medical informaticsresearch and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics andmedical informatics journals have been used as indication of existing and emerging technologies and topics overthe period 2000–2005 ("recent") and 1990–1990 ("past"). We identified emerging topics that were equallyimportant 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 weresystem biology, protein interaction networks and statistical methods for microarray analyses, whereas emergingtopics in medical informatics were grid technology and tissue microarrays.Conclusion: We conclude that although both fields have their own specific domains of interest, they sharecommon technological developments that tend to be initiated by new developments in biotechnology andcomputer science.
机译:背景: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(请参阅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有关的主题。结果:本文提供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,来自领先的生物信息学和医学信息学期刊的单词对(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。我们确定了近年来与生物信息学和医学信息学同等重要的新兴主题,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。生物技术和计算机科学的新发展往往会引发技术发展。

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