Perez-Iratxeta Carolina, Andrade-Navarro Miguel A, Wren Jonathan D
Ottawa Health Research Institute, Ontario, Canada.
Brief Bioinform. 2007 Mar;8(2):88-95. doi: 10.1093/bib/bbl035. Epub 2006 Oct 31.
The cross-disciplinary nature of bioinformatics entails co-evolution with other biomedical disciplines, whereby some bioinformatics applications become popular in certain disciplines and, in turn, these disciplines influence the focus of future bioinformatics development efforts. We observe here that the growth of computational approaches within various biomedical disciplines is not merely a reflection of a general extended usage of computers and the Internet, but due to the production of useful bioinformatics databases and methods for the rest of the biomedical scientific community. We have used the abstracts stored both in the MEDLINE database of biomedical literature and in NIH-funded project grants, to quantify two effects. First, we examine the biomedical literature as a whole and find that the use of computational methods has become increasingly prevalent across biomedical disciplines over the past three decades, while use of databases and the Internet have been rapidly increasing over the past decade. Second, we study the recent trends in the use of bioinformatics topics. We observe that molecular sequence databases are a widely adopted contribution in biomedicine from the field of bioinformatics, and that microarray analysis is one of the major new topics engaged by the bioinformatics community. Via this analysis, we were able to identify areas of rapid growth in the use of informatics to aid in curriculum planning, development of computational infrastructure and strategies for workforce education and funding.
生物信息学的跨学科性质需要与其他生物医学学科共同发展,在此过程中,一些生物信息学应用在某些学科中变得流行起来,反过来,这些学科又影响着未来生物信息学发展工作的重点。我们在此观察到,各生物医学学科中计算方法的增长不仅仅是计算机和互联网普遍使用范围扩大的反映,而是因为为生物医学科学界的其他领域产生了有用的生物信息学数据库和方法。我们利用存储在生物医学文献的MEDLINE数据库以及美国国立卫生研究院资助项目拨款中的摘要,来量化两种影响。首先,我们审视整个生物医学文献,发现过去三十年来,计算方法在各生物医学学科中的使用越来越普遍,而数据库和互联网的使用在过去十年中迅速增加。其次,我们研究生物信息学主题使用的近期趋势。我们观察到分子序列数据库是生物信息学领域在生物医学中广泛采用的一项成果,并且微阵列分析是生物信息学领域关注的主要新主题之一。通过这种分析,我们能够确定在利用信息学辅助课程规划、计算基础设施开发以及劳动力教育和资金筹集策略方面快速增长的领域。