A Survey of Bioinformatics Database and Software Usage through Mining the Literature.
A Survey of Bioinformatics Database and Software Usage through Mining the Literature.
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DOI：
10.1371/journal.pone.0157989
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Stevens R
中科院分区：
文献类型：
--
作者：
Duck G;Nenadic G;Filannino M;Brass A;Robertson DL;Stevens R
以计算机为基础的资源是许多（如果不是大多数的话）生物和医学研究的核心。然而，尽管生物医学文献中描述的生物信息学资源的选择不断扩大，但迄今为止很少有工作对数据库和软件资源的可用性或使用水平进行全面评估。在这里，我们使用文本挖掘来处理PubMed Central全文语料库，识别科学文献中提到的数据库或软件。我们对生物医学文献中包含的资源进行审计，并对它们的相对使用情况进行比较，包括随着时间的推移以及生物信息学、生物学和医学的子学科之间的使用情况。我们发现这些领域的资源使用趋势是不同的。生物信息学文献强调新资源开发，而生物学和医学中的数据库和软件使用则更为稳定和保守。许多资源只在生物信息学文献中被提及，在普通生物学中被提及的相对较少，在医学文献中被提及的更少。此外，许多资源的使用量正在稳步下降（例如BLAST， SWISS-PROT），尽管有些资源的使用量正在快速增长（例如GO， R）。我们发现资源使用存在显著的不平衡，前5%的资源名称（133个名称）占总使用量的47%，超过70%的资源提取只被提及一次。虽然这些结果突出了生物信息学研究的动态和创造性，但它们提出了关于软件重用、选择和生物信息学实践共享的问题。这么多资源显然从来没有被重用，这是可以接受的吗？最后，我们的工作是朝着从文本中自动提取科学方法迈出的一步。我们在CC0许可下提供了我们研究生成的数据集：http://dx.doi.org/10.6084/m9.figshare.1281371。
Computer-based resources are central to much, if not most, biological and medical research. However, while there is an ever expanding choice of bioinformatics resources to use, described within the biomedical literature, little work to date has provided an evaluation of the full range of availability or levels of usage of database and software resources. Here we use text mining to process the PubMed Central full-text corpus, identifying mentions of databases or software within the scientific literature. We provide an audit of the resources contained within the biomedical literature, and a comparison of their relative usage, both over time and between the sub-disciplines of bioinformatics, biology and medicine. We find that trends in resource usage differs between these domains. The bioinformatics literature emphasises novel resource development, while database and software usage within biology and medicine is more stable and conservative. Many resources are only mentioned in the bioinformatics literature, with a relatively small number making it out into general biology, and fewer still into the medical literature. In addition, many resources are seeing a steady decline in their usage (e.g., BLAST, SWISS-PROT), though some are instead seeing rapid growth (e.g., the GO, R). We find a striking imbalance in resource usage with the top 5% of resource names (133 names) accounting for 47% of total usage, and over 70% of resources extracted being only mentioned once each. While these results highlight the dynamic and creative nature of bioinformatics research they raise questions about software reuse, choice and the sharing of bioinformatics practice. Is it acceptable that so many resources are apparently never reused? Finally, our work is a step towards automated extraction of scientific method from text. We make the dataset generated by our study available under the CC0 license here: http://dx.doi.org/10.6084/m9.figshare.1281371.
分子生物学数据库集合：2006年更新。
影响因子：
14.9
作者：
Galperin, Michael Y.
通讯作者：
Galperin, Michael Y.
生物信息学链接目录：分子生物学网络服务器的汇编。
影响因子：
14.9
作者：
Fox, JA;Butland, SL;McMillan, S;Campbell, G;Ouellette, BFF
通讯作者：
Ouellette, BFF