3.9 Article

Developmental biologists' choice of subjects approximates to a power law, with no evidence for the existence of a special group of 'model organisms'

期刊

BMC DEVELOPMENTAL BIOLOGY
卷 7, 期 -, 页码 -

出版社

BIOMED CENTRAL LTD
DOI: 10.1186/1471-213X-7-40

关键词

-

向作者/读者索取更多资源

Background: This report describes an unexpected aspect of the structure and development of developmental biology research, rather than the development of a specific embryo. Descriptions of modern developmental biology emphasize investigators' concentration on a small number of 'model' organisms and it is assumed that a clear division exists between the attention paid to these 'model' organisms and that paid to other species. This report describes a quantitative analysis of the organisms that were the subjects of studies reported in developmental biology journals published in the years 1965, 1975, 1985, 1995 and 2005, chosen to represent five decades of modern developmental biology. Results: The results demonstrate that the distribution of attention paid to different organisms has a smooth distribution that approximates to a scale-free power law, in which there is no clear discontinuity that divides organisms into 'models' and the rest. This is true for both individual years and for the aggregate of all years' data. In other systems (eg connections in the World Wide Web), such power-law distributions arise from mechanisms of preferential attachment ('the rich get richer'). Detailed analysis of the progress of different organisms over the years under study shows that, while preferential attachment may be part of the mechanism that generates the power law distribution, it is insufficient to explain it. Conclusion: The smoothness of the distribution suggests that there is no empirical basis for dividing species under study into 'model' organisms and 'the rest', and that the widely-held view about organism choice in developmental biology is distorted.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

3.9
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据