Siqueiros-García Jesús M, Hernández-Lemus Enrique, García-Herrera Rodrigo, Robina-Galatas Andrea
Ethical, Legal and Social Studies Department, National Institute of Genomic Medicine, Mexico City, D.F., Mexico.
Computational Genomics Department, National Institute of Genomic Medicine, Mexico City, D.F., Mexico; Complexity in Systems Biology, Center for Complexity Sciences, National Autonomous University of Mexico, Mexico City, D.F., Mexico.
PLoS One. 2014 Apr 3;9(4):e92639. doi: 10.1371/journal.pone.0092639. eCollection 2014.
It has been proposed that the history and evolution of scientific ideas may reflect certain aspects of the underlying socio-cognitive frameworks in which science itself is developing. Systematic analyses of the development of scientific knowledge may help us to construct models of the collective dynamics of science. Aiming at scientific rigor, these models should be built upon solid empirical evidence, analyzed with formal tools leading to ever-improving results that support the related conclusions. Along these lines we studied the dynamics and structure of the development of research in genomics as represented by the entire collection of genomics-related scientific papers contained in the PubMed database. The analyzed corpus consisted in more than 49,000 articles published in the years 1987 (first appearance of the term Genomics) to 2011, categorized by means of the Medical Subheadings (MeSH) content-descriptors. Complex networks were built where two MeSH terms were connected if they are descriptors of the same article(s). The analysis of such networks revealed a complex structure and dynamics that to certain extent resembled small-world networks. The evolution of such networks in time reflected interesting phenomena in the historical development of genomic research, including what seems to be a phase-transition in a period marked by the completion of the first draft of the Human Genome Project. We also found that different disciplinary areas have different dynamic evolution patterns in their MeSH connectivity networks. In the case of areas related to science, changes in topology were somewhat fast while retaining a certain core-structure, whereas in the humanities, the evolution was pretty slow and the structure resulted highly redundant and in the case of technology related issues, the evolution was very fast and the structure remained tree-like with almost no overlapping terms.
有人提出，科学思想的历史与演变可能反映了科学自身发展所处的潜在社会认知框架的某些方面。对科学知识发展的系统分析或许能帮助我们构建科学集体动态的模型。为了达到科学严谨性，这些模型应建立在坚实的实证证据基础之上，并用形式化工具进行分析，从而得出不断完善的结果以支持相关结论。沿着这些思路，我们研究了基因组学研究发展的动态与结构，这是以PubMed数据库中包含的所有与基因组学相关的科学论文集来体现的。所分析的语料库包含1987年（术语“基因组学”首次出现）至2011年间发表的49000多篇文章，这些文章通过医学主题词表（MeSH）内容描述符进行分类。构建了复杂网络，如果两个MeSH术语是同一篇文章的描述符，它们就会相连。对这类网络的分析揭示了一种复杂的结构和动态，在一定程度上类似于小世界网络。这种网络随时间的演变反映了基因组学研究历史发展中的有趣现象，包括在人类基因组计划初稿完成标志的时期似乎出现的一个相变。我们还发现，不同学科领域在其MeSH连接网络中有不同的动态演变模式。在与科学相关的领域，拓扑结构的变化有些快，同时保留一定的核心结构，而在人文学科领域，演变相当缓慢，结构高度冗余，在与技术相关问题的领域，演变非常快，结构保持树状，几乎没有重叠术语。
