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Mapping the structure and dynamics of genomics-related MeSH terms complex networks.

Siqueiros-García JM, Hernández-Lemus E, García-Herrera R, Robina-Galatas A - PLoS ONE (2014)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Ethical, Legal and Social Studies Department, National Institute of Genomic Medicine, Mexico City, D.F., Mexico.

ABSTRACT
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.

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Dynamics of the topological parameters for the History subnetworks.Panels A–F.
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pone-0092639-g008: Dynamics of the topological parameters for the History subnetworks.Panels A–F.

Mentions: Every set of subnetworks (SNs) display a different structure and dynamics [see Figures 7, 8, 9, 10, 11]. When compared against each other, we noticed that despite the low density of each network, there were important differences in the clustering coefficient values. While the set of networks for the humanities had high clustering coefficient values [Figures 7, 8 Panel C], the science subnetwork (represented by the SN Neoplasms), were slightly higher than those presented by a random network [Figure 9 Panel C]. Contrary to the results of the humanities and science SNs clustering coefficients, the technology SNs were below the results for a random network [Figures 10, 11 Panel C]. We believe that these results somehow mirror the nature of the different areas. The results of these thematic SNs suggest that not all areas of inquiry behave in the same way. The humanities appear to move at a slower pace as compared to the other areas. The humanities seem to be quite redundant in their subjects and concepts. For instance, in the case of Ethics, concepts that are central to debates are words like justice, dignity, equity, words that have been in the ethics vocabulary for hundreds of years. Interestingly enough, in an article recently published in the New York Times, Nicholas Christakis makes reference to an apparent state of stagnation in the Social Sciences [23]. From what we see in our Ethics and History SNs, it seems that what is to be for the Social Sciences it might be also true for the Humanities –although the pupose of the formers is different from the latters, since the Social Sciences purport themselves as sciences. We also explored the content of the triangles (responsible for the clustering coefficient) of a fraction of all SNs for each of these subjects, nevertheless, we were able to see that for History, a network with very high clustering coefficient and network centralization [see Tables S3–S7], the terms with the highest connectivity were the terms present as two of the nodes in the triangle. Quite different from this, the Ethics SNs had a high clustering coefficient and network centralization, still triangles were not dominated by highly connected nodes, on the contrary, clusters were more diverse.


Mapping the structure and dynamics of genomics-related MeSH terms complex networks.

Siqueiros-García JM, Hernández-Lemus E, García-Herrera R, Robina-Galatas A - PLoS ONE (2014)

Dynamics of the topological parameters for the History subnetworks.Panels A–F.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3974714&req=5

pone-0092639-g008: Dynamics of the topological parameters for the History subnetworks.Panels A–F.
Mentions: Every set of subnetworks (SNs) display a different structure and dynamics [see Figures 7, 8, 9, 10, 11]. When compared against each other, we noticed that despite the low density of each network, there were important differences in the clustering coefficient values. While the set of networks for the humanities had high clustering coefficient values [Figures 7, 8 Panel C], the science subnetwork (represented by the SN Neoplasms), were slightly higher than those presented by a random network [Figure 9 Panel C]. Contrary to the results of the humanities and science SNs clustering coefficients, the technology SNs were below the results for a random network [Figures 10, 11 Panel C]. We believe that these results somehow mirror the nature of the different areas. The results of these thematic SNs suggest that not all areas of inquiry behave in the same way. The humanities appear to move at a slower pace as compared to the other areas. The humanities seem to be quite redundant in their subjects and concepts. For instance, in the case of Ethics, concepts that are central to debates are words like justice, dignity, equity, words that have been in the ethics vocabulary for hundreds of years. Interestingly enough, in an article recently published in the New York Times, Nicholas Christakis makes reference to an apparent state of stagnation in the Social Sciences [23]. From what we see in our Ethics and History SNs, it seems that what is to be for the Social Sciences it might be also true for the Humanities –although the pupose of the formers is different from the latters, since the Social Sciences purport themselves as sciences. We also explored the content of the triangles (responsible for the clustering coefficient) of a fraction of all SNs for each of these subjects, nevertheless, we were able to see that for History, a network with very high clustering coefficient and network centralization [see Tables S3–S7], the terms with the highest connectivity were the terms present as two of the nodes in the triangle. Quite different from this, the Ethics SNs had a high clustering coefficient and network centralization, still triangles were not dominated by highly connected nodes, on the contrary, clusters were more diverse.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Ethical, Legal and Social Studies Department, National Institute of Genomic Medicine, Mexico City, D.F., Mexico.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus