Mapping the Structure and Dynamics of Genomics-Related MeSH Terms Complex Networks

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 appeareance 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-stucture, 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.

A systematic approach to analyze the social determinants of cardiovascular disease

“…Stage I In this systematic approach we first analyzed the SDCVD using network theory [ 15 ] and scientometrics models formed by systematic key terms [ 13 ] –as given by the Medical Sub Heading ontology (MeSH) developed by the National Library of Medicine of the U.S., in particular by the National Center for Biotechnological Information (NCBI) PUBMED database– that describe each SDCVD according to the CSDH-FW.…”

“… Once a systematic PubMed search procedure has been performed with the Social Determinants of Health MeSH as main parameter and cardiovascular disease terms as modifiers, a series of data curation procedures was made by using e-QAD tool Atlas.TI . The curated corpus was used to obtain data visualizations and to infer semantic-like MeSH Networks [ 13 ]. MeSH networks were later analyzed to look up for non-trivial associations.…”

“…Such connections, however, are quite difficult to unveil or highlight by resorting to traditional systematic reviews and meta-analyses that usually present the information about the different SDCVD fragmented, or at most, integrated according with the subjective appreciation of the expert reviewer [ 7 , 8 ]. Other methodological approaches to systematic analyses of the literature have been used recently [ 9 – 13 ], some of them resort to computational mining of the publication databases and archives, semantic networks and ontology-based methods to add context to theme-driven systematic surveys of the literature.…”

Pathway Analysis: State of the Art

“…At present, more than 35,500 prokaryotic and eukaryotic genomes are at public disposition in the National Center for Biotechnology Information site, as completely sequenced or in progress builds. Since the inception of the term “genomics” in academic literature, research in this field has changed and evolved over dramatically different aspects of human knowledge (Siqueiros-García et al, 2014 ). These facts evidence how modern life sciences research will be dependent of this ever growing biological information gathering, which expands in a multidimensional way, and at an increasingly detailed manner.…”

Mobile-Friendly Dashboards to Display Associations Between Cited-by and Similar Journals on Mobile Health Research: A Bibliometric Study (Preprint)

“…We replaced the cited-by with the similar journals associated with a given journal and applied it to inspect the association between cited-by and similar journals among Both articles [35,36] had applied SNA, and medical subject headings (MESH) terms based on PubMed articles to characterize interesting phenomena of the research.…”