2013
DOI: 10.3892/or.2013.2239
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Analysis of oncology research from 2001 to 2010: A scientometric perspective

Abstract: Over the past half-century, the incidence of tumours has increased, resulting in cancer becoming one of the most lethal diseases in humans. In the present study, we elucidated the status of oncology research from 2001 to 2010. Studies published in 30 representative oncology journals were retrieved from the Web of Science (2001-2010) to compose our dataset. Knowledge domain visualisation, co-citation analysis and social network analysis methods were us… Show more

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Cited by 16 publications
(6 citation statements)
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“…Citation rate of published articles was chosen to define the most important contributions. Articles with high numbers of citations are likely those that impressed other clinicians/scientists and had impact on clinical practice or future developments in the field (Shao et al 2013). It should be noticed that searches in different databases will result in more or less variable citation counts and that the present results therefore provide only a snapshot.…”
Section: Discussionmentioning
confidence: 99%
“…Citation rate of published articles was chosen to define the most important contributions. Articles with high numbers of citations are likely those that impressed other clinicians/scientists and had impact on clinical practice or future developments in the field (Shao et al 2013). It should be noticed that searches in different databases will result in more or less variable citation counts and that the present results therefore provide only a snapshot.…”
Section: Discussionmentioning
confidence: 99%
“…By mapping the oncology research performed from 2001 to 2010, Shao et al identified the four major oncology research fronts: the mechanism of abnormal oncogene expression, tumor metastasis and angiogenesis, the relationship between cancer cells and apoptosis, and finally, tumor vaccine [120].…”
Section: Conclusion and Future Prospectsmentioning
confidence: 99%
“…In contrast to transit map diagrams, network diagrams are algorithmically generated via a variety of computational methods (eg, www.genemania.org). Network analysis is often used to illustrate multidimensional "-omics" datasets such as genomics, transcriptomics, and metabolomics ( Figure 7A) but can also be used to represent any group of interconnected variables such as academic authorship ( Figure 7B) (47,48).…”
Section: Network Analysis Diagramsmentioning
confidence: 99%
“…Journals could play a key role here, standardizing features like colors used to describe stage, histology, or chromosomes, or the symbols used in plots like swim plots. Bringing consensus to data representation will speed the (48). One vertex represents one author.…”
Section: Conclusion and Directionsmentioning
confidence: 99%