Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach.
biomedical text mining
computational network theory
genetics
meta-analysis
natural language processing
network science
prostate cancer
text mining
Journal
Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621
Informations de publication
Date de publication:
2019
2019
Historique:
received:
21
07
2018
accepted:
28
01
2019
entrez:
7
3
2019
pubmed:
7
3
2019
medline:
7
3
2019
Statut:
epublish
Résumé
Prostate cancer is the most common cancer type in men in Finland and second worldwide. In this paper, we analyze almost 150, 000 published papers about prostate cancer, authored by ten thousands of scientists worldwide, with an integrated text mining and computational network theory approach. We demonstrate how to integrate text mining with network analysis investigating research contributions of countries and collaborations within and between countries. Furthermore, we study the time evolution of individually and collectively studied genes. Finally, we investigate a collaboration network of Finland and compare studied genes with globally studied genes in prostate cancer genetics. Overall, our results provide a global overview of prostate cancer research in genetics. In addition, we present a specific discussion for Finland. Our results shed light on trends within the last 30 years and are useful for translational researchers within the full range from genetics to public health management and health policy.
Identifiants
pubmed: 30838019
doi: 10.3389/fgene.2019.00070
pmc: PMC6383410
doi:
Types de publication
Journal Article
Langues
eng
Pagination
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