Global genetics research in prostate cancer: A text minning and computational network theory approach

Facihul Azam, Aliyu Musa, Matthias Dehmer, Olli P. Yli-Harja, Frank Emmert-Streib

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number70
Pages (from-to)70
JournalFrontiers in Genetics
Volume10
Issue numberFEB
DOIs
Publication statusPublished - 2019

Keywords

  • Biomedical Text Mining
  • Computational Network Theory
  • Genetics
  • Meta-Analysis
  • Natural Language Processing
  • Network Science
  • Prostate Cancer
  • Text Mining

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