Azam Md Facihul, Musa Aliyu, Dehmer Matthias, Yli-Harja Olli P, Emmert-Streib Frank
Predictive Society and Data Analysis Lab, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland.
Institute of Biosciences and Medical Technology, Tampere, Finland.
Front Genet. 2019 Feb 14;10:70. doi: 10.3389/fgene.2019.00070. eCollection 2019.
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.
前列腺癌是芬兰男性中最常见的癌症类型，在全球范围内排第二。在本文中，我们运用集成文本挖掘和计算网络理论方法，分析了全球数以万计科学家撰写的近15万篇关于前列腺癌的已发表论文。我们展示了如何将文本挖掘与网络分析相结合，以研究各国的研究贡献以及国家内部和国家之间的合作。此外，我们研究了个体和集体研究基因的时间演变。最后，我们调查了芬兰的一个合作网络，并将所研究的基因与前列腺癌遗传学领域全球研究的基因进行比较。总体而言，我们的结果提供了前列腺癌遗传学研究的全球概况。此外，我们针对芬兰进行了具体讨论。我们的结果揭示了过去30年的趋势，对从遗传学到公共卫生管理和卫生政策等全领域的转化研究人员很有用。
