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.
Frontiers in genetics. 2019 Feb 14*** epublish ***
Md Facihul Azam, Aliyu Musa, Matthias Dehmer, Olli P Yli-Harja, Frank Emmert-Streib
Predictive Society and Data Analysis Lab, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland., Faculty for Management, Institute for Intelligent Production, University of Applied Sciences Upper Austria, Steyr, Austria., Institute of Biosciences and Medical Technology, Tampere, Finland.