TY - JOUR
T1 - Global genetics research in prostate cancer
T2 - A text minning and computational network theory approach
AU - Azam, Facihul
AU - Musa, Aliyu
AU - Dehmer, Matthias
AU - Yli-Harja, Olli P.
AU - Emmert-Streib, Frank
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Biomedical Text Mining
KW - Computational Network Theory
KW - Genetics
KW - Meta-Analysis
KW - Natural Language Processing
KW - Network Science
KW - Prostate Cancer
KW - Text Mining
UR - http://www.scopus.com/inward/record.url?scp=85065963518&partnerID=8YFLogxK
U2 - 10.3389/fgene.2019.00070
DO - 10.3389/fgene.2019.00070
M3 - Article
C2 - 30838019
AN - SCOPUS:85065963518
SN - 1664-8021
VL - 10
SP - 70
JO - Frontiers in Genetics
JF - Frontiers in Genetics
IS - FEB
M1 - 70
ER -