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Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach

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 dem...

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Autores principales: Azam, Md. Facihul, Musa, Aliyu, Dehmer, Matthias, Yli-Harja, Olli P., Emmert-Streib, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383410/
https://www.ncbi.nlm.nih.gov/pubmed/30838019
http://dx.doi.org/10.3389/fgene.2019.00070
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author Azam, Md. Facihul
Musa, Aliyu
Dehmer, Matthias
Yli-Harja, Olli P.
Emmert-Streib, Frank
author_facet Azam, Md. Facihul
Musa, Aliyu
Dehmer, Matthias
Yli-Harja, Olli P.
Emmert-Streib, Frank
author_sort Azam, Md. Facihul
collection PubMed
description 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.
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spelling pubmed-63834102019-03-05 Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach Azam, Md. Facihul Musa, Aliyu Dehmer, Matthias Yli-Harja, Olli P. Emmert-Streib, Frank Front Genet Genetics 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 Media S.A. 2019-02-14 /pmc/articles/PMC6383410/ /pubmed/30838019 http://dx.doi.org/10.3389/fgene.2019.00070 Text en Copyright © 2019 Azam, Musa, Dehmer, Yli-Harja and Emmert-Streib. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Azam, Md. Facihul
Musa, Aliyu
Dehmer, Matthias
Yli-Harja, Olli P.
Emmert-Streib, Frank
Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach
title Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach
title_full Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach
title_fullStr Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach
title_full_unstemmed Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach
title_short Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach
title_sort global genetics research in prostate cancer: a text mining and computational network theory approach
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383410/
https://www.ncbi.nlm.nih.gov/pubmed/30838019
http://dx.doi.org/10.3389/fgene.2019.00070
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