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Text Mining the Biomedical Literature for Identification of Potential Virus/Bacterium as Bio-Terrorism Weapons
There are some viruses and bacteria that have been identified as bioterrorism weapons. However, there are a lot other viruses and bacteria that can be potential bioterrorism weapons. A system that can automatically suggest potential bioterrorism weapons will help laypeople to discover these suspicio...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122316/ http://dx.doi.org/10.1007/978-0-387-71613-8_18 |
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author | Hu, Xiaohua Zhang, Xiaodan Wu, Daniel Zhou, Xiaohua Rumm, Peter |
author_facet | Hu, Xiaohua Zhang, Xiaodan Wu, Daniel Zhou, Xiaohua Rumm, Peter |
author_sort | Hu, Xiaohua |
collection | PubMed |
description | There are some viruses and bacteria that have been identified as bioterrorism weapons. However, there are a lot other viruses and bacteria that can be potential bioterrorism weapons. A system that can automatically suggest potential bioterrorism weapons will help laypeople to discover these suspicious viruses and bacteria. In this paper we apply instance-based learning & text mining approach to identify candidate viruses and bacteria as potential bio-terrorism weapons from biomedical literature. We first take text mining approach to identify topical terms of existed viruses (bacteria) from PubMed separately. Then, we apply a text mining method bridge these terms as instances with the remaining viruses (bacteria) and thus to discover how much these terms describe the remaining viruses (bacteria). In the end, we build an algorithm to rank all remaining viruses (bacteria). We suspect that the higher the ranking of the virus (bacterium) is, the more suspicious they will be potential bio-terrorism weapon. Our findings are intended as a guide to the virus and bacterium literature to support further studies that might then lead to appropriate defense and public health measures. |
format | Online Article Text |
id | pubmed-7122316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71223162020-04-06 Text Mining the Biomedical Literature for Identification of Potential Virus/Bacterium as Bio-Terrorism Weapons Hu, Xiaohua Zhang, Xiaodan Wu, Daniel Zhou, Xiaohua Rumm, Peter Terrorism Informatics Article There are some viruses and bacteria that have been identified as bioterrorism weapons. However, there are a lot other viruses and bacteria that can be potential bioterrorism weapons. A system that can automatically suggest potential bioterrorism weapons will help laypeople to discover these suspicious viruses and bacteria. In this paper we apply instance-based learning & text mining approach to identify candidate viruses and bacteria as potential bio-terrorism weapons from biomedical literature. We first take text mining approach to identify topical terms of existed viruses (bacteria) from PubMed separately. Then, we apply a text mining method bridge these terms as instances with the remaining viruses (bacteria) and thus to discover how much these terms describe the remaining viruses (bacteria). In the end, we build an algorithm to rank all remaining viruses (bacteria). We suspect that the higher the ranking of the virus (bacterium) is, the more suspicious they will be potential bio-terrorism weapon. Our findings are intended as a guide to the virus and bacterium literature to support further studies that might then lead to appropriate defense and public health measures. 2008 /pmc/articles/PMC7122316/ http://dx.doi.org/10.1007/978-0-387-71613-8_18 Text en © Springer Science+Business Media, LLC 2008 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Hu, Xiaohua Zhang, Xiaodan Wu, Daniel Zhou, Xiaohua Rumm, Peter Text Mining the Biomedical Literature for Identification of Potential Virus/Bacterium as Bio-Terrorism Weapons |
title | Text Mining the Biomedical Literature for Identification of Potential Virus/Bacterium as Bio-Terrorism Weapons |
title_full | Text Mining the Biomedical Literature for Identification of Potential Virus/Bacterium as Bio-Terrorism Weapons |
title_fullStr | Text Mining the Biomedical Literature for Identification of Potential Virus/Bacterium as Bio-Terrorism Weapons |
title_full_unstemmed | Text Mining the Biomedical Literature for Identification of Potential Virus/Bacterium as Bio-Terrorism Weapons |
title_short | Text Mining the Biomedical Literature for Identification of Potential Virus/Bacterium as Bio-Terrorism Weapons |
title_sort | text mining the biomedical literature for identification of potential virus/bacterium as bio-terrorism weapons |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122316/ http://dx.doi.org/10.1007/978-0-387-71613-8_18 |
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