Application of Ecological Network Theory to the Human Microbiome
In healthy humans, many microbial consortia constitute rich ecosystems with dozens to hundreds of species, finely tuned to functions relevant to human health. Medical interventions, lifestyle changes, and the normal rhythms of life sometimes upset the balance in microbial ecosystems, facilitating pa...
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| Format: | Article |
| Language: | English |
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Wiley
2008-01-01
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| Series: | Interdisciplinary Perspectives on Infectious Diseases |
| Online Access: | http://dx.doi.org/10.1155/2008/839501 |
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| _version_ | 1849397832752037888 |
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| author | James A. Foster Stephen M. Krone Larry J. Forney |
| author_facet | James A. Foster Stephen M. Krone Larry J. Forney |
| author_sort | James A. Foster |
| collection | DOAJ |
| description | In healthy humans, many microbial consortia constitute rich ecosystems with dozens to hundreds of species, finely tuned to functions relevant to human health. Medical interventions, lifestyle changes, and the normal rhythms of life sometimes upset the balance in microbial ecosystems, facilitating pathogen invasions or causing other clinically relevant problems. Some diseases, such as bacterial vaginosis, have exactly this sort of community etiology. Mathematical network theory is ideal for studying the ecological networks of interacting species that comprise the human microbiome. Theoretical networks require little consortia specific data to provide insight into both normal and disturbed microbial community functions, but it is easy to incorporate additional empirical data as it becomes available. We argue that understanding some diseases, such as bacterial vaginosis, requires a shift of focus from individual bacteria to (mathematical) networks of interacting populations, and that known emergent properties of these networks will provide insights that would be otherwise elusive. |
| format | Article |
| id | doaj-art-a7d4fa2f6432459e97db873319d8bbb0 |
| institution | Kabale University |
| issn | 1687-708X 1687-7098 |
| language | English |
| publishDate | 2008-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Interdisciplinary Perspectives on Infectious Diseases |
| spelling | doaj-art-a7d4fa2f6432459e97db873319d8bbb02025-08-20T03:38:49ZengWileyInterdisciplinary Perspectives on Infectious Diseases1687-708X1687-70982008-01-01200810.1155/2008/839501839501Application of Ecological Network Theory to the Human MicrobiomeJames A. Foster0Stephen M. Krone1Larry J. Forney2Department of Biological Sciences, University of Idaho, Moscow, ID 83844-3051, USAThe Initiative for Bioinformatics and Evolutionary STudies (IBEST), University of Idaho, Moscow, ID 83844-3051, USADepartment of Biological Sciences, University of Idaho, Moscow, ID 83844-3051, USAIn healthy humans, many microbial consortia constitute rich ecosystems with dozens to hundreds of species, finely tuned to functions relevant to human health. Medical interventions, lifestyle changes, and the normal rhythms of life sometimes upset the balance in microbial ecosystems, facilitating pathogen invasions or causing other clinically relevant problems. Some diseases, such as bacterial vaginosis, have exactly this sort of community etiology. Mathematical network theory is ideal for studying the ecological networks of interacting species that comprise the human microbiome. Theoretical networks require little consortia specific data to provide insight into both normal and disturbed microbial community functions, but it is easy to incorporate additional empirical data as it becomes available. We argue that understanding some diseases, such as bacterial vaginosis, requires a shift of focus from individual bacteria to (mathematical) networks of interacting populations, and that known emergent properties of these networks will provide insights that would be otherwise elusive.http://dx.doi.org/10.1155/2008/839501 |
| spellingShingle | James A. Foster Stephen M. Krone Larry J. Forney Application of Ecological Network Theory to the Human Microbiome Interdisciplinary Perspectives on Infectious Diseases |
| title | Application of Ecological Network Theory to the Human Microbiome |
| title_full | Application of Ecological Network Theory to the Human Microbiome |
| title_fullStr | Application of Ecological Network Theory to the Human Microbiome |
| title_full_unstemmed | Application of Ecological Network Theory to the Human Microbiome |
| title_short | Application of Ecological Network Theory to the Human Microbiome |
| title_sort | application of ecological network theory to the human microbiome |
| url | http://dx.doi.org/10.1155/2008/839501 |
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