Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics
Investigating the microbiome is on the frontier of science. It has the potential to resolve many issues in the realms of energy, food, human health, the environment, and biotechnology. Scientists are trying to understand, in a fundamental way, how microbes influence each other and how they organize...
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| 主要作者: | |
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| 格式: | Online |
| 语言: | 英语 |
| 出版: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| 主题: | |
| 在线阅读: | 27254 |
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| _version_ | 1869519678885330944 |
|---|---|
| author | Hyun-Seob Song (Ed.) |
| author_browse | Hyun-Seob Song (Ed.) |
| author_facet | Hyun-Seob Song (Ed.) |
| author_sort | Hyun-Seob Song (Ed.) |
| collection | Directory of Open Access Books |
| description | Investigating the microbiome is on the frontier of science. It has the potential to resolve many issues in the realms of energy, food, human health, the environment, and biotechnology. Scientists are trying to understand, in a fundamental way, how microbes influence each other and how they organize into interaction networks. These are the keys to predicting and engineering community function and properties of the microbiome. In this regard, mathematical modeling and computational analysis play an increasing role. This book is a collection of contributions from lead scientists in the field. It provides innovative approaches and fresh perspectives for modeling environmental communities and engineered microbial consortia. Reading this book will give researchers a solid look at cutting-edge science in microbial community modeling, and at the remaining challenges such modeling poses. |
| format | Online |
| id | doab-20.500.12854ir-53393 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-533932024-04-11T15:10:46Z Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics Hyun-Seob Song (Ed.) TP155-156 microbial interaction metabolic networks coexistence biofilm Microbial communities model consortia individual-based modeling metabolic coupling stability thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology Investigating the microbiome is on the frontier of science. It has the potential to resolve many issues in the realms of energy, food, human health, the environment, and biotechnology. Scientists are trying to understand, in a fundamental way, how microbes influence each other and how they organize into interaction networks. These are the keys to predicting and engineering community function and properties of the microbiome. In this regard, mathematical modeling and computational analysis play an increasing role. This book is a collection of contributions from lead scientists in the field. It provides innovative approaches and fresh perspectives for modeling environmental communities and engineered microbial consortia. Reading this book will give researchers a solid look at cutting-edge science in microbial community modeling, and at the remaining challenges such modeling poses. 2021-02-11T19:31:50Z 2021-02-11T19:31:50Z 2018-07-04 13:24:50 2018 book 27254 9783038429753 9783038429760 https://directory.doabooks.org/handle/20.500.12854/53393 eng image/png Attribution-NonCommercial-NoDerivatives 4.0 International http://www.mdpi.com/books/pdfview/book/664 http://www.mdpi.com/books/pdfview/book/664 MDPI - Multidisciplinary Digital Publishing Institute 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783038429753 9783038429760 VIII, 286 open access |
| spellingShingle | TP155-156 microbial interaction metabolic networks coexistence biofilm Microbial communities model consortia individual-based modeling metabolic coupling stability thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology Hyun-Seob Song (Ed.) Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics |
| title | Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics |
| title_full | Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics |
| title_fullStr | Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics |
| title_full_unstemmed | Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics |
| title_short | Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics |
| title_sort | microbial community modeling prediction of microbial interactions and community dynamics |
| topic | TP155-156 microbial interaction metabolic networks coexistence biofilm Microbial communities model consortia individual-based modeling metabolic coupling stability thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology |
| topic_facet | TP155-156 microbial interaction metabolic networks coexistence biofilm Microbial communities model consortia individual-based modeling metabolic coupling stability thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology |
| url | 27254 |
| work_keys_str_mv | AT hyunseobsonged microbialcommunitymodelingpredictionofmicrobialinteractionsandcommunitydynamics |