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Title: Special Issue: Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics

Microbial communities are networks of species, the interaction structure of which dynamically reorganizes in a varying environment. Even in a static condition, community dynamics are often difficult to predict due to highly nonlinear interspecies interactions. Understanding the fundamental principles of microbial interactions is therefore key for predicting and harnessing community function and properties. As extensively reviewed previously, mathematical models and computational methods that can predictively link interactions to community behaviors are indispensable tools for achieving this goal.
Authors:
ORCiD logo [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Biological Sciences Division
Publication Date:
Report Number(s):
PNNL-SA-133283
Journal ID: ISSN 2227-9717; PROCCO; PII: 4511
Grant/Contract Number:
AC05-76RL01830
Type:
Accepted Manuscript
Journal Name:
Processes
Additional Journal Information:
Journal Volume: 6; Journal Issue: 5; Journal ID: ISSN 2227-9717
Publisher:
Multidisciplinary Digital Publishing Institute (MDPI)
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 54 ENVIRONMENTAL SCIENCES
OSTI Identifier:
1457770

Song, Hyun-Seob. Special Issue: Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics. United States: N. p., Web. doi:10.3390/pr6050041.
Song, Hyun-Seob. Special Issue: Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics. United States. doi:10.3390/pr6050041.
Song, Hyun-Seob. 2018. "Special Issue: Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics". United States. doi:10.3390/pr6050041. https://www.osti.gov/servlets/purl/1457770.
@article{osti_1457770,
title = {Special Issue: Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics},
author = {Song, Hyun-Seob},
abstractNote = {Microbial communities are networks of species, the interaction structure of which dynamically reorganizes in a varying environment. Even in a static condition, community dynamics are often difficult to predict due to highly nonlinear interspecies interactions. Understanding the fundamental principles of microbial interactions is therefore key for predicting and harnessing community function and properties. As extensively reviewed previously, mathematical models and computational methods that can predictively link interactions to community behaviors are indispensable tools for achieving this goal.},
doi = {10.3390/pr6050041},
journal = {Processes},
number = 5,
volume = 6,
place = {United States},
year = {2018},
month = {4}
}