IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models

IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models

Abstract Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD databa...

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Main Authors: Chao Ye, Nan Xu, Chuan Dong, Yuannong Ye, Xuan Zou, Xiulai Chen, Fengbiao Guo, Liming Liu
Format: Article
Language:English
Published: Nature Publishing Group 2017-04-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-017-00820-6
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spelling doaj-26d78116c2144cd98197bed621f4aa7d2020-12-08T00:42:26ZengNature Publishing GroupScientific Reports2045-23222017-04-01711910.1038/s41598-017-00820-6IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic ModelsChao Ye0Nan Xu1Chuan Dong2Yuannong Ye3Xuan Zou4Xiulai Chen5Fengbiao Guo6Liming Liu7State Key Laboratory of Food Science and Technology, Jiangnan UniversityState Key Laboratory of Food Science and Technology, Jiangnan UniversityKey Laboratory for Neuroinformation of Ministry of Education, University of Electronic Science and Technology of ChinaSchool of Biology and Engineering, Guizhou Medical UniversityState Key Laboratory of Food Science and Technology, Jiangnan UniversityState Key Laboratory of Food Science and Technology, Jiangnan UniversityKey Laboratory for Neuroinformation of Ministry of Education, University of Electronic Science and Technology of ChinaState Key Laboratory of Food Science and Technology, Jiangnan UniversityAbstract Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.https://doi.org/10.1038/s41598-017-00820-6
collection DOAJ
language English
format Article
sources DOAJ
author Chao Ye
Nan Xu
Chuan Dong
Yuannong Ye
Xuan Zou
Xiulai Chen
Fengbiao Guo
Liming Liu
spellingShingle Chao Ye
Nan Xu
Chuan Dong
Yuannong Ye
Xuan Zou
Xiulai Chen
Fengbiao Guo
Liming Liu
IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models
Scientific Reports
author_facet Chao Ye
Nan Xu
Chuan Dong
Yuannong Ye
Xuan Zou
Xiulai Chen
Fengbiao Guo
Liming Liu
author_sort Chao Ye
title IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models
title_short IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models
title_full IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models
title_fullStr IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models
title_full_unstemmed IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models
title_sort imgmd: a platform for the integration and standardisation of in silico microbial genome-scale metabolic models
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2017-04-01
description Abstract Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.
url https://doi.org/10.1038/s41598-017-00820-6
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