The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
대사 네트워크는 화학 반응과 세포 내 화합물 간의 관계를 나타냅니다. 미생물을 이용한 유용한 대사산물 생산에서는 성장 결합(Growth Coupling)을 초래하기 위해 원래 네트워크로부터 반응 삭제 전략을 계산해야 하는 경우가 종종 있는데, 이는 목표 대사산물 생산과 세포 성장이 동시에 달성된다는 의미입니다. 간단한 기본 플럭스 모드(EFM) 기반 방법은 이러한 반응 삭제 전략을 나열하는 데 유용하지만 고려해야 할 사례 수는 종종 네트워크 크기의 지수 함수에 비례합니다. 따라서, 반응 삭제 전략 후보의 수를 좁히는 방법을 개발하는 것이 바람직합니다. 본 연구에서 저자는 성장과 생산에 대한 특정 기준을 충족시키기 위해 L1 규범이 최소인 대사 흐름을 고려하는 L1 규범 최소 모드 아이디어를 소개하고 이를 기반으로 하는 빠른 대사 설계 목록 알고리즘(minL1-FMDL)을 개발했습니다. 다항식 시간에 작동합니다. (1) minL1-FMDL의 성능을 간단한 EFM 기반 방법의 성능과 비교하기 위해 상대적으로 작은 네트워크와 (2) minL1-FMDL의 확장성을 검증하기 위해 게놈 규모 네트워크에 대해 계산 실험을 수행했습니다. 계산 실험에서 minL1-FMDL의 목표 대사산물 생산 속도의 평균값이 단순 EFM 기반 방법보다 높으며, minL1-FMDL의 계산 시간은 게놈 규모에서도 충분히 빠른 것으로 나타났습니다. 네트워크. MATLAB에서 구현된 개발된 소프트웨어 minL1-FMDL은 https://sunflower.kuicr.kyoto-u.ac.jp/~tamura/software에서 사용할 수 있으며 대사산물 생산을 위한 게놈 규모의 대사 네트워크 설계에 사용할 수 있습니다. .
Takeyuki TAMURA
Kyoto University
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부
Takeyuki TAMURA, "L1 Norm Minimal Mode-Based Methods for Listing Reaction Network Designs for Metabolite Production" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 5, pp. 679-687, May 2021, doi: 10.1587/transinf.2020EDP7247.
Abstract: Metabolic networks represent the relationship between chemical reactions and compounds in cells. In useful metabolite production using microorganisms, it is often required to calculate reaction deletion strategies from the original network to result in growth coupling, which means the target metabolite production and cell growth are simultaneously achieved. Although simple elementary flux mode (EFM)-based methods are useful for listing such reaction deletions strategies, the number of cases to be considered is often proportional to the exponential function of the size of the network. Therefore, it is desirable to develop methods of narrowing down the number of reaction deletion strategy candidates. In this study, the author introduces the idea of L1 norm minimal modes to consider metabolic flows whose L1 norms are minimal to satisfy certain criteria on growth and production, and developed a fast metabolic design listing algorithm based on it (minL1-FMDL), which works in polynomial time. Computational experiments were conducted for (1) a relatively small network to compare the performance of minL1-FMDL with that of the simple EFM-based method and (2) a genome-scale network to verify the scalability of minL1-FMDL. In the computational experiments, it was seen that the average value of the target metabolite production rates of minL1-FMDL was higher than that of the simple EFM-based method, and the computation time of minL1-FMDL was fast enough even for genome-scale networks. The developed software, minL1-FMDL, implemented in MATLAB, is available on https://sunflower.kuicr.kyoto-u.ac.jp/~tamura/software, and can be used for genome-scale metabolic network design for metabolite production.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020EDP7247/_p
부
@ARTICLE{e104-d_5_679,
author={Takeyuki TAMURA, },
journal={IEICE TRANSACTIONS on Information},
title={L1 Norm Minimal Mode-Based Methods for Listing Reaction Network Designs for Metabolite Production},
year={2021},
volume={E104-D},
number={5},
pages={679-687},
abstract={Metabolic networks represent the relationship between chemical reactions and compounds in cells. In useful metabolite production using microorganisms, it is often required to calculate reaction deletion strategies from the original network to result in growth coupling, which means the target metabolite production and cell growth are simultaneously achieved. Although simple elementary flux mode (EFM)-based methods are useful for listing such reaction deletions strategies, the number of cases to be considered is often proportional to the exponential function of the size of the network. Therefore, it is desirable to develop methods of narrowing down the number of reaction deletion strategy candidates. In this study, the author introduces the idea of L1 norm minimal modes to consider metabolic flows whose L1 norms are minimal to satisfy certain criteria on growth and production, and developed a fast metabolic design listing algorithm based on it (minL1-FMDL), which works in polynomial time. Computational experiments were conducted for (1) a relatively small network to compare the performance of minL1-FMDL with that of the simple EFM-based method and (2) a genome-scale network to verify the scalability of minL1-FMDL. In the computational experiments, it was seen that the average value of the target metabolite production rates of minL1-FMDL was higher than that of the simple EFM-based method, and the computation time of minL1-FMDL was fast enough even for genome-scale networks. The developed software, minL1-FMDL, implemented in MATLAB, is available on https://sunflower.kuicr.kyoto-u.ac.jp/~tamura/software, and can be used for genome-scale metabolic network design for metabolite production.},
keywords={},
doi={10.1587/transinf.2020EDP7247},
ISSN={1745-1361},
month={May},}
부
TY - JOUR
TI - L1 Norm Minimal Mode-Based Methods for Listing Reaction Network Designs for Metabolite Production
T2 - IEICE TRANSACTIONS on Information
SP - 679
EP - 687
AU - Takeyuki TAMURA
PY - 2021
DO - 10.1587/transinf.2020EDP7247
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2021
AB - Metabolic networks represent the relationship between chemical reactions and compounds in cells. In useful metabolite production using microorganisms, it is often required to calculate reaction deletion strategies from the original network to result in growth coupling, which means the target metabolite production and cell growth are simultaneously achieved. Although simple elementary flux mode (EFM)-based methods are useful for listing such reaction deletions strategies, the number of cases to be considered is often proportional to the exponential function of the size of the network. Therefore, it is desirable to develop methods of narrowing down the number of reaction deletion strategy candidates. In this study, the author introduces the idea of L1 norm minimal modes to consider metabolic flows whose L1 norms are minimal to satisfy certain criteria on growth and production, and developed a fast metabolic design listing algorithm based on it (minL1-FMDL), which works in polynomial time. Computational experiments were conducted for (1) a relatively small network to compare the performance of minL1-FMDL with that of the simple EFM-based method and (2) a genome-scale network to verify the scalability of minL1-FMDL. In the computational experiments, it was seen that the average value of the target metabolite production rates of minL1-FMDL was higher than that of the simple EFM-based method, and the computation time of minL1-FMDL was fast enough even for genome-scale networks. The developed software, minL1-FMDL, implemented in MATLAB, is available on https://sunflower.kuicr.kyoto-u.ac.jp/~tamura/software, and can be used for genome-scale metabolic network design for metabolite production.
ER -