Abstract
In metabolic network modification, we newly add enzymes or/and knock-out genes to maximize the biomass production with minimum side-effect. Although this problem has been studied for various problem settings via mathematical models including flux balance analysis, elementary mode, and Boolean models, some important problem settings still remain to be studied. In this paper, we consider Boolean Reaction Modification (BRM) problem, where a host metabolic network and a reference metabolic network are given in the Boolean model, the host network initially produces some toxic compounds and cannot produce some necessary compounds, but the reference network can produce the necessary compounds, and we should minimize the total number of removed reactions from the host network and added reactions from the reference network so that the toxic compounds are not producible, but the necessary compounds are producible in the resulting host network. We developed integer linear programming (ILP)-based methods for BRM, and compared with OptStrain and SimOptStrain. The results show that our method performed better for reducing the total number of added and removed reactions, while OptStrain and SimOptStrain performed better for optimizing the production of the target compound. Our developed software is freely available at “http://sunflower.kuicr.kyoto-u.ac.jp/~rogi/solBRM/solBRM.html”.
| Original language | English |
|---|---|
| Pages (from-to) | 1853-1862 |
| Number of pages | 10 |
| Journal | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
| Volume | 15 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 24 Nov 2017 |
Keywords
- algorithm
- Biochemistry
- Bioinformatics
- Biological system modeling
- Biomass
- Boolean model
- Compounds
- feedback vertex set
- flux balance analysis
- integer linear programming
- Mathematical model
- metabolic network
- Production
Cite this
}
Computing Minimum Reaction Modifications in a Boolean Metabolic Network. / Tamura, Takeyuki; Lu, Wei; Song, Jiangning; Akutsu, Tatsuya.
In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 15, No. 6, 24.11.2017, p. 1853-1862.Research output: Contribution to journal › Article › Research › peer-review
TY - JOUR
T1 - Computing Minimum Reaction Modifications in a Boolean Metabolic Network
AU - Tamura, Takeyuki
AU - Lu, Wei
AU - Song, Jiangning
AU - Akutsu, Tatsuya
PY - 2017/11/24
Y1 - 2017/11/24
N2 - In metabolic network modification, we newly add enzymes or/and knock-out genes to maximize the biomass production with minimum side-effect. Although this problem has been studied for various problem settings via mathematical models including flux balance analysis, elementary mode, and Boolean models, some important problem settings still remain to be studied. In this paper, we consider Boolean Reaction Modification (BRM) problem, where a host metabolic network and a reference metabolic network are given in the Boolean model, the host network initially produces some toxic compounds and cannot produce some necessary compounds, but the reference network can produce the necessary compounds, and we should minimize the total number of removed reactions from the host network and added reactions from the reference network so that the toxic compounds are not producible, but the necessary compounds are producible in the resulting host network. We developed integer linear programming (ILP)-based methods for BRM, and compared with OptStrain and SimOptStrain. The results show that our method performed better for reducing the total number of added and removed reactions, while OptStrain and SimOptStrain performed better for optimizing the production of the target compound. Our developed software is freely available at “http://sunflower.kuicr.kyoto-u.ac.jp/~rogi/solBRM/solBRM.html”.
AB - In metabolic network modification, we newly add enzymes or/and knock-out genes to maximize the biomass production with minimum side-effect. Although this problem has been studied for various problem settings via mathematical models including flux balance analysis, elementary mode, and Boolean models, some important problem settings still remain to be studied. In this paper, we consider Boolean Reaction Modification (BRM) problem, where a host metabolic network and a reference metabolic network are given in the Boolean model, the host network initially produces some toxic compounds and cannot produce some necessary compounds, but the reference network can produce the necessary compounds, and we should minimize the total number of removed reactions from the host network and added reactions from the reference network so that the toxic compounds are not producible, but the necessary compounds are producible in the resulting host network. We developed integer linear programming (ILP)-based methods for BRM, and compared with OptStrain and SimOptStrain. The results show that our method performed better for reducing the total number of added and removed reactions, while OptStrain and SimOptStrain performed better for optimizing the production of the target compound. Our developed software is freely available at “http://sunflower.kuicr.kyoto-u.ac.jp/~rogi/solBRM/solBRM.html”.
KW - algorithm
KW - Biochemistry
KW - Bioinformatics
KW - Biological system modeling
KW - Biomass
KW - Boolean model
KW - Compounds
KW - feedback vertex set
KW - flux balance analysis
KW - integer linear programming
KW - Mathematical model
KW - metabolic network
KW - Production
UR - http://www.scopus.com/inward/record.url?scp=85036502014&partnerID=8YFLogxK
U2 - 10.1109/TCBB.2017.2777456
DO - 10.1109/TCBB.2017.2777456
M3 - Article
VL - 15
SP - 1853
EP - 1862
JO - IEEE/ACM Transactions on Computational Biology and Bioinformatics
JF - IEEE/ACM Transactions on Computational Biology and Bioinformatics
SN - 1545-5963
IS - 6
ER -